Managing risk within a bank is a massive undertaking. To stay relevant, today’s Chief Risk Officer must embrace artificial intelligence (AI) and machine learning . Unfortunately, many banks are struggling to understand what machine learning is, let alone how it can improve their risk management practices.
The good news is that technological advances in machine learning are bringing AI solutions into reach for everyone at a much lower cost and a much higher ROI. The bad news is that your competitors are racing to modernize their risk teams as well.
This report describes five key AI use cases that every Chief Risk Officer needs to address:
- Anti-Money Laundering and Know Your Customer
- Fraud Detection/Prevention
- Streamlining Model Risk Management
- Credit Risk & Loss Forecasting
- Targeted Risk Review
The generative AI space is changing quickly, and the flexibility, safety and security of DataRobot helps us stay on the cutting edge with a HIPAA-compliant environment we trust to uphold critical health data protection standards. We’re harnessing innovation for real-world applications, giving us the ability to transform patient care and improve operations and efficiency with confidence
DataRobot provides us with innovative ways to test new ideas. Given a problem and a dataset, DataRobot allows us to generate multiple prototypes 20% faster. And the process facilitates the learning evolution of our data scientists.