From the first machine-language programs to modern development environments, computing has always sought to hide technical complexity in order to let business logic shine through. This quest for abstraction led us from assembly languages to high-level languages, then to frameworks, and today to low-code.

By encapsulating authentication, data management, user interface and APIs into visual components, low-code offers a “higher level of visual programming.” It’s more than a fad: it represents the next major step in software abstraction, capable of redefining speed, governance and collaboration in application creation.

From Assembly to Low-Code: A History of Abstraction

The logic of abstraction hides technical details so you can focus on business value. Low-code pushes this principle to the extreme with drag-and-drop visual components.

Since assembly—where each instruction corresponds to an executable byte—readability and writability have been paramount. High-level languages (C, Java, Python) freed developers from manual memory management and register scheduling, letting them focus on algorithms and data structures.

Low-code brings that abstraction into graphical interfaces: each preconfigured block integrates authentication, persistence, security and UI. The platform orchestrates lifecycles, unit testing and continuous integration.

Beyond a technical evolution, it’s a cultural shift: visual programming becomes accessible to non-technical users while giving IT teams the power to calibrate industrialization, DevOps and security to suit their needs.

Principles of Software Abstraction

Abstraction separates business logic from underlying hardware and software resource management. By hiding runtime environment details (OS, database, network), it frees developers to concentrate on functional value.

Persistence frameworks, or Object-Relational Mapping (ORM), pioneered this concept in high-level languages. They automate translating business objects into SQL queries and ensure transactional consistency.

More recently, containers and orchestration (Docker, Kubernetes) have generalized infrastructure abstraction, deploying isolated, scalable workloads under continuous supervision.

Low-Code: Abstraction Taken to the Extreme

Low-code platforms centralize data models, business rules and interface design in a single visual studio. Each component embeds security best practices, REST API patterns and automated testing mechanisms.

With preconfigured connectors (ERP, CRM, Single Sign-On), they drastically reduce prototyping time. Developers assemble blocks, deploy with one click and benefit from a managed infrastructure—SaaS or on-premise—according to sovereignty and compliance needs.

This level of abstraction does raise questions about customization limits and dependency on platform evolution, underscoring the importance of rigorous governance and a technology choice aligned with long-term strategy.

A New Level of Visual Programming

Low-code doesn’t replace hand-coding; it complements it by offering a high-level visual interface while still allowing custom code insertions for specialized requirements.

In a modular ecosystem, a hybrid approach mixes open-source building blocks, bespoke microservices and low-code platforms. This strategy minimizes vendor lock-in and ensures scalability over the medium and long term.

Each visual abstraction relies on a metadata layer that feeds CI/CD, test generation and automated documentation—ensuring traceability and maintainability of the software product.

Example: Prototyping a Logistics Tracking Tool

An SME in the logistics sector deployed a collaborative order-tracking tool with automated notifications in just three weeks. Using low-code components, they integrated Single Sign-On to the intranet and a standard SQL relational database without tying up internal IT resources.

This project demonstrated low-code’s ability to cut prototyping time by 80%, ensure GDPR compliance and facilitate integration with the existing ERP system.

Impact of Low-Code Abstraction on Development Fundamentals

Development cycles can accelerate by up to 10× according to Gartner. Maintainability depends on strict citizen-developer contribution controls to limit technical debt.

Preconfigured environments and intuitive learning enable business teams to generate production-level applications in days. Gartner estimates low-code development is up to ten times faster than traditional frameworks.

However, perceived speed can mask hidden complexity: without governance, shadow-IT initiatives multiply application silos, generate technical debt and weaken security.

Speed and Delivery Acceleration

Low-code offers a catalog of ready-to-use templates and workflows. It cuts repetitive coding (CRUD, forms, reporting) and automates unit and integration tests.

Platforms natively include CI/CD pipelines. Staging and production deployments occur with one click and instant rollback. This velocity suits iterative projects and high-ROI proofs of concept.

Time saved frees IT teams for higher-value tasks: architecture, cybersecurity and advanced automation.

Maintainability and Technical Debt Governance

Ease of implementation can encourage proliferation of ad hoc applications. Without a centralized repository, each change or bug may trigger cascading incidents.

A low-code governance framework enforces naming conventions, versioning and testing rules. Process documentation and periodic component reviews ensure ecosystem quality and longevity.

Automated tracking of connector obsolescence and dependencies helps anticipate platform migrations and mitigate lock-in risks.

Contributor Roles and Stakeholder Profiles

Abstraction level determines creators: Citizen Developers speed prototyping, Business Analysts formalize requirements, and IT teams validate security and integration.

This cross-functional collaboration improves alignment between business needs and technical solutions. Co-creation workshops (design thinking) involve all profiles, fostering ownership and reducing back-and-forth.

Process industrialization relies on shared pipelines, where each stage (development, testing, acceptance) is measured by business performance and quality indicators.

Example: Billing Process Optimization

A financial services provider adopted a Business Process Automation platform to automate multi-entity billing. BPMN modeling enabled cascading approvals, automated reminders and regulatory report generation.

This initiative cut billing time by 60% and delivered real-time performance metrics without custom development.

Three Conceptual Paradigms of Low-Code

Low-code platforms fall into three main paradigms addressing different needs. Each approach shapes speed, flexibility and industrialization.

Depending on project nature and contributor profiles, you choose between UI-Driven, Business Process Automation or Data Model approaches. Each strikes a balance among simplicity, governance and extensibility. For more on these paradigms, see our article Low-Code vs No-Code: Quick Wins, Limits and Solutions.

Citizen Developer / UI-Driven Approach

Business-oriented, this approach provides a drag-and-drop graphic studio to design interfaces and navigation logic directly. Components include input controls, validation rules and report generation.

With a visual editor, business users can create interactive prototypes in hours, test them with end users and validate functionality before involving IT for scaling.

Ideal for intranet applications or support tools, this method emphasizes speed and simplicity at the expense of deeper customization.

Business Process Automation (BPA)

BPA platforms use BPMN to model business logic. They bridge process analysis and execution, delivering a HyperAutomation cycle coupled with process mining.

Each BPMN diagram becomes executable, with prebuilt connectors orchestrating human tasks, web services and scripts. Emphasis is on traceability, documentation and continuous optimization.

This approach suits organizations aiming to industrialize workflows, cut operational costs and derive insights from process logs.

Data Model Approach

Targeted at IT teams, this category combines a data-schema editor, a REST service generator and a CI/CD pipeline capable of deploying TypeScript, Java or .NET code.

Developers retain full control over data structures, security and API customization while enjoying the velocity of a low-code platform.

It’s ideal for high-volume, industrial-scale projects requiring automated testing, monitoring and advanced security policies.

Example: Industrial Quality-Tracking Application

An industrial manufacturer chose a Data Model platform to develop a quality-tracking system. Developers modeled data, created secure APIs and deployed automatically to a private cloud.

The project reduced production incidents by 40% and improved real-time reporting, while preserving the option to integrate additional open-source features.

Strategic Stakes of Low-Code

Paradigm choice must reflect digital maturity and internal skills. Dependency and scalability risks demand a governance and exit strategy.

Each low-code platform balances speed and autonomy, cost and flexibility. Strategic decisions rely on use-case analysis, data volume and internal capacity for change management. Low-code solutions should include code export or migration mechanisms to an open-source framework in case of contract termination or strategy shift.

Choosing a Paradigm by Digital Maturity

Organizations in an exploratory phase may favor UI-Driven for internal prototypes. As maturity grows, BPA or the Data Model approach deliver the needed industrialization and openness.

A digital maturity audit maps skills, processes and priorities, aligning platform choice with the IT roadmap and business ambitions.

This ensures measurable ROI and progressive upskilling of teams.

Risks: Lock-in and Scalability Limits

Adopting a proprietary platform can lead to vendor lock-in if you become overly reliant on exclusive connectors and components. Licensing and upgrade costs may become prohibitive over time.

Low-code solutions must offer code export or migration paths to an open-source framework in case of contract end or strategic pivot.

Finally, data governance and regulatory compliance (GDPR, ISO 27001) require fine-grained traceability of data flows and access.

Opportunities: Time-to-Market and Collaboration

Low-code significantly reduces time-to-market, enabling rapid testing of new offers and features. Cross-functional workshops bring business and IT together, fostering continuous innovation.

This method helps break down silos, empower Citizen Developers and strengthen end-user buy-in—the key to adoption and solution longevity.

By embedding security, accessibility and performance from the start, low-code becomes a strategic lever for digital transformation.

Toward a New Era of Augmented Development

Low-code doesn’t replace traditional development; it redefines its contours by offering an unprecedented level of visual abstraction. It accelerates delivery but demands structured governance, a fitting paradigm choice and an exit strategy to prevent vendor lock-in.

Mature organizations blend Citizen Developers, Business Analysts and IT teams within shared DevOps pipelines, combining modularity, open source and CI/CD.

Our team of open-source and agile experts is ready to help you craft the most relevant low-code strategy for your maturity level, business challenges and security-performance requirements.

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In an age of accelerated digitalization, the Banking as a Service (BaaS) model is transforming how banks operate and engage with their customers. By exposing their white-label banking infrastructure via APIs, financial institutions become technology platforms capable of delivering embedded financial services wherever they’re needed.

This shift represents a move from a product-centric approach to a strategy built around user experience and cross-industry collaboration. For IT and business decision-makers, understanding this paradigm is essential to seize the opportunities offered by embedded finance and remain competitive in a rapidly evolving ecosystem.

Definition and Mechanics of Banking as a Service

BaaS involves exposing banking services (accounts, payments, cards, credit) through APIs under a white-label arrangement. This infrastructure lets non-bank players integrate financial services directly into their offerings.

White-Label Architecture and APIs

The heart of BaaS lies in a robust, modular digital banking platform hosted and maintained by a licensed institution. It exposes REST or SOAP endpoints that simplify the integration of financial services into any application or website while ensuring security and compliance standards are met.

Each API is designed to be scalable and interoperable: KYC onboarding, account creation, e-wallet management, payment and card issuance and authorization, and real-time transaction monitoring. Data flows are encrypted and authenticated via OAuth2 or certificates, ensuring confidentiality and integrity.

Clear API governance and well-documented service catalogs facilitate adoption by development teams. Banks often provide developer portals with sandboxes, technical guides, and dedicated support to accelerate implementation and reduce friction.

Integration by Non-Bank Actors

BaaS paves the way for embedded finance, enabling retailers, SaaS platforms, utilities, or mobility operators to offer financial services without a banking license. These players act as front-end intermediaries, enriching their value proposition and retaining users with personalized, context-driven financial services.

For example, an e-commerce site can provide installment financing directly on its product page or create an e-wallet tied to a loyalty program.

The BaaS approach promotes the distribution of financial products through non-traditional channels, extending banks’ reach and strengthening customer engagement by delivering integrated, seamless experiences between partner platforms and the underlying banking system.

Why Traditional Banks Are Embracing BaaS

Faced with pressure from neobanks and Big Tech, traditional banks see BaaS as an opportunity to modernize their systems while diversifying revenue streams. The model drastically cuts customer acquisition costs and unlocks new markets through partnerships.

Lower Customer Acquisition Costs

The cost to acquire a customer via a BaaS channel often falls from $100–200 to $5–35, as financial services promotion leverages partner brands that already have customer trust and engagement. Banks can deploy targeted offers without bearing the full burden of marketing and technology expenses.

Partners handle communication, customer relations, and distribution, while the bank focuses on service optimization and operational management. This shared effort reduces time-to-market and improves ROI on digital projects.

Over time, BaaS enhances banking profitability, especially for low-value transactional segments, by minimizing front-end investments and capitalizing on ecosystem-driven volumes.

Accelerated Innovation Despite Legacy Systems

Traditional banks often struggle with rigid legacy systems that slow new feature rollouts. BaaS serves as an abstraction layer that shields the core banking system while providing an agile testing ground.

IT teams can deploy new APIs, integrate third-party services (scoring, AI, open data), and pilot offers in weeks rather than months. Quick feedback from partners and end users allows refining the offering before wide-scale launch.

This model fosters a “fail fast, learn fast” culture, where innovation is measured by usage and customer satisfaction rather than by lengthy internal project cycles.

Access to New Markets Through Ecosystem Logic

By embedding themselves in B2B2C platforms, banks expand geographically and sectorally without building branch networks. They partner with local players, specialized fintechs, or marketplaces to reach niche customers or underserved regions. As open banking democratizes access to financial data, banks can offer value-added services based on predictive analytics and personalization.

This embedded finance strategy captures revenue on every partner-initiated transaction without disproportionate fixed costs.

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Key Benefits of BaaS for Banks and Their Partners

BaaS accelerates innovation cycles and enhances customer experience by delivering native, seamless financial services. It also boosts competitiveness with a modular, scalable architecture.

Faster Innovation and Reduced Time-to-Market

BaaS APIs are built for rapid deployment of banking functionality: account opening, automated KYC, issuance of virtual or physical cards. Banks gain a ready-to-use development kit, minimizing design and integration phases.

Each new service can be tested with select partners before full production rollout. Feedback guides product evolution, ensuring precise alignment with business and regulatory requirements.

This accelerated innovation cycle revitalizes banks’ image and creates a virtuous circle: each successful use case enhances the BaaS platform’s credibility and attracts new partners.

Enhanced Customer Experience Through Seamless Integration

Embedding financial services directly within purchase or usage journeys eliminates channel breakpoints. Customers can access loans, make payments, or manage their wallets without leaving a retailer’s site or specialized SaaS application.

Personalization leverages partner behavioral data and the bank’s transaction history, delivering high-value contextual offers and notifications. The result is a more cohesive experience with fewer drop-offs.

Smoother UX drives higher conversion rates, greater customer satisfaction, and loyalty while reducing pressure on traditional support channels.

Increased Competitiveness and B2B2C Expansion

The B2B2C model shares development and infrastructure costs between banks and partners, while banks retain control over banking operations and sensitive data ownership.

Service modularity enables bespoke bundles for each customer segment or industry vertical, optimizing ROI per project. Simultaneously, cloud scalability ensures rapid capacity increases without technical bottlenecks.

For example, an insurance-focused SaaS provider integrated a split-payment and financial claims module, achieving a 30 percent transaction growth and improved customer retention by offloading front-end relationship management and relying on a robust banking back end.

Challenges to Address and Future Outlook

Implementing a BaaS model demands stringent security, compliance, and technical integration to maintain trust and service continuity. Banks must also rethink their customer engagement strategies.

Security and Regulatory Compliance

BaaS processes sensitive data in real time: personal information, financial transactions, credit scores. Every API call must comply with GDPR, PSD2, KYC, and AML requirements while guaranteeing exchange authenticity and integrity.

Institutions need monitoring, anomaly detection, and incident management mechanisms, plus end-to-end encryption. API logs, audits, and regular penetration tests are essential to validate system robustness.

Collaborating with security-conscious partners strengthens overall ecosystem resilience but requires clear governance and strict SLAs for each exposed service.

Technical Integration and Ownership of Customer Relationships

Ensuring API compatibility with legacy systems and existing middleware is a major hurdle. Banks often must adapt or migrate modules to achieve seamless interoperability without disrupting production.

Moreover, customer relationship management becomes more complex: the partner’s front end captures experience, while the bank remains the regulatory guarantor. Brand strategy and differentiation must be revisited to prevent dilution of the bank’s image.

A balance must be struck between platform openness and trust preservation, ensuring end users clearly recognize the banking institution as the protector of security and compliance.

The Future of Banking Brands and a Tech-First Stance

“Banking is necessary, banks are not,” as Bill Gates famously said. Banks must transform into open digital infrastructures, leveraging data and artificial intelligence to deliver proactive, personalized experiences.

The development of super-apps or integrated service suites—combining finance, commerce, and mobility—will help avoid disintermediation by FAANG or neobanks. These platforms will continuously add value through context-aware recommendations driven by real-time data analytics.

Finally, adopting open-source and microservices architectures will ensure scalability, agility, and independence from proprietary vendors, while retaining the trust and regulatory strengths that define banks.

Rethink Your Banking Positioning in the Digital Ecosystem

Banking as a Service doesn’t spell the end for banks—it signals their rebirth as trusted infrastructures at the heart of seamless digital ecosystems. By opening their APIs, mastering security, and embracing a platform-first culture, banks can accelerate innovation, enhance customer experience, and conquer new segments.

Our experts at Edana guide financial institutions in defining their BaaS strategy, implementing modular open-source architectures, and managing compliance and performance challenges. Together, let’s turn your digital ambition into a sustainable competitive advantage.

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Claims management is a strategic challenge for insurers, affecting settlement speed, cost control, and policyholder trust. Despite the rise of automation and artificial intelligence technologies, many players struggle to move from simple data-based reporting to a data-driven approach that orchestrates real-time decisions and delivers personalized journeys.

This article examines the three main obstacles – system fragmentation, limited fraud detection on unstructured data, and a lack of focus on customer experience – and then presents the levers for initiating a sustainable transformation. The goal: to combine operational performance, data reliability, and customer satisfaction.

System and Data Fragmentation

Proliferating application silos increase the number of interfaces and undermine process consistency. Heterogeneous data flows require complex connectors and slow down the implementation of seamless automation.

Application Silos and Rigid Interfaces

In many insurance organizations, claims workflows rely on legacy solutions and specialized software packages. Each component exposes its own APIs or export formats, forcing the creation of ad hoc connectors. This technical mosaic makes maintenance fragile and introduces failure points whenever a single version is updated.

The multiplication of ETL tools and transformation scripts increases latency and complicates monitoring. As a result, end-to-end task automation remains illusory without a unified orchestration layer. When an incident occurs, teams struggle to pinpoint the slowdown’s origin – database, message bus, or third-party service.

This domino effect means every new or upgraded component requires extensive regression testing, which slows deployment frequency and lengthens time-to-market for any claims process evolution.

Diversity of Data Formats and Sources

Claims generate a wide variety of data: structured forms, image files, free-form PDF reports, voice recordings, and IoT sensor streams. Without a single standard format, consolidation demands manual or semi-automated workflows that are resource- and time-intensive.

In the absence of a master data management (MDM) system, performance indicators for processing remain imprecise, compromising dashboard quality and the ability to make proactive decisions on cost control or detecting abnormal trends.

Impact on Time-to-Market and Service Quality

When data reconciliation is manual or semi-automated, the claims process lengthens, weighing heavily on customer experience. The average cost per file increases, even though rapid settlement has become a key differentiator in the sector.

Pilot projects that automate only a single service or format often fail to deliver expected gains due to the lack of a unified vision. Insurers see limited productivity improvements and persistently high error rates.

To deploy sustainable automation, it is essential to align the application architecture on a modular platform capable of accommodating new components and ensuring consistent exchanges without locking in the ecosystem.

Fraud Detection from Unstructured Data

Fraudulent claims involve varied, often unindexed data and require advanced analytical capabilities. Manual processes struggle to cover all subtle signals.

The Multiform Nature of Insurance Fraud

Fraud attempts take many forms: inaccurate declarations, imaginary major damage, falsified invoices, or duplicate billing. Supporting documents may be altered or compiled from different providers.

While some fraud is caught by simple rules (amounts exceeding a threshold), much of it relies on complex indicators: date inconsistencies, suspicious photo edits, or a mismatch between geolocation and the claim location.

The fluidity of these schemes prevents satisfactory coverage by a single set of static rules. Without semantic analysis and machine learning, fraudsters eventually exploit the gaps in traditional processes.

Limitations of Manual Processes and After-the-Fact Analysis

In many companies, document review is still done manually or relies on basic optical recognition scripts. This model relegates fraud detection to post-acceptance control, making it late and ineffective at quickly eliminating false positives.

Dedicated teams become overwhelmed whenever claim volumes surge, such as after a major weather event or large-scale incident. Controllers then face tough trade-offs that can allow risky cases to slip through.

Without an AI layer to automatically scan text, images, and metadata, late-detected anomalies generate follow-ups, calls, and sometimes disputes, all of which strain customer relations and raise handling costs.

The Role of AI in Analyzing Unstructured Data

Natural language processing (NLP) and computer vision models can now scan expert reports, identify inconsistencies, and rate document reliability in real time. AI classifies and prioritizes claims according to a risk score.

For example, a P&C insurer was still managing fraud detection through Excel by manually linking each element. After deploying an intelligent analysis engine, the share of high-risk claims doubled and manual reviews dropped by 30 %. This case shows that proactive detection gains both precision and speed.

An intelligent, modular automation approach can leverage these algorithms alongside business rules to trigger targeted investigations without burdening standard workflows, thereby improving control teams’ efficiency.

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Lack of Focus on Customer Experience

Claims journeys often remain siloed and opaque, generating frustration and dissatisfaction. Automation must also rest on an omnichannel, user-centric approach.

Customer Expectations and Industry Standards

Today’s policyholders expect real-time case tracking, clear notifications, and the ability to interact without delay. E-commerce and financial services set a high bar for responsiveness.

Without integrated interfaces, policyholders sometimes have to call a hotline, wait on hold, and provide the same information multiple times. This degraded experience fuels abandonment and harms the Net Promoter Score (NPS).

Leading insurers offer mobile apps with built-in chat, document management spaces, and interactive histories, while automatically orchestrating back-office processing steps.

Opaque Claims Journeys

When back-office infrastructure isn’t connected to the customer platform, every update requires a manual sequence: CRM entry, email dispatch, and portal update. This latency immediately impacts satisfaction.

Lack of visibility into claim status drives up inbound calls and emails, overloading support services and prolonging handling times.

Without automatic status updates, satisfaction surveys are skewed and corrective actions delayed, whereas proactive follow-up (push notifications, automated messages) reduces human intervention and boosts loyalty.

Portals and Chatbots: Steps Toward Autonomy

Self-service portals and chatbots capable of understanding basic inquiries cut redundant requests and enhance policyholder peace of mind. In a digitized journey, each step generates a trigger event for AI.

For example, an e-commerce platform implemented a multilingual chatbot for customer support. Its automatic resolution rate jumped by 40 % and status-related calls fell by 55 %. This initiative demonstrates that customer experience improves when automation is designed with the end user in mind.

By integrating these components with an intelligent workflow engine, the journey is personalized based on the policyholder’s profile and business rules, delivering contextualized communications (SMS, email, push) without manual intervention.

Deploying the Levers of Transformation

A data-driven approach, coupled with a modular architecture and reinforced data governance, is key to high-performance, scalable claims processing. AI and intelligent automation play central roles.

Intelligent Automation and Proactive Fraud Detection

By combining microservices for NLP and computer vision, it is possible to deploy continuous processing chains that evaluate every supporting document in real time. Predictive models instantly alert control teams to high-risk cases.

Using open-source frameworks (TensorFlow, PyTorch) ensures technological independence and eases model evolution as new fraud scenarios emerge. Integration into CI/CD pipelines allows rapid iteration on datasets and performance improvement.

This intelligent automation accelerates productivity, reduces false alerts, and frees teams to focus on the most complex cases while enhancing detection reliability.

End-to-End Integrated Vision and Modular Architecture

A claims processing platform should be conceived as a hybrid ecosystem, blending existing modules with custom developments. An event bus (Kafka, RabbitMQ) ensures exchange consistency between services and facilitates decoupling.

For example, a mid-sized manufacturing company restructured its architecture into microservices, isolating document management, amount estimation, and billing. This modularity reduced systemic incident times by 60 % and enabled rapid integration of new data-collection channels, demonstrating the efficacy of a unified vision.

Standardizing APIs and adopting contract-driven development (CDD) strengthen integration robustness and limit maintenance efforts while preventing vendor lock-in.

Data Governance and a Data-Driven Culture

Implementing a centralized data lake or data warehouse, combined with a data catalog and clear data governance rules, ensures information reliability and traceability. Every claim datum becomes an asset for predictive analytics.

Monthly committees bringing together IT, business units, and data experts prioritize key indicators (average settlement time, fraud detection rate, customer satisfaction) and fine-tune automation actions. This agile governance fosters a shared data culture.

Finally, training teams on analytics tools and promoting data ownership drive maturity, turning data into an innovation engine across the entire claims lifecycle.

From Transactional Handling to Proactive Engagement

Claims automation is not just about deploying bots or AI models: it requires a rethinking of architecture, solid data governance, and a policyholder-centric design. By overcoming system fragmentation, enhancing fraud detection, and placing user experience at the heart of transformation, insurers can achieve significant gains in productivity, reliability, and satisfaction.

Moving from a transactional model to proactive engagement demands a unified, modular, and scalable vision capable of continuously integrating new algorithms and communication channels. Edana’s experts guide organizations through this journey, from strategy definition to operational implementation, ensuring full technological independence and sustainable skill development.

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In an environment where data accumulation is accelerating, many organizations struggle to turn this volume into strategic advantages. Siloed systems, fragmented processes, and a lack of end-to-end visibility hinder innovation and slow down decision-making.

A modern data platform provides a technical and cultural framework to consolidate, govern, and exploit these assets. It serves as the foundation for democratizing information access and deploying cross-functional use cases. This article outlines the key steps to design this essential infrastructure, establish a data-driven culture, generate tangible value, and pave the way for artificial intelligence.

Defining a Modern Data Platform

A data platform unites the ingestion, consolidation, and governance of information from disparate systems. It ensures the quality, traceability, and security required to build a reliable and scalable data ecosystem.

Consolidation and Multi-Channel Ingestion

The primary mission of a platform is to collect data from diverse sources: ERP, CRM, IoT sensors, external partners, or line-of-business applications.

Consolidation involves storing data in a dedicated zone—often a data lake or a cloud data warehouse—where it is structured and time-stamped. This step prevents format inconsistencies and normalizes information before any processing. A data catalog documents the provenance, frequency, and context of each dataset.

One financial services institution implemented a Kafka pipeline to ingest transaction data and market indicators simultaneously. This centralized collection, combined with a scalable architecture, reduced the delivery time for regulatory reports from several days to just a few hours.

Governance and Data Quality Validation

At the heart of the platform lies governance, which defines privacy policies, transformation rules, and quality indicators. Data lineage processes document each step in a data’s journey, from the source system to final consumption. This traceability is crucial for meeting regulatory requirements and quickly restoring data integrity in case of an incident.

Quality metrics—such as completeness, consistency, and freshness—are calculated automatically at each ingestion cycle. Monitoring dashboards alert teams to any deviation, ensuring rapid remediation. A shared repository of business definitions prevents ambiguity and duplication.

The governance structure should involve a dedicated team (data office) and business stakeholders. Together, they prioritize critical datasets and oversee cleaning or correction initiatives. Effective governance minimizes the risk of using incorrect data in strategic analyses.

Interoperability and Access Control

An open platform relies on API standards and protocols like REST, GraphQL, or gRPC to expose data securely. Interoperability eases the integration of web services, notebooks for data scientists, and third-party AI solutions. A microservices model allows each component to evolve independently without impacting the entire system.

Access control is enforced through centralized authentication (OAuth2, LDAP) and role-based access policies (RBAC). Each user or application can access only the datasets they’re authorized for, strengthening security and ensuring compliance with privacy regulations. Activity logs maintain full traceability of all requests.

Fostering a Data-Driven Culture

Platform success depends not only on technology but on team buy-in and skill development. A data-driven culture is built on a common language, shared processes, and collaborative governance.

Promoting Data Literacy

Data literacy refers to each employee’s ability to understand, interpret, and leverage data. This skill is cultivated through tailored training, hands-on workshops, and internal educational resources. The goal is to foster autonomy and avoid creating new silos.

Continuous training programs—combining e-learning modules and in-person sessions—address the specific needs of both business and technical users. Data champions, serving as internal ambassadors, provide on-the-ground support to facilitate tool adoption.

Aligning Business and IT Language

A common language is anchored by a shared glossary, where each business concept (customer, order, product) is precisely defined. This consistency is captured in a data dictionary accessible via the platform. Co-design workshops bring together business leaders and data architects regularly to validate these definitions.

Adopting a layered model—where business semantics are separated from the raw layer—facilitates evolution. Data transformations and aggregations are documented in logical views that are directly understandable by non-technical users.

Collaborative Governance and Agile Rituals

Collaborative governance relies on cross-functional committees, bringing together IT, data owners, and business representatives. These bodies meet periodically to prioritize needs, adjust pipelines, and monitor quality indicators.

Agile rituals, such as monthly “data reviews,” enable teams to reassess priorities and share best practices. Data request tickets are managed in a common backlog, providing visibility into the status of each project.

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Creating Cross-Functional Use Cases

Beyond concepts, a platform is judged by the value it generates in real-world use cases. It accelerates time-to-market, improves operational efficiency, and fosters cross-functional innovation.

Single Customer View for Services

The Single Customer View (SCV) aggregates all customer interactions with the organization across every channel. This unified perspective enables personalized experiences, anticipates customer needs, and enhances the reliability of marketing campaigns.

A digital team can deploy automated workflows to propose tailored offers based on each customer’s history and profile. Processing time shrinks from days to minutes thanks to near real-time analysis.

An e-commerce company demonstrated that an SCV built on a cloud platform reduced churn by 25% and accelerated new marketing campaign launches by 40%.

Predictive Maintenance in Industry

Collecting machine data (temperature, vibration, pressure) combined with maintenance history enables proactive failure prediction. Analytical algorithms detect early warning signals of malfunctions, scheduling maintenance at the optimal time.

This approach prevents unplanned downtime, optimizes production line availability, and lowers repair costs. Technical teams can concentrate their efforts on high-value interventions.

A manufacturing site showed that a predictive maintenance solution decreased downtime by 20% and extended the lifespan of critical equipment.

Product Innovation and Cross-Functional Collaboration

R&D, marketing, and operations teams can rely on shared datasets to design new services. Direct access to secure data pipelines accelerates prototyping and reduces dependencies on IT.

Internal hackathons leverage this data to generate disruptive ideas, later validated through proofs of concept. The platform provides a controlled environment where each experiment maintains traceability and governance.

Connecting Data and AI

High-performing AI relies on reliable, well-structured, and accessible data. The data platform lays the foundation required to deploy robust, scalable models.

Ensuring AI Dataset Quality

AI projects demand labeled, consistent, and balanced datasets. The platform offers workflows for preparation, cleansing, and annotation. Automated feature engineering pipelines extract relevant variables for modeling.

Traceability of training data and model parameters ensures reproducibility and auditability. Models can evolve continuously while adhering to compliance requirements.

Data Architectures for Machine Learning and Deep Learning

The architecture must separate raw, preparation, and production storage zones. Staging areas orchestrate training cycles, while a data warehouse serves analytical queries for performance monitoring.

MLOps frameworks (TensorFlow Extended, MLflow) integrate with the platform, automating model deployment, monitoring, and updates. Scoring APIs expose predictions to business applications.

Democratizing Access and Driving Industrialization

Providing collaborative spaces (notebooks, sandboxes) and self-service APIs encourages data scientists and domain engineers to develop and test new algorithms.

Project templates and model catalogs facilitate the reuse of best practices and accelerate industrialization. Built-in approval processes ensure compliance and security.

Unleash the Potential of Your Data

Implementing a modern data platform, fostering a shared culture, and delivering concrete use cases transforms data into a lever for innovation and competitiveness. It provides a solid foundation for AI and advanced analytics.

Whether you aim to improve decision-making, optimize operations, or create new services, this integrated approach adapts to any context. Our experts are ready to guide you through designing, deploying, and adopting your data-driven strategy.

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Web3 is no longer just a buzzword; it signals the start of a radical transformation in the banking sector. Traditional institutions now stand at a crossroads: embrace this revolution or risk being swiftly outpaced by more agile players.

With the rise of tokenization, the growth of decentralized finance, and high expectations from connected generations, every bank must assess its readiness. This article presents seven concrete levers to capitalize on Web3 right now while building a sustainable strategy. It is aimed at IT, operational, and executive teams intent on turning this shift into a lasting competitive advantage.

Seizing the Strategic Timing of Web3

Web3 is on the verge of an inflection point where experimentation gives way to mass adoption. Banks that have invested in crypto, distributed ledger technology, and tokenization will be at the forefront of the next growth wave.

Anticipating the Technological Shift

As blockchain infrastructures transition from experimental to mature, timing becomes critical. Banks must identify the most promising use cases today to avoid missing the window of opportunity.

Falling behind means rushing to set up a robust technical foundation in a highly competitive environment. It is crucial to assess the scalability and resilience of DLT platforms to ensure seamless evolution.

Developing Web3 Skills In-House

Hiring or upskilling professionals who understand cryptographic, regulatory, and economic challenges is essential. IT teams must master the fundamentals of smart contracts, wallets, and asset tokenization before client demand becomes exponential.

At the same time, educating business units on these new technologies will facilitate alignment between strategic vision and operational execution, preventing silo formation that can hinder innovation.

Assessing and Modernizing the Existing Architecture

A rigid or centralized architecture may prove incompatible with Web3’s distributed nature. It is therefore crucial to analyze the modularity and openness of the current IT ecosystem.

Banks should plan for bridges between their core banking systems and public or private blockchain networks. Adopting a hybrid approach, combining open-source components with custom development can limit vendor lock-in and ensure controlled scalability.

Modernizing the Banking Offering with Crypto and DLT

Introducing comprehensive crypto services and automated internal processes now is a key differentiator. DLT can reduce IT costs while enhancing transparency and security in operations.

Comprehensive Crypto Services

Secure digital wallets, custody services, staking, and trading are becoming standard banking offerings. Providing a single platform where clients can buy, hold, lend, or sell crypto-assets simplifies the experience and attracts new clientele.

Automated tax management via integrated smart contracts ensures built-in compliance, reducing the risk of errors and fines. This fiscal transparency builds trust with regulators and clients alike.

For example, an e-commerce platform launched a custody-based crypto service. This project demonstrated that an institution can offer a secure and user-friendly experience while strengthening regulatory responsibility through on-chain transaction tracking.

Internal Efficiency Through DLT

Private or consortium blockchains facilitate automation of business processes: settlement processing, account reconciliation, and document management. Business process automation eliminates manual tasks and multiple approval delays.

By minimizing human intervention, banks achieve significant back-office cost savings. Operational responsiveness increases, reducing error risks and enhancing client satisfaction.

Tokenization of Financial Assets

The ability to fractionalize real-world assets (bonds, securities, fund shares) into tokens opens access to a broader pool of investors. Financial and geographical barriers fall, creating new revenue streams.

Tokenization also streamlines the issuance process by automating compliance and distribution via smart contracts. Issuance and management costs are thus drastically reduced.

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Anticipating Emerging Use Cases: NFTs, the Metaverse, and Regenerative Finance

NFT custody, metaverse presence, and regenerative finance present immediate opportunities to engage Gen Z and Gen Alpha. These new universes offer enriched client relationships aligned with sustainable values.

NFT Custody

Offering a secure custody service for non-fungible tokens meets growing demand from professionals and collectors. Banks can capitalize on the expansion of the unique digital asset market.

Implementing a dedicated interface backed by insurance guarantees enhances trust and positions the bank as a go-to player in this innovative segment.

For example, an institution developed a digital vault for NFTs, ensuring full traceability of transactions. This initiative proved that banks can become trusted custodians in the on-chain art and culture space.

Metaverse Presence

Virtual spaces provide new touchpoints to engage younger generations. Fintechs and banks can host conferences, investment simulations, or interactive events without geographical constraints.

Regenerative Finance (ReFi)

Tokenizing carbon credits or sustainable project units allows clients to directly participate in on-chain verifiable ESG initiatives. Each transaction guarantees immutable traceability of environmental commitments.

Offering blockchain-based green financial products strengthens the bank’s sustainable strategy credibility and creates a new attraction lever for responsible investors.

Strengthening Client Engagement and Building a Hybrid Financial Ecosystem

Blockchain-based loyalty programs and planning for a multichain future solidify an image of innovation and long-term resilience. Proactive regulation management and technological partnerships ensure the sustainability of this transition.

Blockchain-Based Loyalty Programs

Converting loyalty points into tokens exchangeable across multiple platforms enriches the client experience. Traceability allows verification of reward origins and usage, enhancing transparency and personalization.

Exclusive benefits such as early access to new products can be issued as privilege NFTs, boosting engagement and retention.

For instance, a banking cooperative deployed a loyalty program using ERC-20 tokens. This solution achieved a 30% higher reward usage rate than a traditional system while providing full visibility into the client journey.

Building a Multi-Chain Ecosystem

Preparing for a financial future where value moves across multiple blockchains requires implementing inter-network bridges and interoperability standards.

This hybrid approach, combining public and private networks, offers flexibility and security while avoiding reliance on a single technology or vendor.

Managing Regulation and Technological Partnerships

The implementation of the Markets in Crypto-Assets (MiCA) framework in Europe and specific regulations in Switzerland requires banks to integrate compliance from the design phase of Web3 services. Smart contracts must include native KYC/AML mechanisms to meet regulatory requirements.

Collaborating with blockchain consortia, specialized fintechs, and open-source providers ensures access to best practices and rapid adaptation to legislative changes.

Turning Your Web3 Transition into a Competitive Advantage

Web3 presents a unique window of opportunity to create new revenue streams, modernize internal operations, and validate your institution’s sustainable commitment. The seven levers outlined here enable immediate action while preparing for a secure, scalable hybrid financial ecosystem.

No matter your maturity level, you are not alone in this transformation. Our experts assist in identifying priority use cases, implementing modular architectures, and proactively managing regulation. Launch your Web3 strategy today and be ready to capture tomorrow’s growth.

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The shift to digital payments must leave no one behind. Those over 65 are less inclined to adopt mobile wallets, even as cash and check usage declines sharply.

For banking institutions, the challenge is two-fold: ensuring financial inclusion for seniors while strengthening their loyalty against competition from neobanks and Big Tech. Designing “senior-first” solutions requires a streamlined, coherent UX approach, tailored security mechanisms, and a testing phase that directly involves senior users to guarantee adoption and retention.

Understanding the Adoption Gap and Its Stakes

Those over 65 adopt mobile wallets at a significantly slower pace than 35–50-year-olds. This lag coincides with the gradual disappearance of cash and check payments.

For banks, this creates a dual imperative: maintain financial inclusion for senior clients while reinforcing customer relationships in the face of new digital players.

A Generational Divide in Wallet Usage

Seniors’ adoption of electronic wallets remains timid, often hindered by perceived app complexity and fear of mistakes, as highlighted in our article on UX practices.

Those over 65 still favor cash or checks—methods considered more tangible and within their control. This preference exposes banks to the risk of customer attrition if accessible digital alternatives aren’t offered.

Without an adapted offering, banks risk losing market share in the senior segment—historically loyal and profitable. Understanding the psychological and ergonomic barriers faced by this age group is crucial to designing an inclusive user experience.

Financial Inclusion: A Regulatory and Social Imperative

The gradual phase-out of cash compels banks to guarantee payment service access for all customer segments. Regulators encourage financial inclusion through frameworks like the Payment Services Directive 2 (PSD2), as discussed in our article on modern KYC.

Ensuring a successful digital transition for seniors promotes social cohesion and economic stability. By designing simple, secure wallets, institutions reassure this clientele about the reliability and confidentiality of their transactions—meeting both regulatory and social demands.

In this context, banks’ role goes beyond providing payment tools: they must offer dedicated guidance and support to avoid digital exclusion and maintain senior users’ trust.

Building Loyalty Amidst New Entrants

Neobanks and Big Tech focus on playful, ultra-simplified interfaces, pushing traditional banks to rethink their mobile payment solutions. Seniors are a valuable segment, with often more stable deposit volumes and higher advisory service needs. Banks that fail to meet ergonomic standards risk losing this long-standing clientele.

Strengthening senior loyalty hinges on trust and everyday ease of use. A well-designed wallet secures the bank-customer relationship by offering clear journeys and tailored support. Absent this, senior users may turn to more agile players or abandon mobile services altogether, undermining the overall customer relationship.

Implementing a targeted incentive and digital training program enhances the perception of proximity and professionalism, contributing to long-term mobile wallet adoption.

Designing a “Senior-First” Wallet

The interface must be simple, legible, and guided, with optimal consistency across iOS and Android. Journeys should be intuitive, minimizing complex gestures and featuring generously sized buttons.

Security relies on adapted multi-factor authentication, favoring biometrics while offering a clear, accessible PIN fallback.

Simplified, Consistent Interface

For seniors, each screen should focus on a single action, avoiding nested menus and non-descriptive icons. Font size should be at least 16–18 pt with high contrast to facilitate reading, in line with WCAG 2.2 standards. Touch targets of at least 44 px should be placed within thumb reach and explicitly labeled.

Consistency between iOS and Android versions builds trust: senior users will recognize the same visual and functional cues regardless of device. Transitions and animations should be kept minimal to avoid confusion and distraction.

One regional bank developed a senior-first wallet prototype with enhanced contrast and oversized buttons. In testing sessions, 85% of seniors completed a transfer without external assistance, demonstrating the effectiveness of a streamlined, coherent interface.

Adapted Security Mechanisms

Implementing progressive strong authentication (2FA) starts with biometrics (Face ID, Touch ID) for quick access without memorizing passwords. If biometric enrollment fails, a simplified PIN on a high-contrast numeric pad provides an accessible fallback.

The biometric enrollment process should be guided step by step, with clear explanations about data privacy. Error messages must use plain language, detailing how to resolve the issue without technical jargon.

This user-friendly security approach helped a pension fund reduce connection-related support calls by 60%, proving that combining biometrics with a well-designed PIN fallback boosts adoption without compromising security.

User Testing from the Prototype Phase

Involving seniors from the prototyping stage ensures the app meets their needs and quickly identifies friction points during user acceptance testing. Observation workshops and real-life test sessions validate critical journeys (balance check, transfer, payment) before costly development.

Live observations often reveal misunderstandings of icons or labels and highlight preferences for supplemental text or verbal explanations. These early insights allow for refining information hierarchy and improving the integrated step-by-step guide.

During prototyping, a cantonal bank found that a three-step interactive tutorial reduced navigation errors among seniors by 40%, underscoring the importance of co-design and early user testing.

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Technical Foundations and Performance

The architecture must be modular, PSD2-compliant, and guarantee end-to-end encryption with anti-fraud mechanisms tailored to senior usage. The solution should remain scalable to keep pace with evolving standards.

Compatibility with older devices, telemetry for detecting friction, and feature flags enable continuous experience optimization and responsive support.

Flexible, Compliant Architecture

Adopting a native component–based architecture for iOS and Android ensures optimal performance and direct access to biometric APIs, supported by an API-first integration for scalable, secure IT architectures.

PSD2 compliance requires managing clear authorization scopes and consents, stored securely. Transactions are encrypted end to end, while AI algorithms analyze real-time payment anomalies specific to seniors (e.g., unusually large transfers).

Performance and Backward Compatibility

To ensure access for seniors with older devices, the app must be optimized for operating systems three to five years old, using proven methods for resolving performance issues or bugs in enterprise software. Critical features load first, and heavy libraries are replaced with lighter alternatives.

Built-in telemetry tracks success rates on key screens, identifies slowdowns, and measures user behavior. Feature flags facilitate phased rollouts of new features to a small senior panel before global deployment.

In-App Accessibility and Support

The wallet must adhere to iOS and Android accessibility standards (VoiceOver, TalkBack) and respect system preferences like enlarged text or dark mode. Reminder pop-ups and a “risk-free demo” mode offer gradual learning.

A step-by-step tutorial system with annotations and visuals guides users through each stage. Errors are met with immediate feedback and the option to cancel or go back without data loss.

Key Features and Success Metrics

High-value features for seniors include a simplified mode, two-tap recurring payment workflows, and quick-access assistance. Transparent, reassuring security complements the offering.

Tracking KPIs such as wallet activation rates for 65+, time to first payment, and 30/90-day retention measures effectiveness and enables continuous adjustment.

Simplified View and Guided Rituals

The “Essential Mode” immediately displays the balance, latest transaction, and a “Pay” button—without information overload. These features boost customer loyalty by providing short, explicit workflows.

Guided rituals—such as invoice sharing or group payments—are packaged into brief flows without multiple screens. Senior users feel supported and can complete transactions in just a few taps.

This approach led to a significant increase in seniors’ first payments, demonstrating its direct impact on adoption.

Reassuring Assistance and Security

An “Call My Advisor” button and priority chat offer immediate human support. A one-tap “Lock Card” feature is highlighted with a clear icon and reassuring confirmation message.

Alerts for unusual transactions are clear and contextualized, with immediate action options. Personalized limits allow setting security thresholds tailored to individual habits.

This strategy reduced reported fraud incidents among seniors by 35%, proving the effectiveness of accessible, proactive security.

KPI Tracking and Performance Monitoring

Key metrics include wallet activation rate for users 65 and over, time to first payment, and success rates of critical journeys (transfer, payment, balance check). These reveal friction points to address quickly.

Monitoring drop-off rates by screen and support calls by issue highlights areas needing UX adjustments or clearer functionality. Thirty- and ninety-day retention, along with the senior NPS, gauge long-term satisfaction and loyalty.

By combining these KPIs with periodic surveys, banks can refine their product roadmap and continuously strengthen their relationship with senior clients.

Turning Your Wallet into a Senior Loyalty Engine

Adopting a “senior-first” approach for your mobile wallets is a strategic opportunity: inclusion, security, and satisfaction converge to reinforce senior customer loyalty. By focusing on a clean interface, tailored security mechanisms, modular architecture, and rigorous KPI tracking, you’ll meet the expectations of a population that values simplicity and trust.

Our Edana experts support you in designing, testing, and deploying senior-ready wallets that combine performance, compliance, and optimal user experience. Together, let’s turn your challenges into sustainable loyalty opportunities.

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Since the advent of ATMs and mobile apps, the banking sector hasn’t stopped innovating technologically. Today, the race for features gives way to a new demand: user experience (UX). Institutions must prove that their digital journeys are not only reliable but also seamless, personalized, and engaging. Without this focus, brand image erodes and customers switch to neobanks or tech giants that place UX at the heart of their proposition. In this article, we explore why UX has become the number-one strategic lever in digital banking and how banks can rise to this challenge to win over new generations and strengthen trust among all users.

The Strategic Dilemma Banks Face Regarding User Experience

Traditional banks must choose between delivering an exceptional digital experience or risking increased customer attrition. Poor UX weakens brand image and puts them at a competitive disadvantage against neobanks.

From Technology to Feelings: The Critical Stake

For a long time, banking digitalization was all about adding channels: website, mobile app, chatbot… This approach ensures a digital presence but doesn’t guarantee satisfaction. Customers now evaluate every interaction based on intuitiveness, speed, and cross-channel coherence.

These criteria have become essential for loyalty. A complex onboarding process or a tedious authentication flow will discourage a customer, who will then turn to a competitor offering an optimized journey.

UX is no longer just a marketing asset but a key performance indicator. It influences not only service adoption but also the perception of an institution’s reliability and modernity.

Standards Set by Neobanks and Tech Giants

Players like a mid-sized Swiss cantonal bank found that even a slight delay in the design of mobile notifications led to a 20 % increase in support requests. This case demonstrates that smoothness directly translates into operational efficiency gains.

Neobanks have redefined expectations: a clean interface, near-instant verification processes, and built-in assistance. Tech giants minimize all perceived complexity by eliminating “friction points.”

To stay competitive, banks must align their UX standards with these new benchmarks and adopt a continuous improvement approach, integrating user feedback and iterative testing.

Reputational Risks and Business Impacts

Poor digital experiences generate frustration and distrust. Criticism spreads quickly via social networks and review platforms, damaging reputation and institutional trust.

From a financial standpoint, every lost customer represents not just forfeited recurring revenue but also increased acquisition costs to offset the loss.

Conversely, a pleasant banking journey encourages the uptake of additional services—savings, loans, advisory—creating a virtuous cycle of revenue and loyalty.

Engaging the TikTok Generation Through Gamification

Young customers expect instant, playful, and personalized interactions. Gamification emerges as a powerful lever to engage them sustainably.

Understanding Generation Z’s Expectations

Under-25s consume information on social media and demand interactive experiences. They value speed, transparency, and the social dimension of services.

These users are averse to lengthy forms or financial jargon. They appreciate clarity, spontaneity, and real-time feedback.

For banks, this means adapting the tone and format of interfaces: micro-interactions, dynamic visuals, and contextual messages enhance attention and engagement.

Gamification as an Engagement Driver

An experimental Swiss neobank introduced an animated “chat-guide” offering challenges and virtual rewards during account opening. The initiative increased completion rates by 35 %. This example shows how gamification can turn an administrative step into a playful experience.

Game mechanics—points, levels, badges—encourage exploration of services and foster loyalty. They also aid in understanding complex products like savings or loans.

By combining gamification with personalized recommendations, banks create an ongoing dialogue, boosting both app usage time and the adoption of new features.

Integrating Gamification into the Customer Journey

Successful gamification integration requires detailed analysis of key journey stages: onboarding, feature education, and regular usage.

It’s crucial to calibrate challenge difficulty and reward value to balance fun and utility. A system that’s too simple loses its appeal; one that’s too complex discourages users.

Finally, gamification must serve a clear business objective: acquisition, activation, or retention. Cross-functional governance—uniting UX, marketing, and security teams—ensures a coherent approach.

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Designing an Inclusive and Accessible Digital Bank

Accessibility is no longer a luxury but an ethical and regulatory requirement. Designing for all strengthens trust and expands the customer base.

Accessibility Standards and Regulations

Several international directives impose digital accessibility criteria for online services, including WCAG and eIDAS in Europe. These standards aim to ensure access for individuals with disabilities.

Complying with these requirements reduces the risk of penalties and demonstrates a bank’s social commitment. It also improves the experience for all users.

A proactive approach integrates accessibility from the design phase, with regular audits and automated validation tools.

User Testing with Disabled Customers

A mid-sized institution in French-speaking Switzerland organized co-design workshops with visually impaired and hearing-impaired users. These sessions uncovered button labeling issues and insufficient contrast, which were then fixed in the final version.

This case highlights the importance of real-life testing to uncover unexpected challenges and improve usability.

Feedback from these user groups forms the basis for internal guidelines, ensuring continuous accessibility consideration in every update.

Benefits of a Universal UX

An accessible interface is clearer and simpler for everyone: better contrast, coherent navigation, and explicit labels. These qualities reduce dropout rates and support requests.

Inclusion enhances brand image and creates a competitive edge, especially with companies focused on Environmental, Social, and Governance (ESG) responsibility and compliance.

Ultimately, investing in accessibility yields operational savings and opens doors to new customer segments.

Personalization, Trust, and the Evolution Toward a True Banking Experience

Intelligent and responsible data usage becomes the key to personalization under the lens of security and consent. The goal: turning the bank into a financial companion.

Information Security and Identity Management

Trust is built on data protection and robust authentication mechanisms. Multi-factor authentication (MFA), end-to-end encryption, and precise role management ensure confidentiality.

A Swiss cantonal group deployed a unified identity management system providing secure Single Sign-On across all services. This example illustrates how centralization enhances experience while reinforcing security.

Access governance must be dynamic, with continuous monitoring and periodic reviews to prevent internal and external risks.

Consent-Based Open Banking and Digital Twins

Open banking offers advanced personalization opportunities, provided explicit customer consent is upheld. Open APIs enable integration of third-party services while maintaining data control.

The digital banking twin concept creates a digital replica of the customer profile to simulate personalized financial scenarios without exposing raw data. A Swiss fintech tested this model by offering budget forecasts based on a digital twin, demonstrating relevant recommendations without sharing sensitive information.

This approach builds trust and encourages adoption of value-added services while preserving privacy.

From Digital Bank to a Differentiating Banking Experience

Institutions that focus on UX secure a sustainable competitive advantage. By placing the user at the center—through gamification, accessibility, personalization, and security—they meet new generations’ expectations while strengthening trust among all customers.

This approach relies on modular, open-source, and scalable solutions tailored to the business context. Seamless and inclusive journeys translate into higher service adoption and better retention.

Our experts are ready to support your institution in defining and implementing your UX strategy to turn every interaction into an opportunity for growth and trust.

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The insurance industry is under mounting pressure: digital competitors, customer demands for hyper-personalization, and cost-control imperatives are driving traditional carriers to reinvent their business models. In this context, the Internet of Things (IoT) has emerged as a differentiation catalyst, unlocking new revenue streams and enhancing risk prevention.

Insurers are progressing through multiple levels of IoT integration—from simple connected gadgets to fully autonomous ecosystems. These solutions naturally align with emerging trends such as parametric insurance, pay-as-you-go models, or embedded finance, paving the way for a proactive, data-driven customer relationship.

IoT to Enhance Customer Service

First-tier IoT improves the customer experience and loss prevention through basic connected devices. These solutions boost retention while reducing incident-related expenses.

Home Sensors for Loss Prevention

Connected humidity and smoke sensors provide immediate alerts in case of danger, limiting damage scope and repair costs. Their installation is often straightforward and modular, catering to needs ranging from individual homes to commercial premises.

By configuring alert thresholds to suit the context, these sensors also build trust among policyholders, who come to view their coverage as a value-added service rather than just a claims tool.

For the insurer, real-time alarm monitoring streamlines intervention management and supports negotiations for local emergency service partnerships. Integration into the customer portal further reinforces a proactive, transparent relationship.

To learn more, see our automation of business processes with AI.

Wearables for Health Monitoring and Prevention

Connected watches and fitness bands continuously track cardiovascular metrics, activity levels, and sleep patterns. With this data, insurers can offer personalized wellness programs and tailored health advice.

Beyond mere data collection, analyzing lifestyle habits helps identify risk trends and send preventive notifications (activity reminders, nutritional tips) before complications arise.

These devices boost policyholder engagement by transforming a passive arrangement into an active health partnership. They lay the groundwork for customizable offerings based on real-time behavior indicators.

Vehicle Fleet Monitoring

Telematics units connected to commercial vehicles transmit driving data—speed, braking, acceleration, and routes—to a shared dashboard for both the insurer and the client company.

With these insights, fleet managers can pinpoint risky behaviors and launch targeted training programs. The insurer, in turn, refines the risk profile and can offer dynamic discounts or add-on services, supported by understanding APIs for connecting your systems.

One transportation company equipped its fleet with OBD-II sensors and reduced claims by 15%.

Leveraging IoT Data to Refine Offerings

At the next level, IoT becomes a source of massive, real-time data. Insurers tailor their products and reward responsible behavior.

Dynamic, Granular Pricing

Continuous data collection enables precise pricing, adjusted according to actual usage or prevention levels achieved. Policyholders see tangible benefits when they adopt safer practices.

By combining IoT data streams with scoring algorithms, insurers automatically recalibrate premiums, delivering greater transparency and minimizing renewal-time surprises.

One auto insurer trialed a parametric pricing model based on the usage frequency of smart home heating devices, resulting in a 20% increase in customer satisfaction and a measurable drop in maintenance-related claims.

Behavior-Based Loyalty Programs

IoT platforms power reward schemes with tiers tied to policyholder adherence to best practices. Coupons, discounts, or complementary services encourage preventive measures.

A mobile app synchronized with connected devices tracks real-time goals (daily step counts, tire-pressure checks, leak detection). Each milestone unlocks a tangible benefit.

These programs deepen customer relationships and foster a virtuous cycle of prevention and reward, while feeding the CRM for more targeted campaigns.

To structure your IoT data, consult our guide on data wrangling.

Behavior-Based Risk Management

Insurers incorporate IoT indicators into their risk management solutions to anticipate claims and adjust reserves. Predictive models enriched with granular data improve forecast accuracy.

Centralized data streams enable proactive control: when an anomaly is detected, an alert is sent to the policy administrator or approved repairer, limiting claim scope.

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Building Interconnected IoT Ecosystems

The third level involves collaborative platforms among insurers, manufacturers, and service providers. Data sharing spawns new services and streamlines the value chain.

Collaborative Claims Management Platforms

Shared portals aggregate IoT data, repair histories, and service schedules. Declaration and handling processes occur in real time, cutting both delays and costs.

Insurers can delegate certain tasks to certified partners while maintaining full visibility over the claim cycle, instantly boosting operational efficiency.

Integrated Partnerships with Automotive Manufacturers

Vehicle data captured at the factory or on the road feed after-sales services bundled with insurance. Predictive maintenance and mileage-based guarantees become packaged offerings.

Manufacturers gain a comprehensive view of the product lifecycle, while insurers strengthen their presence throughout vehicle usage. This deep-tech alliance accelerates the time-to-market for new services.

IT and Device Interoperability

To enable data sharing, platforms adopt open standards and standardized APIs, avoiding vendor lock-in and allowing each player to freely connect their services.

Microservices architectures orchestrate IoT streams and ensure security by isolating business contexts. Modular components simplify evolution and the onboarding of new partners. Discover our article on middleware.

Intelligent Automation of IoT Processes

The final tier features autonomous systems that detect, command, and trigger actions without human intervention. IoT becomes truly actuative and proactive.

Automatic Incident Detection and Response

With embedded AI, certain sensors automatically detect imminent incidents (pipe bursts, fires, intrusions) and immediately alert a monitoring center.

Orchestration scripts then dispatch teams or automatically lock down critical systems, limiting damage. Continuous monitoring feeds models that refine themselves with field feedback.

One municipality activated a motorized valve to reduce water loss by 70% during a pipeline incident.

For deeper insight into AI’s impact on claims management, read our article on insurance and automation.

Autonomous Predictive Maintenance

Connected industrial equipment reports performance indicators (vibration, temperature, current). Algorithms detect anomalies before they lead to major failures.

Intervention planning is now fully autonomous: workshop booking, spare-part procurement, and workforce scheduling are automated.

Robotic Interventions and Digital Twins

Drones or mobile robots, guided by real-time digital twins, can inspect and repair assets in hazardous or hard-to-reach environments.

These machines, linked to an IoT platform, execute predefined routines and report each step to enrich the model and automate future cycles.

Moving to Preventive, Data-Driven Insurance

Across these four maturity levels, IoT proves far more than a novelty: it becomes a lever for diversification and performance. Connected insurance can drastically reduce claims, enable real-time pricing adjustments, and build open ecosystems among partners. An experimental approach—rapid prototyping, iterative development, and continuous learning—is the key to scaling beyond isolated pilots.

Our experts combine open-source solutions, secure modular architectures, and agile governance to support you at every stage. Whether you need to establish an IoT proof of concept, integrate data streams, or deploy intelligent automation, we help you maximize ROI and ensure the sustainability of your initiatives.

To integrate your IoT devices with existing systems, read our guide on modernizing legacy IT systems.

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Co-creation represents a powerful alternative to acquiring off-the-shelf solutions or pursuing 100% in-house development, sharing risks, expertise, and ambition among stakeholders. By adopting this approach, you shape a product aligned with business challenges and benefit from an optimized time-to-market through fast, measurable delivery cycles. Edana’s co-creation methodology places product value at the heart of every stage—from initial scoping to scaling—through a robust architecture and user-centric design. This ensures full technological ownership and continuous, performance-driven evolution.

Explore: Strategic Scoping and Field Assessment

The exploration phase is essential for establishing a shared product vision. The field assessment identifies constraints, data sources, and regulatory requirements.

Value-Driven Ideation

During ideation, the business model and value proposition form the basis of every decision. Each proposed feature is explicitly linked to a business impact, ensuring the backlog’s relevance. Collaborative workshops foster a common vision and stakeholder alignment.

Scoping includes analyzing current processes and defining clear metrics. With validated performance indicators, the team can quickly trade off high-impact opportunities against development effort. This prevents scope creep and maintains focus on value.

The initial roadmap is organized into incremental releases, each delivering a viable, measurable product. Milestones are defined by added value, allowing the team to confirm adoption of early deliverables before further investment.

Field Assessment and Compliance

An audit of existing processes uncovers operational friction points and potential optimizations. Data flows are mapped, and sector-specific security or regulatory constraints are identified. This diagnosis is critical for risk anticipation and design governance.

Reviewing compliance requirements (GDPR, internal policies, industry standards) secures the architecture from day one. Integrating these aspects upfront avoids delays and costs associated with later modifications. Security standards guide technology and protocol choices.

The field assessment culminates in a detailed report with pragmatic recommendations. These findings steer the prioritization of initiatives based on their criticality and the organization’s digital maturity.

Value-Based Prioritization and Governance

Prioritization is achieved through scoring that balances business impact and technical risk. Each item is evaluated against collectively defined criteria, ensuring continuous alignment between IT, business units, and external partners. The backlog remains dynamic and transparent.

Joint governance combines steering committees with agile rituals. Regular reviews adjust priorities based on measured results and user feedback. This decision agility keeps objectives in focus.

Key performance indicators (KPIs) feed a shared dashboard, ensuring traceability of decisions and progress tracking. This visibility allows for early detection of budgetary or schedule variances.

Example: A Swiss transport organization struggled to consolidate data from multiple systems and meet security obligations. Through a thorough exploration phase, major data flows were mapped and regulatory requirements integrated from the outset. This case highlights the importance of a field assessment to scope a complex project and build stakeholder confidence.

Create: User-Centric Design and Incremental Delivery

This phase turns vision into tested prototypes, ensuring an optimal UX. Engineering is based on a modular architecture and continuous delivery of the Minimum Viable Product.

UX/UI Design and Prototyping

The design process relies on design thinking workshops with end users to refine user journeys. High-fidelity wireframes and prototypes undergo early usability testing to validate assumptions and reduce the risk of misalignment with real needs. This co-construction strengthens team buy-in.

Graphic and ergonomic choices align with the organization’s brand identity while ensuring intuitive navigation. Every interaction is analyzed to eliminate friction, with special attention to mobile and field contexts. Accessibility and responsive design are non-negotiable criteria.

Early test feedback fuels rapid prototype iterations. These short loops allow adjustments to information hierarchy and prioritize modules based on observed impact. User insights guide the functional roadmap.

Modular Architecture and Security by Design

The modular architecture is structured around microservices or independent modules, facilitating scalability. Each component is designed for individual deployment and scaling to avoid excessive coupling. Modern open-source technologies ensure maintenance freedom and limit vendor lock-in.

Security is integrated at the design phase: data encryption, infrastructure hardening, and systematic code reviews. Authentication protocols and access controls align directly with the regulatory diagnosis. This by-design approach minimizes future vulnerabilities.

Database schemas are optimized for variable loads and growing data volumes. Factory and caching patterns are adopted for performance, while log persistence traces every critical event.

Incremental Delivery and Impact Measurement

The MVP marks the first tangible milestone, delivered in a few short sprints. Usage indicators are continuously collected via customized dashboards, measuring adoption and satisfaction. This data-driven culture guides subsequent prioritization and validates each release’s ROI.

Enhancements follow a backlog prioritized by value and risk, adjusted at each demo. Stakeholders engage in sprint reviews, ensuring full transparency and ongoing control of development effort.

CI/CD pipelines automate unit and integration tests, significantly reducing validation cycles. Monitoring tools alert on performance or security regressions, enabling proactive incident management.

Example: As a subsidiary of a multi-sector services company, one client co-created a field platform for its technicians. By delivering an MVP in three months and tracking daily usage, the team optimized workflows and cut report entry time by 70%. This illustrates the power of incremental delivery and precise metrics to steer development.

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Grow: Governance, Automation, and Optimization

After the MVP, scaling up relies on an evolving roadmap and agile governance. Industrialization leverages CI/CD, automation, and cost optimization.

Roadmap and Governance

The product roadmap is based on collected KPIs and business feedback. It unfolds into planned releases, combining functional enhancements and technical improvements. Steering committees co-decide trade-offs, ensuring ongoing alignment between strategic objectives and delivery capacity.

Cross-functional governance engages business sponsors and technical experts in quarterly reviews. This collaborative dynamic ensures rapid adaptability to changing contexts and better anticipation of future needs. Decisions are documented and traceable.

Success criteria rely on quantifiable indicators (adoption rate, processing time, business ROI). This granularity allows low-value initiatives to be paused or adjusted, reallocating resources to high-impact features.

Industrialization via CI/CD and Automation

CI/CD pipelines orchestrate all build, test, and deployment steps, ensuring consistent, rapid delivery. Automated tests cover critical scenarios, reducing regression risks. Updates can be deployed to production multiple times per day.

Infrastructure as Code scripts standardize environment configuration, ensuring reproducibility and compliance. Automation workflows handle recurring tasks (migrations, deployments, backups), freeing teams for higher-value activities.

Continuous performance and security monitoring feed proactive alerts. Incidents are managed via integrated playbooks, minimizing downtime and ensuring robust SLAs. This rigor builds user trust and supports growth.

Cost Optimization and Extensibility

Cloud architectures leverage auto-scaling mechanisms to adjust capacity during peak loads. Unused resources are shut down to optimize operational costs, while instances are right-sized based on performance thresholds defined during diagnosis.

Microservice segmentation enables new features to be injected without affecting the entire system. Modules are packaged and deployed independently, facilitating enhancements and reuse. This approach also limits vendor lock-in.

A regular dependency update policy optimizes security and performance. Automated code reviews assess quality and standards compliance, preventing technical debt and preparing the product for unconstrained growth.

Example: A Swiss logistics operator saw its internal application evolve from an MVP to a full-fledged service in under a year. By automating tests and deployments, the platform increased its processing capacity by 200% while reducing infrastructure costs by 30%. This case underscores the importance of structured industrialization to sustain growth.

Collaborate Effectively: Roles and Responsibilities

Co-creation relies on a clear division of contributions and decisions. A shared cadence fosters engagement and goal achievement.

Business Expertise and Field Access

The internal partner brings in-depth process knowledge, strategic priorities, and daily usage insights. This business perspective guides feature definition and release sequencing. Field experts actively participate in workshops and validate prototypes.

Partner’s Strategic and Technical Contribution

The external partner contributes expertise in digital strategy, software engineering, enterprise architecture, and cybersecurity. They orchestrate sprints, ensure code quality, and manage technical risks, maintaining security by design.

With deep knowledge of open-source technologies and industrialization best practices, they propose scalable, modular solutions. They anticipate future needs and recommend adaptations to avoid vendor lock-in.

Shared Cadence and Value Management

Agile rituals (backlog refinements, sprint demos, retrospectives) involve all stakeholders, promoting transparency and engagement. Each deliverable is approved based on business value and technical quality criteria.

Joint governance uses clearly defined indicators to measure progress and impact. Prioritization adjustments are ratified in steering committees, ensuring continuous alignment with business objectives.

Regular communication and asynchronous collaboration tools maintain information flow between teams, reducing silos and speeding decision-making. This transparency is a key success factor in co-creation.

Transform Co-creation into a Growth Engine

Co-creation offers a unique balance of innovation, agility, and risk control. By exploring value first, creating through incremental deliveries, and industrializing with discipline, each product gains adoption, robustness, and autonomy. Clear role definitions and shared governance ensure effective collaboration and controlled scaling.

Our experts guide organizations through every project phase, from scoping to scale-up. They share their know-how in design, scalable architecture, cybersecurity, and digital strategy to turn your challenges into lasting success.

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The digital transformation is upending traditional banks today, particularly in the DACH region (Germany, Austria, Switzerland), which are confronted with the rise of agile neobanks and automated investment platforms. Fragmented IT systems and legacy processes too often hamper their ability to innovate and provide a seamless customer experience.

Yet, Swiss institutions are demonstrating that a platform-oriented IT strategy, together with an agile culture, AI and automation, can transform a banking service into a true technology enterprise. Rather than viewing IT as a mere cost center, banks should elevate it into a lever for growth and innovation. This article presents four key pillars to succeed in this transition and thrive in the software era.

Adopt an open and interconnected platform

An open banking platform makes it easier to integrate partners and launch new services. It places interoperability and innovation at the heart of your IT ecosystem.

API Management and Open Banking

APIs play a central role in opening up financial services. By exposing standardized interfaces, a bank can bring together fintechs, insurers, and payment providers to enrich its customer offering. This interconnectivity creates a network of value-added services without burdening the core of your legacy system.

Implementing a robust, secure, and governed API layer ensures controlled access to data and transactions. It meets regulatory requirements while fostering the agility needed for rapid partnerships. The API-first approach reinforces this strategy by placing interfaces at the core of design.

A mid-sized Swiss bank deployed an API catalog for its payment and credit services. This example shows that centralized governance, combined with a monitoring platform, reduced the time to implement third-party integrations by 40%, while ensuring traceability and compliance.

Fintech Partner Ecosystem

Beyond APIs, building a fintech partner ecosystem enables you to offer differentiated services without developing every component in-house. The marketplace model, or “third-party banking,” increases offering flexibility and lowers entry costs.

This strategy requires a modular platform capable of dynamically composing services from different providers. It implies an IT architecture designed to load, configure, and run external microservices securely.

A Swiss cantonal bank has been working for two years with several fintech startups on a loans and insurance marketplace. The example demonstrates that a common data repository and a sandbox platform accelerate innovation cycles, tripling the rate of new services in production.

Modular Infrastructure and Hybrid Cloud

Designing your infrastructure as independent modules—microservices, containers, and serverless functions—allows you to scale each component according to actual load. This optimizes costs and performance while ensuring increased resilience.

Using a hybrid cloud, combining local data centers and hyperscaler providers, offers the necessary flexibility without sacrificing data sovereignty. A phased rollout, orchestrated via CI/CD pipelines, ensures continuous quality control.

A Swiss financial institution segmented its core banking foundation into decoupled microservices. This example shows that, thanks to this modularity, it was able to migrate 60% of its workloads to a public cloud while keeping latency under 100 ms for 95% of transactions.

Foster an Agile and Collaborative Culture

An agile culture brings IT and business units closer together, reduces time-to-market, and increases internal satisfaction. Team autonomy sparks creativity and responsiveness.

Cross-Functional Agile Methods

Adopting agile frameworks—Scrum, Kanban, or SAFe—brings together cross-functional teams around short sprints and clear objectives. This approach shortens development cycles and encourages early business feedback.

Within IT departments, establishing autonomous squads facilitates ownership of business challenges. Each team is responsible for the full service lifecycle, from design to operation, which improves quality and empowers each contributor.

A Swiss private bank formed three squads dedicated to digitizing customer portals. The example shows that in less than six months, the delivery time for a new feature dropped from eight weeks to two, while maintaining 100% regulatory compliance.

Co-Creation and Design Thinking

Involving end users and business stakeholders from the start optimizes the relevance of developed features. Design thinking workshops foster creativity and align IT with operational priorities.

Defining customer journeys, building prototypes, and iterative testing phases ensure the final product aligns with real needs. This approach reduces rework and non-value-added development.

In a mobile payment solutions project, a Swiss bank held ten collaborative workshops with advisors and pilot customers. The example demonstrates that user feedback during the prototype phase reduced post-launch adjustments by 30%.

Empowering Teams and Continuous Learning

Skill development is crucial to support digital transformation. Promoting continuous learning—internal training, hackathons, certifications—boosts employee engagement and ensures the adoption of new practices.

Establishing internal communities of practice allows experts to share experiences and best practices, particularly on architecture, security, and UX. These regular exchanges strengthen cohesion and spread the agile culture throughout the organization.

A Swiss financial institution launched an internal certification program for DevOps and Cloud. The example shows that 80% of participants then applied these skills to real projects, helping reduce production incidents by 45%.

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Leverage AI and Advanced Analytics

AI and advanced analytics enable predictive and contextual financial services. Personalization enhances customer satisfaction and value creation.

Real-Time Customer Profiling

By analyzing navigation, transaction, and interaction data in real time, it becomes possible to instantly tailor offerings to each profile. Contextual recommendations—products, services, or alerts—increase engagement rates.

Implementing a centralized data lake and stream processing pipelines ensures a unified customer view. Real-time scoring algorithms feed your CRM and digital channels, ensuring a coherent omnichannel experience.

A Swiss wealth management firm implemented a streaming profiling engine for its online clients. This example shows that the open rate for service suggestions jumped by 25%, while churn decreased by 15% over six months.

Predictive Scoring and Risk Prevention

Machine learning models applied to credit history and transactional behavior improve the accuracy of lending decisions. Predictive scoring anticipates default risks and optimizes client portfolio management.

The integration of external data—social media, economic indicators, payment data—increases model granularity. Robust governance ensures transparency and compliance with GDPR and MiFID standards.

A Swiss cantonal bank deployed a predictive scoring tool for its SME loans. The example demonstrates a 20% reduction in credit losses and a 30% increase in approved applications while maintaining controlled risk.

Automate Customer Journeys and Human Interaction

Targeted automation reduces repetitive tasks and speeds up business processes. It frees up time for high-value interactions.

Request Processing Automation

Automating KYC processes, credit applications, or complex transfers involves orchestrated workflows and rule engines. Task standardization reduces errors and accelerates the validation cycle.

Combining OCR, RPA, and secure APIs ensures automated processing of documents and account statements while maintaining traceability and auditability at every step.

A Swiss bank implemented an automated process for credit card applications. This example shows that response time dropped from five business days to two hours, with customer satisfaction increasing by 35%.

Robotic Process Automation for Back Office

Deploying software robots for repetitive tasks—transaction reconciliation, regulatory report generation, data updates—increases reliability and reduces operational costs.

Centralized robot orchestration, coupled with continuous monitoring, allows for quick script adjustments and ensures minimal maintenance.

A Swiss wealth management firm automated its monthly portfolio consolidation. This example proves that it cut human time spent on this task by four and generated annual savings of 200,000 CHF.

Omnichannel Orchestration

Orchestrating interactions between chatbots, advisors, and self-service portals ensures the right channel is offered at the right time. Hybrid scenarios, combining automation and escalation to humans, are essential to maintain relationship quality.

A centralized messaging platform connects all digital touchpoints. Automated scripts pre-qualify requests and route complex cases to experts, ensuring seamless follow-up.

A regional Swiss bank implemented this omnichannel orchestration. This example demonstrates that the volume of conversations handled without human intervention reached 60%, while increasing the Net Promoter Score by 12 points over one year.

Turn IT into a Growth Lever

Adopting an open platform, instilling an agile culture, leveraging AI, and automating judiciously are the four pillars of a successful IT transformation in the financial sector. These levers, demonstrated by concrete Swiss cases, show that it is possible to reconcile innovation, operational performance, and service quality.

Institutions that invest in these strategic pillars won’t just survive disruption—they will redefine banking experience standards. Our Edana experts are at your disposal to analyze your specific challenges and guide you into this new technological era.

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