3 Practical Uses For AI In Risk Management

Every year, financial crime becomes more sophisticated, new malware emerges and fraud losses rise. Top that problem up with continuously evolving regulations and hefty non-compliance penalties, and financial institutions are facing an increasingly complex risk landscape.

To compete in the new environment, banks, insurance companies, asset managers and other industry players need to rethink how they approach financial risk management.

That’s where artificial intelligence can lend a helping hand. With advanced analytical capabilities, AI can augment human-led risk management activities to drive better outcomes much faster.

It is estimated that through better decision-making and improved risk management, AI could generate more than $250 billion in the banking industry.

Insurance companies, banks and fintech startups alike are starting to integrate AI-driven analytics into their financial risk management software. Here’s a roundup of three practical use cases to give you the idea of AI potential.