Mindtree uses AI and ML to help banks reduce risk and improve compliance
Mindtree is using artificial intelligence and machine learning technology to help banks improve their ability to detect financial crimes and enhance reconciliation management. These service offerings are done through a partnership with Tookitaki’s machine-learning- powered platform.
Mindtree states that banks and other financial institutions are challenged by both the rising sophistication of financial crimes worldwide and increasingly complex regulations requiring strict operating and reporting standards. The ongoing efforts to manually detect money laundering, dealing with false alarms and fragmented reconciliation processes are costly and time consuming. They add that there is an urgent need for these institutions to automate many of these processes, reducing errors and accelerating their response times to incidents.
To address these challenges, Mindtree and Tookitaki are now offering these services:
Smart Alert Management: An automated, dynamically-adaptive model based on artificial intelligence and machine learning technology to detect suspicious cases more accurately. It reduces false alerts, increases true positives (suspicious cases missed by rules/ legacy systems), lowers costs, and helps the productivity of analysts. Banks can improve the anti-money laundering process using machine learning.
Smart Reconciliation Management: An automated approach to reconciliation management across business functions. Using machine learning and analytics, it increases match rates, resolves exceptions, recommends adjustment amounts and generates an audit trail for thorough business understanding. This shifts reconciliation from being subjective and error-prone to objective and more accurate. Banks can automatically handle exceptions and correct source systems while staying compliant.
