Fintech Innovation in Financial Services Training Course

Participants can define a customer problem and design a testable digital value proposition.

• Customer-journey mapping from acquisition through onboarding, servicing and retention
• Jobs to Be Done interviews identifying functional, emotional and social needs
• Pain-point prioritisation using frequency, severity, value and feasibility criteria
• Value Proposition Canvas matching customer jobs, pains and product gains
• Service blueprints linking frontstage journeys with operational support processes
• Accessibility and vulnerable-customer considerations within digital product design

Participants can evaluate fintech revenue models, cost structures and path-to-profitability assumptions.

• Business Model Canvas applied to regulated digital financial-service propositions
• Revenue models including interchange, subscriptions, spreads, fees and referral income
• Customer acquisition cost, activation rate and lifetime value calculations
• Contribution margin analysis for payments, lending and subscription products
• Cohort analysis tracking retention, usage, churn and revenue development
• Network effects, switching costs and scale economics in platform models

Participants can assess payment innovations against customer, commercial and risk requirements.

• Card payments, account-to-account transfers and wallet operating models compared
• Payment-message flows covering authorisation, clearing, settlement and dispute handling
• ISO 20022 data elements and migration implications for payment services
• Real-time payment propositions assessed through liquidity, fraud and resilience requirements
• Merchant acquiring economics, interchange structures and payment acceptance costs
• Central bank digital currency concepts and retail payment implications

Participants can design an API-enabled financial-service proposition and operating model.

• Open banking roles: account providers, third-party providers and customers
• API product design using user stories, service levels and versioning
• Consent management covering purpose limitation, revocation and customer records
• Embedded finance models within marketplaces, software platforms and merchant journeys
• API monetisation through premium access, revenue sharing and transaction pricing
• Sandbox, production and developer-portal controls for external API ecosystems

Participants can design digital onboarding flows with proportionate identity and financial-crime controls.

• Digital identity components: proofing, authentication, authorisation and credential management
• Know Your Customer workflows combining document, biometric and database checks
• Risk-based customer due diligence aligned with FATF risk-based principles
• Transaction-monitoring scenarios, alert triage and suspicious activity escalation
• Liveness detection, synthetic identity and deepfake fraud risk indicators
• Onboarding conversion metrics balanced against fraud loss and compliance outcomes

Participants can assess digital lending propositions, underwriting methods and model risks.

• Digital lending journeys from application capture through collections and closure
• Credit decisioning rules using affordability, bureau, transactional and behavioural data
• Alternative-data assessment for relevance, bias, consent and predictive stability
• Expected credit loss concepts linked to portfolio segmentation and monitoring
• Champion-challenger testing for underwriting models and policy cut-offs
• Fair-lending controls covering explainability, adverse action and disparate outcomes

Participants can evaluate digital advice, insurance and wealth propositions within conduct requirements.

• Robo-advice suitability workflows, portfolio models and client risk profiling
• Digital wealth platforms using fractional investing, goals and automated rebalancing
• Insurtech propositions across distribution, underwriting, claims and prevention services
• Usage-based insurance pricing informed by telematics and behavioural data
• Conduct-risk controls for disclosures, suitability, pricing and customer communications
• Human-in-the-loop escalation points for complex advice and claims decisions

Participants can evaluate AI use cases and establish appropriate model governance controls.

• AI use-case selection using value, feasibility, risk and data-readiness criteria
• Machine-learning lifecycle from problem definition through monitoring and retirement
• Generative AI applications for service, operations, research and coding support
• Model-risk management covering validation, drift, explainability and documentation
• Bias testing using subgroup performance, error rates and outcome comparisons
• Human oversight, escalation thresholds and audit trails for automated decisions

Participants can define data governance requirements for digital financial-service initiatives.

• Data domains, ownership and stewardship within financial-services operating models
• Data-quality dimensions: accuracy, completeness, timeliness, consistency and validity
• Data lineage mapping from source systems through models and customer outputs
• Privacy-by-design controls for collection, retention, sharing and deletion
• Master data management for customer, product, account and counterparty records
• Data-sharing agreements specifying purpose, access, security and accountability

Participants can assess target architecture choices and associated control responsibilities.

• Core banking modernisation options: replacement, renovation, abstraction and coexistence
• Cloud service models: infrastructure, platform and software responsibilities compared
• Microservices architecture, event-driven integration and service-domain boundaries
• Legacy-system integration using APIs, middleware, batch processing and data replication
• Technology architecture diagrams showing channels, services, data and control points
• Exit planning, portability and concentration risk for cloud providers

Participants can identify cyber and resilience controls required for digital financial products.

• NIST Cybersecurity Framework functions applied to financial-services technology assets
• Threat modelling using assets, threats, vulnerabilities and mitigating controls
• Identity and access management using least privilege and privileged-access controls
• Operational-resilience mapping of important business services and dependencies
• Incident response playbooks covering containment, communication, recovery and lessons learned
• Resilience testing through scenario analysis, failover tests and recovery objectives

Participants can distinguish viable distributed-ledger use cases from unsuitable applications.

• Distributed-ledger architecture: nodes, consensus, immutability and permissioning explained
• Tokenisation models for securities, funds, deposits and real-world assets
• Smart-contract controls covering code review, permissions and exception handling
• Custody models for private keys, wallets and digital-asset records
• Settlement finality, liquidity and legal enforceability in tokenised transactions
• Use-case screening against process complexity, trust gaps and integration costs

Participants can incorporate regulatory, conduct and consumer-protection requirements into product decisions.

• Regulatory perimeter analysis for digital products, activities and distribution models
• Consumer-duty principles applied to product design, pricing and customer support
• Fair treatment assessments for disclosures, fees, exclusions and collections practices
• Outsourcing governance covering materiality, oversight, audit rights and exit plans
• Recordkeeping requirements for customer consent, decisions and communications
• Regulatory engagement plans for novel products and significant technology changes

Participants can select fintech partners using commercial, technical and risk criteria.

• Partner selection scorecards weighting strategic fit, capability, economics and risk
• Vendor due diligence covering ownership, financial health and delivery capacity
• Technology assessments reviewing architecture, security, APIs and integration dependencies
• Service-level agreements defining availability, support, recovery and performance metrics
• Contract clauses for data ownership, audit access, subcontracting and termination
• Ongoing vendor monitoring through key risk indicators and service reviews

Participants can build a quantified investment case for a fintech initiative.

• Problem statements linked to customer, revenue, cost, risk and control outcomes
• Benefit mapping separating cashable savings, revenue uplift and risk reduction
• Cost models covering implementation, licences, integration, operations and change
• Net present value, internal rate of return and payback calculations
• Scenario analysis testing adoption, pricing, cost and loss assumptions
• Investment-committee papers presenting recommendations, assumptions and decision requests

Participants can structure delivery governance for a controlled fintech product launch.

• Product roadmaps connecting outcomes, releases, dependencies and funding decisions
• Agile delivery roles across product, engineering, risk, compliance and operations
• Minimum viable product scope defined through hypotheses and acceptance criteria
• Control-by-design checkpoints within discovery, build, testing and release stages
• Change-impact assessments covering processes, roles, training and customer communications
• Adoption metrics tracking activation, usage, satisfaction and operational readiness

Participants can establish metrics and governance for a portfolio of fintech initiatives.

• Balanced scorecards linking financial, customer, operational, risk and innovation measures
• North-star metrics selected for product value and sustainable customer behaviour
• A/B testing design using hypotheses, cohorts, guardrails and statistical significance
• Funnel analysis identifying drop-off across acquisition, onboarding and transaction journeys
• Innovation portfolio matrices balancing horizon, risk, value and resource demand
• Governance forums defining decision rights, escalation thresholds and reporting cadence

Participants can create a phased transformation roadmap aligned to target operating-model changes.

• Target operating model covering capabilities, processes, people, technology and governance
• Capability heat maps identifying priority gaps and investment sequencing
• Roadmap phases structured around foundations, pilots, scale-up and optimisation
• Dependency mapping across data, architecture, vendors, controls and regulatory approvals
• Benefits-realisation plans assigning owners, baselines, targets and review dates
• Executive communication narratives connecting transformation choices with strategic priorities

Participants can build, review and present a complete fintech innovation proposal with commercial, technical, risk and implementation evidence.

• Opportunity definition grounded in customer evidence, market conditions and strategic priorities
• Digital proposition specified through journeys, value proposition and operating model
• Technology architecture outlining APIs, data flows, platforms and integration dependencies
• Risk-control assessment covering conduct, cyber, privacy, model and third-party exposures
• Financial case presenting costs, benefits, scenarios, assumptions and investment metrics
• Phased roadmap defining governance, milestones, owners, measures and decision gates