Fraud Detection

Aviva uncovered a record £230 million in fraudulent insurance claims, highlighting the growing sophistication of fraudsters using AI. To combat this, Aviva is deploying its own AI tools to detect fabricated evidence, counterfeit documents, and inflated claims. This AI system analyzes vast datasets for anomalies and inconsistencies, acting as a crucial filter to augment human investigators and address the challenges of AI-generated deception in the financial sector.

Mastercard is investing heavily in large tabular models (LTMs) for its next-gen AI fraud detection and financial services. LTMs excel with structured data, crucial for banking. Mastercard is integrating them gradually as a complementary layer to mitigate risks of system-wide failure. The company plans to scale data input, develop APIs/SDKs for internal use, and prioritize privacy, transparency, and explainability. While LTMs promise enhanced efficiency and precision, their success depends on overcoming challenges like adversarial robustness, post-training costs, and regulatory acceptance.