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Poor data quality can compromise even the most advanced AI models, leading to biased decisions, regulatory breaches, and reputational harm. Imagine an AI model ‘let loose’ on inaccurate or incomplete data! That’s why robust data governance is essential, not only for compliance but also for building trustworthy AI systems.\u003C\u002Fp>\u003Cp>In one Customer Due Diligence (CDD) project, Talan Data x AI assisted a multinational bank in reconciling customer identity data across multiple jurisdictions. Our support ensured their compliance with both local and global anti-money laundering (AML) requirements. This involved creating a unified data model, implementing real-time validation checks, and establishing audit trails to support regulatory reporting.\u003C\u002Fp>\u003Cp>Another frequent challenge is conflicting consent data. For example, a customer might opt out of marketing communications via one channel but remain opted in on another due to fragmented systems. 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