For financial organizations struggling with these predicaments, California-based Cognive emerges as a boon with their groundbreaking unified solution that enables financial institutions to take proactive approach in anticipating and combating financial crime. The company is well-known and established in the anti-money laundering (AML) and fraud prevention continuum owing to its unified cognitive ecosystem—Human Enhancement Artificial Technology platform (HEAT)—powered by Active AI and Distributed Protocols.
HEAT platform functions as an end-to-end analytics platform that integrates financial processes and employees’ information into a holistic AML system by extracting all the relevant insights from internal and external sources. “From reducing the frequency of false alerts and extracting previously unknown threats and scenarios to elevating the speed of the case review process and improving operational load, HEAT platform delivers long anticipated effectiveness of AI in the financial industry,” begins Viktor Nazarov, founder of Cognive.
An extension of the HEAT platform is the cross-institutional intelligence mechanism that facilitates seamless collaboration between financial organizations without sharing any sensitive information on the cloud. By configuring the degree of cross-institutional intelligence automation in accordance with transactional rules, models, and typologies, financial firms can launch their products and services in compliance with the rapidly changing regulations. Additionally, financial institutions can proactively and instantaneously deploy cross-institutional mechanism with other organizations if any fraud or money laundering cases are detected. “The idea behind cross-institutional intelligence mechanism is to exponentially improve the countering ability of financial firms by acting collectively against any suspicious activity,” mentions Nazarov.
In one of the recent case, the Transaction Monitoring System (TMS) of a financial institution was generating an overwhelming number of alerts, most of which were identified as false upon investigating. After studying the problem, Cognive applied its unified HEAT platform that analyzed the data, built dynamic profiles, classified and mapped analysts’ decisions related to each false alert to create a central recommendation system. “The outcomes were fascinating; there was a 60 percent reduction in the number of alerts generated without reducing the number of analyzed transactions. Even the operational workload diminished by 80 percent,” says Nazarov. This partnership was also bolstered the case review process speed by several times and improved the overall efficacy of the process.
Cognive is now planning a dynamic future with its ability to develop practical AI-based solutions. With a vision to establish a central system for every enterprise, Cognive is aiming at working with automation and cross-institutional intelligence to change the landscape of mutual business and collaboration between firms.