Identify AI applications across financial services functions relevant to their institution. Describe how AI is changing three core banking and insurance functions in GCC institutions specifically. Apply AI tools to complete real financial services tasks, transaction anomaly identification, report summarization, and financial analysis. Use a responsible AI checklist to assess whether a proposed AI financial services tool is genuinely fit for purpose. Identify data privacy, accuracy, and fairness considerations relevant to AI use in their specific role.

Day one covers the GCC AI landscape in financial services, then goes deep on how AI is changing banking specifically, fraud detection and anti-money-laundering with fewer false positives, credit scoring moving from rules-based to model-based decisions, and customer analytics in GCC retail banking, before applying AI hands-on to transaction anomaly identification, report summarization, and internal financial analysis. Day two defines what responsible AI actually means in a financial services context, accuracy, transparency, and accountability, walks through common failure modes in AI-driven financial decisions, and builds an eight-question practical checklist for screening any AI tool before it’s trusted with a financial decision. Day three covers data privacy basics for AI in financial institutions, what personal data these tools can and cannot process, the real limits of model accuracy in daily use, and algorithmic bias implications specific to credit and insurance in GCC markets.

This is AI training that assumes the regulator is already in the room

a fraud detection model with a false positive rate that frustrates good customers, or a credit scoring tool that can’t explain its own decision to a regulator, isn’t a technical footnote, it’s a business and compliance failure with direct financial consequences. Institutions that train staff to screen AI tools before deployment catch these problems in review, not in an audit finding. This program exists so financial services professionals can use AI’s genuine advantages in fraud detection, analysis, and reporting, without inheriting risks the institution can’t defend in front of a regulator or an auditor