Introduction
The programme “Improving External Audit Results Using Artificial Intelligence” develops professional practice in Control and Audit. 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 fraud prevention, warning sign detection, and integrity protection, with practical work on artificial intelligence applications and controls, risk assessment, controls, and response, governance, accountability, and compliance management. 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 “Improving External Audit Results Using Artificial Intelligence”.
- Design an AI use case with verification criteria and human review.
- Prepare a risk register connecting causes, consequences, controls, and treatment responsibilities.
- Define decision-making authority, accountability mechanisms, and obligation monitoring.
- Distinguish suspicious indicators and design a professional response that preserves evidence and confidentiality.
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 “Improving External Audit Results 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. 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.
4. Governance, Accountability, and Compliance Management
- Map decision-making, oversight, and execution levels, and identify separation of roles and potential conflicts of interest.
- Review policies, committees, delegated authorities, and reporting frequency, and connect each responsibility to clear authority and limits.
- Create an obligations register specifying the source, scope, responsible party, and compliance evidence, and review applicable local requirements.
- Define disclosure, accountability, complaint handling, and misconduct reporting mechanisms, and protect information confidentiality during follow-up.
- Assess a practical governance case and prepare a gap remediation plan with review indicators and evidence of action closure.
5. Fraud Prevention, Warning Sign Detection, and Integrity Protection
- Analyze exposure to fraud and conflicts of interest in the process, and distinguish errors, suspicious indicators, and established facts.
- Identify warning signs in transactions, authorities, and data, and design analytical checks that support verification without making accusations.
- Review segregation of duties, approvals, reconciliations, and system permissions, and assess their effectiveness in prevention and detection.
- Define reporting, escalation, evidence preservation, and confidentiality procedures, and review local legal requirements before taking investigative action.
- Prepare a case study covering indicators, additional data required, and a plan for correcting controls and monitoring the response.
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 risk register, control matrix, and prioritized treatment plan.
- An authority matrix, obligations register, and escalation and review mechanism.
- A matrix of suspicious indicators and controls, and an evidence preservation and escalation checklist.
Who should attend
- Practitioners, specialists and supervisors whose work relates to the programme subject.
- Managers and teams working in control and audit, according to their practical responsibilities.
- Professionals responsible for applying the outputs of “Improving External Audit Results 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 “Improving External Audit Results 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.