Business problem:

Anti-Money Laundering (AML) Transaction Monitoring products and processes generate high numbers of false positives (98%) due to unsophisticated detection coupled with limited breadth of investigative information and limited quality assurance. This forces financial firms to deploy significant human capital to manually investigate such alerts. Financial Institutions are constantly trying to achieve operational simplification, risk optimization as well as cost reduction.

Our Solution:

IVOR, powered by Microsoft Cloud, enables financial institutions to reduce the volume of false positives by 65+%. Made possible with a machine learning driven model that adapts to changes in environment. IVOR allows financial institutions to significantly reduce human capital allocation while efficiently managing risk. Moreover, IVOR can work as a bolt on solution, integrating harmoniously with current alerting products or in its own right.

Key features of the solution are:

Machine learning driven engine that adapts to changes in customers behaviors/policy
Flexible coverage, suitable for any size of player, nationally or internationally
Integratable within any existing infrastructure - Any Cloud and/or On Prem

Our Differentiators:

Domain expert driven machine intelligence with powerful predictive features
A country agnostic solution suitable for domestic and multinational organizations
Auto self-explanatory model understandable by regulators with minimal manual input
Augmenting and enhancing existing technology rather than competing
Machine Learning Operations (MLOPS) allows IVOR to execute effectively in changing data environments
Auto-builds and deploys alternative models as customer behaviors change

For more details about this Microsoft Financial Service Cloud solution, please feel free to connect with us!

Wipro Intelligent Volume Optimization and Risk-management (IVOR)

作者 Wipro Ltd