Introduction
The programme “Oversight of Banks' Financial Systems Using Artificial Intelligence” develops professional practice in Risk and Credit. It connects the subject with workplace challenges by examining existing evidence and practices and choosing methods appropriate to the organization and its available resources.
The learning progresses from risk-based auditing and evidence gathering to risk assessment, controls, and response, with practical work on artificial intelligence applications and controls, financial statement and report analysis, credit analysis and banking risk. Participants prepare outputs to support workplace application and review the quality and results of implementation.
Learning objectives
- Design an audit engagement connecting risks, objectives, tests, and evidence in an application related to “Oversight of Banks' Financial Systems Using Artificial Intelligence”.
- Design an AI use case with verification criteria and human review.
- Interpret performance, financial position, and cash flows using documented analysis with clear limitations.
- Prepare a credit analysis and risk scenario showing repayment capacity and controls.
- Prepare a risk register connecting causes, consequences, controls, and treatment responsibilities.
Learning areas
1. Risk-Based Auditing and Evidence Gathering
- Define the engagement subject, objectives, scope, and assessment criteria, and develop an initial understanding of the process and its main risks.
- Assess control design and suitability for the objectives, and select tests and samples proportionate to risk levels and available data.
- Collect sufficient, appropriate evidence, document sources and verification procedures, and maintain independence, objectivity, and information confidentiality.
- Write a finding connecting the criterion, condition, cause, and effect, and discuss the response and agreed action with the relevant party.
- Prepare a clear report and action follow-up plan, applying current professional requirements relevant to the audit type and work environment. The application examines a case related to “Oversight of Banks' Financial Systems Using Artificial Intelligence”.
2. Artificial Intelligence Applications and Controls
- Identify a task that AI can support, and separate inputs and human decisions from outputs produced by the tool.
- Prepare suitable test data and examples while respecting confidentiality, privacy, and permissions, and use de-identified training exercise data.
- Write clear instructions covering the task, context, constraints, and output format, and compare multiple formulations using a fixed set of examples.
- Check outputs for errors, bias, and unsupported information, and identify cases that require specialist review.
- Assess the feasibility of use in terms of quality, time, cost, and risk, and document controls for approval, monitoring, and stopping when failures occur.
3. Financial Statement and Report Analysis
- Read the relationships between the statements of financial position, performance, and cash flows and the notes, identifying the effects of accounting policies and estimates.
- Perform horizontal and vertical analysis and compare profitability, liquidity, efficiency, and leverage indicators, considering the nature and size of the business.
- Examine earnings quality, cash flows, and nonrecurring items, and identify differences between accounting results and actual liquidity.
- Test the sensitivity of results to changes in sales, costs, collections, and financing, stating the assumptions and constraints in each scenario.
- Write a financial report linking indicators to management's question and available alternatives, presenting risks and additional data needed for the decision.
4. Credit Analysis and Banking Risk
- Analyze the financing purpose, repayment sources, and nature of the business, and review the financial and nonfinancial data needed to assess the customer.
- Assess cash flows, debt servicing capacity, and collateral, distinguishing the primary repayment source from supplementary protections.
- Classify relevant credit, market, liquidity, and operational risks, considering the applicable regulatory framework and internal policies.
- Test the effects of changes in revenues, prices, and maturities on repayment capacity, and define conditions and monitoring requirements addressing the identified risks.
- Prepare a documented recommendation covering limits, assumptions, information gaps, and warning indicators without turning the training case into an actual financing decision.
5. Risk Assessment, Controls, and Response
- Define the work context, objectives, and assessment boundaries, and distinguish the risk source, potential event, and effects on results.
- Gather risks from processes, data, past incidents, and interviews with responsible staff, and document causes and existing controls.
- Estimate likelihood and impact using stated criteria, and review control effectiveness to determine residual risk levels.
- Select a response proportionate to the risks, resources, and authority, and specify the owner, deadline, and early warning indicator.
- Test a scenario involving changing circumstances, update the risk register, and present material risks and required decisions to the appropriate authority.
Practical outputs
- An audit engagement program, working papers, and an actionable finding.
- A use case brief and a test template for the quality of AI outputs.
- A comparative financial analysis report and a memo of findings and assumptions.
- A credit memo, risk register, and early warning indicators.
- A risk register, control matrix, and prioritized treatment plan.
Who should attend
- Practitioners, specialists and supervisors whose work relates to the programme subject.
- Managers and teams working in risk and credit, according to their practical responsibilities.
- Professionals responsible for applying the outputs of “Oversight of Banks' Financial Systems Using Artificial Intelligence” within their organizations.
Prerequisites
- Working familiarity with the programme field and the ability to discuss a professional case or challenge.
- Confirm the suitability of your experience and any specialist prerequisites with the Union before participation.
Conclusion
The programme “Oversight of Banks' Financial Systems Using Artificial Intelligence” brings together concepts, case review and a practical application. Participants prepare steps that can be adapted to their responsibilities and organizational resources, with an indicator to follow application and review results after returning to work.
Participation arrangements and any special requests are specified in the confirmation issued by the Union.