Financial Technology Foundations Training Course

Participants can map payment flows and identify operational, settlement and fraud control points.

• Card-payment flow from authorisation through clearing, settlement and chargebacks
• Account-to-account payment rails, real-time payments and batch clearing
• ISO 20022 message concepts for payment data and reconciliation
• Merchant acquiring, payment gateways, wallets and payment orchestration roles
• Reconcile settlement positions using transaction files, fees and reserve balances
• Fraud controls: velocity rules, device fingerprinting and transaction monitoring
• PCI DSS v4.0 responsibilities for cardholder-data environments
• Payment exception management for reversals, returns, disputes and failed transactions

Participants can evaluate API-enabled financial services, consent models and associated control requirements.

• API architecture concepts: endpoints, authentication, tokens and data payloads
• Open-banking account-information and payment-initiation service models
• Consent lifecycle covering capture, scope, renewal, withdrawal and audit evidence
• OAuth 2.0 authorisation flows for third-party financial-data access
• Embedded-finance propositions within retail, mobility, marketplace and payroll platforms
• Assess API controls for availability, rate limits, logging and access segregation
• Data minimisation principles applied to customer financial-data sharing
• Service-level measures for API uptime, latency, errors and incident response

Participants can assess digital lending processes, credit models and model-risk controls.

• Digital lending journey from acquisition through underwriting, servicing and collections
• Credit decision engines combining bureau, transaction and behavioural data
• Alternative-data assessment for relevance, bias, consent and explainability
• Scorecard development concepts: segmentation, predictors, cut-offs and overrides
• Model-risk governance covering validation, monitoring, documentation and approval
• Fair-lending controls for disparate impact, adverse action and complaint analysis
• Fraud prevention during digital onboarding, identity proofing and application review
• Portfolio monitoring using vintage analysis, roll rates and expected losses

Participants can evaluate analytics and AI use cases using data quality, governance and control criteria.

• Financial-data lifecycle from collection through storage, use, retention and disposal
• Data-quality dimensions: completeness, accuracy, timeliness, consistency and validity
• Customer analytics for segmentation, next-best action and retention measurement
• Machine-learning applications in fraud detection, credit and customer service
• Feature engineering risks arising from proxies, drift and data leakage
• Explainable-AI techniques for reason codes, traceability and decision challenge
• Human-in-the-loop controls for high-impact automated financial decisions
• Model monitoring metrics: precision, recall, stability and calibration

Participants can distinguish distributed-ledger use cases from unsuitable applications and related control requirements.

• Distributed-ledger components: nodes, consensus, cryptography and shared records
• Public, private and permissioned blockchain design trade-offs
• Tokenisation of deposits, securities, funds and real-world assets
• Stablecoin structures, reserve management, redemption and depegging risks
• Digital-asset custody models: hot wallets, cold wallets and multisignature
• Smart-contract risks including coding errors, oracle failures and governance
• Blockchain settlement benefits compared with legal finality and operational constraints
• Assess use cases using problem fit, control feasibility and economics

Participants can connect regulatory technology applications to financial-crime and identity-control requirements.

• Regtech applications for regulatory reporting, surveillance and compliance workflow
• Digital identity components: verification, authentication, credentials and liveness detection
• Know-your-customer risk assessment using customer, product and geography factors
• Customer due-diligence records, beneficial ownership and periodic review triggers
• Transaction-monitoring scenarios for sanctions, fraud and money-laundering indicators
• FATF Recommendations applied to virtual assets and service providers
• Case-management workflow for alert triage, investigation and suspicious-activity reporting
• False-positive reduction through threshold tuning, segmentation and quality assurance

Participants can identify security, privacy and resilience controls for fintech-enabled financial services.

• NIST Cybersecurity Framework 2.0 functions applied to fintech services
• Threat modelling using assets, actors, attack paths and control priorities
• Identity-and-access management: least privilege, multifactor authentication and privileged access
• Privacy impact assessment for customer data, profiling and automated decisions
• Cyber-fraud threats including account takeover, phishing and social engineering
• Incident-response playbooks covering containment, communication, recovery and evidence preservation
• Operational-resilience mapping for important business services and dependency chains
• Scenario testing for cloud outages, cyberattacks and critical supplier failure

Participants can conduct structured fintech supplier assessments and define governance for outsourced services.

• Vendor due diligence covering ownership, finances, controls and delivery capability
• Request-for-proposal criteria aligned with functional, technical and control requirements
• Assess cloud-service contracts for data location, access and exit provisions
• Third-party risk register linking services, dependencies, risks and accountable owners
• Service-level agreements for availability, security incidents, support and recovery
• Control-right clauses covering audit access, assurance reports and subcontractors
• Implementation governance using steering committees, workstreams and decision logs
• Benefits-realisation measures for cost, cycle time, errors and adoption

Participants can create a phased fintech adoption plan with measurable benefits, ownership and control gates.

• Use-case prioritisation matrix combining value, feasibility, risk and strategic fit
• Business case structure for investment, operating costs, benefits and assumptions
• Process baseline measures for turnaround time, cost, errors and satisfaction
• Pilot design defining hypotheses, customer segment, controls and success thresholds
• Implementation roadmap with dependencies, milestones, owners and decision gates
• Change-management plan for operating procedures, training and stakeholder communications
• Post-implementation review against benefits, incidents, controls and customer outcomes
• Personal application plan for a selected financial-technology opportunity