Fintech Innovation and Disruption Training Course

Participants can define a regulated digital-service problem using customer evidence and service-design methods.

• Service blueprints linking customer actions, frontstage processes and backstage controls
• Customer journey maps for onboarding, payments, lending and claims
• Design thinking problem statements grounded in observable customer evidence
• Persona assumptions tested against behavioural, transactional and complaint data
• Accessibility requirements for mobile journeys, authentication and assisted channels
• Prototype acceptance criteria specifying speed, clarity, recovery and consent

Participants can assess technology architecture options for scalable and controlled fintech services.

• Reference architectures separating channels, orchestration, core systems and data
• API product design using REST resources, versioning and error contracts
• OAuth 2.0 and OpenID Connect roles in delegated authorisation
• Event-driven patterns for payment status, notifications and reconciliation updates
• Microservices trade-offs: autonomy, observability, latency, resilience and data consistency
• Build-buy-partner decisions assessed through capability, cost, risk and speed

Participants can evaluate cloud and data-management choices against financial-services operating requirements.

• Cloud shared-responsibility model applied to regulated financial workloads
• Data lakehouse layers: ingestion, curation, serving and lineage controls
• Master data management for customer, account, merchant and product records
• Data quality rules measuring completeness, validity, timeliness and uniqueness
• Data residency assessments covering jurisdictions, subcontractors, backups and access
• FinOps unit economics for cloud consumption, tagging and cost allocation

Participants can analyse payment propositions, economics, processing flows and operational risks.

• Payment rails compared: cards, ACH, real-time payments and wire transfers
• ISO 20022 message concepts: parties, accounts, remittance and status
• Merchant acquiring economics, interchange, scheme fees and chargeback exposure
• Payment orchestration routing rules for approval rates, cost and resilience
• Reconciliation design matching authorisations, captures, settlements, refunds and ledger entries
• Cross-border payments analysed through FX spreads, correspondent banking and sanctions

Participants can assess digital-lending models from underwriting through collections and loss management.

• Digital lending journey from acquisition through underwriting, servicing and collections
• Credit policy translated into scorecards, cut-offs, limits and exceptions
• Alternative-data governance testing relevance, bias, provenance and consent
• Expected credit loss concepts linked to IFRS 9 staging
• Loan pricing models combining funding cost, losses, capital and margin
• Collections strategies using delinquency buckets, treatment paths and hardship options

Participants can evaluate digital banking propositions and account-service operating models.

• Digital account opening controls for identity, eligibility and product suitability
• Deposit product economics: interest expense, liquidity value and attrition
• Core banking modernisation options: replacement, progressive renovation and wrapping
• Personal financial management features using categorisation, goals and alerts
• Banking-as-a-Service responsibilities across sponsor bank, fintech and programme manager
• Service-level indicators for availability, onboarding completion and transaction success

Participants can assess digital wealth and insurance propositions, including conduct and suitability requirements.

• Robo-advice suitability workflows, portfolio models and investor disclosures
• Digital wealth platforms: custody, execution, rebalancing and fee administration
• Insurtech value chain from quote through underwriting, claims and renewal
• Usage-based insurance pricing signals, telematics consent and claims verification
• Parametric insurance triggers, data sources, basis risk and payout controls
• Conduct-risk reviews for recommendations, disclosures, incentives and vulnerable customers

Participants can distinguish viable distributed-ledger use cases from poorly justified technology applications.

• Distributed ledger design: nodes, consensus, finality and governance
• Permissioned versus public networks assessed for privacy, throughput and control
• Tokenisation structures for deposits, securities, funds and real-world assets
• Smart contract controls: code review, oracle risk and upgrade authority
• Stablecoin reserve, redemption, custody and regulatory risk analysis
• Central bank digital currency models and intermediary roles

Participants can identify regulatory obligations and design proportionate compliance arrangements for fintech services.

• Regulatory perimeter analysis distinguishing regulated activity, outsourcing and technology supply
• Licensing pathways for payments, e-money, lending and investment services
• Regulatory change inventories linking obligations, owners, controls and evidence
• Regtech workflow design for reporting, attestations, monitoring and audit trails
• Consumer protection duties covering disclosures, complaints, pricing and fair treatment
• Third-party risk assessments covering concentration, subcontracting, exit and resilience

Participants can assess cybersecurity and resilience controls for customer-facing financial technology.

• Threat modelling with STRIDE for mobile, API and cloud services
• Zero Trust architecture principles for identity, devices, networks and workloads
• PCI DSS v4.0 scoping for cardholder-data environments and service providers
• OWASP API Security Top 10 applied to financial interfaces
• Security incident playbooks covering containment, investigation, notification and recovery
• Business continuity metrics: recovery time, recovery point and dependency mapping

Participants can design financial-crime and fraud controls appropriate to a fintech product model.

• Customer due diligence workflows for individuals, businesses and beneficial owners
• Sanctions screening controls covering lists, matching thresholds and escalation
• Transaction monitoring scenarios calibrated to products, segments and typologies
• Fraud typologies: authorised push payments, account takeover and mule networks
• Case-management evidence supporting suspicious activity reports and audit review
• Fraud loss metrics separating gross loss, recovery and prevention value

Participants can assess AI use cases, model risks and data-protection obligations in financial services.

• Machine-learning lifecycle from feature design through monitoring and retirement
• Model risk management inventories, validation, approval and performance thresholds
• Fairness testing using disparate impact, error rates and segment outcomes
• Explainability methods: feature importance, reason codes and adverse-action notices
• Generative AI controls for prompts, retrieval, human review and confidentiality
• Data protection impact assessments for automated decisions and sensitive data

Participants can structure platform and partnership propositions with defined commercial and control responsibilities.

• Platform business models: multi-sided markets, network effects and governance
• Embedded finance propositions within retail, mobility, payroll and marketplace journeys
• Open banking consent flows, account access and payment initiation
• Partner due diligence covering financial health, controls, conduct and strategy
• Commercial agreements allocating revenue, liability, data rights and termination
• Platform KPIs: active users, conversion, retention, take rate and cohort value

Participants can build and challenge commercial assumptions behind a fintech investment proposition.

• Unit economics linking acquisition cost, activation, retention and contribution margin
• Customer lifetime value assumptions tested through cohorts, churn and discount rates
• Fintech valuation methods: revenue multiples, DCF and comparable transactions
• Scenario analysis for volume, pricing, credit losses and funding costs
• Capital planning covering runway, regulatory capital, liquidity and contingency funding
• Board metrics linking growth, risk, operational resilience and customer outcomes

Participants can plan controlled product delivery and make informed technology sourcing decisions.

• Agile product operating model: discovery, delivery, measurement and iteration
• Product backlog prioritisation using RICE, WSJF and regulatory commitments
• Minimum viable product scope defined by hypotheses, controls and metrics
• Vendor selection scorecards comparing functionality, integration, security and support
• Service integration plans covering data migration, testing, release and rollback
• Product analytics funnels measuring acquisition, activation, engagement and retention

Participants can define the people, processes, controls and governance needed to operate a fintech service.

• Target operating model defining processes, roles, technology, data and governance
• RACI matrices assigning accountable owners for product, risk and operations
• Change impact assessments covering people, procedures, controls and customer communications
• Digital talent plans for product, engineering, data and risk roles
• Control automation opportunities identified through process mapping and exception analysis
• Adoption metrics measuring employee use, process compliance and service quality

Participants can create a prioritised fintech strategy with measurable outcomes and decision controls.

• Fintech strategy choices assessed through market attractiveness and capability fit
• Strategic roadmaps sequencing propositions, enablers, controls and investment decisions
• OKRs connecting customer outcomes, commercial targets and risk tolerances
• Risk appetite statements translated into measurable product guardrails
• Investment governance using stage gates, benefit tracking and stop criteria
• Stakeholder narratives tailored for executives, regulators, partners and delivery teams

Participants can prepare an evidence-based business case for a controlled fintech launch or investment.

• Business case structure linking problem, proposition, economics, risks and decisions
• TAM, SAM and SOM estimates built from defensible market assumptions
• Financial model drivers for transactions, users, balances, losses and costs
• Risk-control matrix linking failure scenarios, preventive controls and owners
• Implementation plan sequencing approvals, suppliers, pilots, scaling and exit
• Executive decision papers presenting options, trade-offs, recommendation and evidence

Participants can build, review and present a complete fintech proposition covering customer value, architecture, economics, controls and implementation.

• Capstone brief defining target segment, problem statement and success measures
• Customer journey and service blueprint connecting experience, operations and controls
• Solution architecture specifying APIs, data flows, partners and security boundaries
• Commercial model with unit economics, pricing assumptions and financial scenarios
• Risk, compliance and resilience plan covering controls, ownership and evidence
• Executive presentation defending roadmap, investment case, trade-offs and implementation priorities