Banking Innovation Training Course

Participants can identify priority customer problems using structured research and Jobs to Be Done.

• Jobs to Be Done interviews reveal functional, emotional and social progress
• Customer segments separated by needs, behaviours, economics and service expectations
• Problem statements distinguish observed evidence from internal solution assumptions
• Interview guides test triggers, workarounds, anxieties and decision criteria
• Opportunity scoring ranks frequency, pain, willingness to pay and strategic value
• Research ethics protect vulnerable customers, consent records and personal data

Participants can map banking journeys and identify high-value moments for service improvement.

• Journey maps trace customer goals, channels, emotions, failures and handoffs
• Moments of truth identified during onboarding, payments, borrowing and disputes
• Friction analysis separates policy constraints from poor service design
• Channel-switching patterns expose repeated contacts and avoidable abandonment
• Accessibility requirements considered for digital, assisted and branch interactions
• Journey measures combine completion, effort, time, complaints and conversion

Participants can translate a customer journey into front-stage and back-stage service requirements.

• Service blueprints connect customer actions, employee actions, systems and controls
• Lines of interaction, visibility and internal action clarify accountabilities
• Failure modes mapped at handoffs between channels, teams and suppliers
• Straight-through processing requirements specified for simple, low-risk service requests
• Exception journeys define escalation paths, service levels and customer communications
• Operational readiness criteria cover capacity, training, procedures and support

Participants can convert customer needs into differentiated banking service concepts.

• Value proposition canvases connect customer pains, gains and service features
• Concept statements specify target user, problem, promise and proof
• Feature prioritisation uses MoSCoW, customer value and delivery effort
• Service bundles combine accounts, payments, credit, advice and protection
• Choice architecture shapes disclosures, defaults, prompts and customer decisions
• Concept risks assessed for exclusion, misunderstanding, conduct and foreseeable harm

Participants can evaluate the commercial viability of banking service propositions.

• Business Model Canvas tests customers, channels, partners, revenues and costs
• Revenue models compare fees, interchange, spread income and subscriptions
• Contribution margin includes acquisition, servicing, losses, funding and technology costs
• Customer lifetime value assessed alongside retention, cross-sell and attrition assumptions
• Unit economics identify break-even volumes, payback periods and scale thresholds
• Sensitivity analysis tests adoption, pricing, losses and operating-cost assumptions

Participants can design channel roles and handoffs that improve banking service outcomes.

• Channel strategy assigns discovery, fulfilment, advice and support roles
• Mobile-first flows reduce data entry, document upload and repeat authentication
• Assisted-digital journeys support customers unable to complete digital tasks
• Conversational interfaces triage requests while preserving escalation to trained staff
• Branch and contact-centre roles redesigned around complex or vulnerable needs
• Channel performance tracked through containment, completion, effort and resolution

Participants can assess payment-service innovations and their operational implications.

• Payment journeys compare account-to-account, card, wallet and cross-border rails
• ISO 20022 data fields support richer payment information and reconciliation
• Instant-payment propositions address speed, confirmation, limits and fraud controls
• Request-to-pay services improve bill collection, consent and payment choice
• Payment exception handling covers returns, recalls, disputes and investigation
• Merchant propositions assess acceptance costs, settlement timing and working capital

Participants can evaluate open banking and embedded finance opportunities within defined controls.

• Open banking models distinguish account information, payment initiation and data sharing
• Consent journeys specify purpose, scope, duration, revocation and customer notices
• API product design defines users, service levels, pricing and developer support
• Embedded finance propositions assess distribution partners and brand-accountability boundaries
• Third-party due diligence covers security, resilience, conduct and financial viability
• Data-sharing value cases test customer benefit against consent and integration costs

Participants can select appropriate sourcing approaches for banking innovation initiatives.

• Build-buy-partner decisions compare speed, control, cost and strategic differentiation
• Partner selection criteria cover product fit, architecture, governance and resilience
• Commercial term sheets address pricing, ownership, termination and service levels
• Proof-of-concept scope defines hypotheses, interfaces, data and success measures
• Vendor concentration risk assessed across critical services and substitutability
• Joint governance establishes decision rights, issue escalation and performance reviews

Participants can specify responsible data-led service propositions and performance measures.

• Customer data inventories distinguish transactional, behavioural, declared and derived data
• Next-best-action models require clear triggers, eligibility rules and suppressions
• Segmentation methods combine customer needs, profitability, risk and engagement
• Propensity models assessed for drift, bias, explainability and monitoring
• Data minimisation limits collection to necessary service and decision purposes
• Personalisation metrics include relevance, conversion, opt-out and complaint rates

Participants can identify suitable AI use cases and define practical control requirements.

• AI use-case selection ranks value, feasibility, risk and data readiness
• Generative AI service assistants require grounded knowledge and human escalation
• Model risk controls document purpose, inputs, testing, approval and monitoring
• Explainability requirements differ for customer support, fraud and credit decisions
• Prompt-injection and data-leakage risks addressed through access and content controls
• Human-in-the-loop review defined for material customer and risk outcomes

Participants can integrate risk, conduct and compliance requirements into service design.

• Risk-by-design identifies operational, conduct, financial-crime and technology exposures
• Three Lines Model clarifies innovation ownership, oversight and independent assurance
• Customer outcomes testing examines clarity, fairness, suitability and foreseeable harm
• Privacy impact assessments identify personal-data processing and mitigation actions
• Financial-crime controls cover identity verification, screening, monitoring and reporting
• Control evidence prepared for product approval, audit and regulatory examination

Participants can design onboarding improvements that balance conversion, verification and fraud control.

• Digital identity journeys combine document checks, biometrics and liveness detection
• Know Your Customer requirements translate into evidence, risk tiers and refresh cycles
• Onboarding funnels identify abandonment at data capture, verification and funding
• Fraud threat modelling maps attackers, attack paths, controls and residual risk
• Step-up authentication triggered by transaction risk, device signals and behaviour
• False-positive analysis balances fraud prevention, customer friction and review costs

Participants can design controlled tests that generate decision-quality evidence.

• Assumptions registers distinguish desirability, viability, feasibility and compliance hypotheses
• Minimum viable services test critical customer value without full-scale build
• Experiment cards define audience, intervention, metric, duration and decision rule
• A/B tests require control groups, sample logic and pre-specified measures
• Qualitative feedback explains behavioural results, objections and unmet expectations
• Stop, pivot and scale criteria prevent unsupported continuation of pilots

Participants can define balanced metrics for innovation delivery and service performance.

• North-star metrics connect customer value with sustainable business performance
• Funnel metrics trace awareness, application, activation, usage and retention
• Leading indicators identify adoption barriers before financial results emerge
• Service-level metrics cover availability, response time, resolution and recoveries
• Risk indicators track fraud, complaints, exceptions, losses and control breaches
• Metric trees link team actions to portfolio objectives and executive reporting

Participants can prioritise innovation initiatives and govern investment through staged decisions.

• Portfolio maps classify initiatives by horizon, certainty, value and investment need
• Stage-gate governance defines evidence required for discovery, pilot and scale
• Investment cases separate one-off change costs from recurring operating costs
• Resource planning identifies scarce capabilities, dependencies and delivery bottlenecks
• Benefits-realisation plans assign owners, baselines, targets and review dates
• Executive dashboards communicate portfolio health, decisions, risks and next actions

Participants can organise banking service delivery around iterative release and control needs.

• Product backlogs translate service outcomes into prioritised delivery work
• User stories specify user, need, outcome and acceptance criteria
• Minimum releasable products align customer value with operational readiness
• DevSecOps practices integrate security testing, change controls and deployment evidence
• Architecture decisions assess integration patterns, data flows and resilience requirements
• Release plans coordinate technology, operations, communications, training and support

Participants can plan controlled scaling of validated banking services.

• Scale-readiness assessments cover demand, capacity, controls, technology and partner performance
• Operating-model changes define roles, handoffs, incentives and decision rights
• Change impact assessments identify affected teams, procedures, skills and communications
• Frontline enablement uses role-based guidance, coaching and escalation materials
• Customer migration plans sequence communications, consent, support and fallback options
• Post-launch reviews compare realised benefits, incidents and improvement priorities

Participants can incorporate inclusion and sustainability considerations into banking service choices.

• Financial inclusion analysis identifies barriers related to income, location and identity
• Vulnerable-customer needs inform accessibility, support, communication and product safeguards
• Digital exclusion risks assessed through device access, literacy and connectivity
• Sustainable-finance service ideas link customer needs with credible environmental data
• Greenwashing controls test claims, disclosures, evidence and product governance
• Impact measures distinguish customer outcomes from promotional activity and intentions

Participants can build, review and present a complete bank service innovation proposal with customer, commercial, delivery and control evidence.

• Customer problem evidence synthesised into a prioritised innovation opportunity statement
• Service blueprint defines channels, processes, systems, partners and control points
• Business Model Canvas documents target segments, revenues, costs and dependencies
• Pilot plan specifies hypotheses, metrics, governance, budget and decision criteria
• Risk assessment addresses conduct, privacy, fraud, resilience and third-party exposures
• Executive presentation communicates value, investment request, roadmap and implementation decisions