Threats are continually evolving and made more difficult by data breaches that are external to the bank. Firms face increasing pressure from regulators to be more proactive to detect and prevent fraud. Rules-based systems without advanced analytical capabilities are not adaptive enough to detect sophisticated fraud schemes.
Goals and Objectives
Improve transaction monitoring programs to reduce financial losses from financial fraud. Avoid reputational risks from fraud events and costly regulator fines that can damage their reputations and brand names.
Advanced analysis tools including AI and machince learning to improve detection rates and reduce false positives.
Use Case Summary
Firms use advanced analytics to improve the effectiveness of their fraud detection programs. Machine learning is used to fine tune existing models and create new ones to better identify sophisticated fraud schemes.