financial services.

Industrial Generative AI
for Financial Services

McKinsey projects generative AI to create a $250-410 billion annual impact in the insurance and banking sectors. Enhance risk management, refine policy and portfolio pricing, accelerate forecasting, and run next-generation fraud prevention—all while cutting compute costs and speeding up calculations.

Use cases

Solutions for Financial Services’ most computationally complex challenges.

Anomaly Detection

Fast Alternative to Monte Carlo

Optimization

Predictive Modeling

High Throughput Computing

Anomaly Detection

Fast Alternative to Monte Carlo

Optimization

Predictive Modeling

High Throughput Computing

Identify anomalies or outliers with greater accuracy using mathematical techniques from quantum science.

Key Challenges


  • Identifying potential fraud by detecting outlier transactions
  • Limited training data for fraud detection algorithms hinders detection of novel or underrepresented forms of fraud
  • Identify mispricing and arbitrage in illiquid markets
  • Price pattern and trend recognition

Zapata AI Solutions


Credit Fraud Detection

Detect credit fraud more accurately, leveraging generative AI to enrich training data for machine learning detection algorithms.

Insurance Fraud Detection

Detect insurance fraud more accurately than traditional approaches to accelerate remediation and reduce losses.

featured resources

How can these solutions work for your enterprise?