Over time, organizations have accumulated millions of records on policies, benefits, claims etc. collected from various systems, mergers, and migrations, creating a complex mix of formats, codes, and inconsistencies.
Regulatory expectations are rising. Frameworks like Solvency II, IFRS 17, and the WTP demand transparent, traceable, and trustworthy data so every decision can be explained and aligned with long-term commitments to policyholders and participants.
Manual checks can’t keep up — fixing errors after they appear is too late, adding cost and delay to reporting. Artificial Intelligence (AI) is emerging not as a replacement for actuaries, but as an intelligent assistant. Its role is to secure data integrity before it reaches the model. By learning from historical patterns, AI can detect, explain, and even correct anomalies in real time — shifting data control from rule-based checks to intelligent assurance.
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