Banks and payment systems are facing growing challenges in managing fraud. Traditional rule-based systems fail to detect new and evolving fraudulent behaviors like Account Takeover (ATO), Synthetic Frauds and card-not-present (CNP) frauds.
In the light of the latest global pandemic, The U.S. Department of Treasury has recently issued an alert on COVID-19 related scams, which may lead to a string of additional data leakage, bank account takeovers, and fraudulent payments. Without effective solutions, fraudsters will continue to generate increasing financial losses and create friction in the customer experience for banks and their customers.
AI is a perfect match for the challenges of battling evolving fraud and enhancing customer experience. Learn how AI and machine learning are the exact solutions to fraud detection problems.
We will cover:
- Data requirements and feature engineering techniques to identify and triage high risk fraudsters and low-risk customers
- Building machine learning fraud detection systems with DataRobot ML Dev to both mitigate fraud and enhance customer experience
- Deploying and delivering enterprise impact at scale with DataRobot MLOps
