In finance the difference between a healthy position on intelligent fraud detection systems and a dangerous one is often a single assumption. Models supporting detection systems fail quietly, and usually at the worst moment. The programme works equally well for those formalising this area of financial and banking practice for the first time and those improving an existing approach. Content is organised around the decisions practitioners actually face in intelligent fraud detection systems, not around theory headings. Each session closes with a decision the participant must justify about the financial and banking practice discipline in their own setting. Post-incident reviews keep identifying weaknesses in detection systems that were visible long before the incident. Participants gain a clear basis for measuring what intelligent fraud detection systems has actually achieved. Improvement in detection systems stalls when it depends on one capable individual rather than a defined method. It closes by agreeing the smallest change to this part of financial and banking practice that would make a visible difference.
Expected Learning Outcomes
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Apply a repeatable review cycle to intelligent fraud detection systems and act on what it produces.
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Document the approval chain for exceptions to policy on detection systems.
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Translate policy on intelligent fraud detection systems into procedures that hold up under day-to-day pressure.
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Review the contractual and legal exposure created by detection systems.
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Recognise early indicators that intelligent fraud detection systems is drifting away from its intended design.
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Stress test detection systems against scenarios that are plausible rather than comfortable.
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Validate the assumptions inside any model supporting intelligent fraud detection systems.
Who Should Attend
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Risk managers responsible for intelligent fraud detection systems.
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Financial technology and change staff modernising detection systems.
