MapR leverages Big Data analytics in fight against financial fraud
Hadoop purveyor MapR Technologies Inc. is throwing its weight behind the fight against fraud, cybercrime, and regulatory non-compliance with a new risk management solution for financial companies.
The idea behind MapR’s new Risk Management Quick Start Solution for Financial Services is that by making more data available to companies, they can better use MapR’s Converged Data Platform to identify and manage these kinds of risks.
In its pitch, MapR notes that traditional messaging and data processing solutions are incapable of handling the increasing scale and complexity of risk management. With the company’s new solution however, it becomes much easier to identify, model and analyze vulnerabilities and help companies to detect things like fraud, identity theft, money laundering, rogue trading and terrorist financing.
“MapR data scientists have worked with some of the world’s largest banks, brokerages and fintech companies,” Dave Jespersen, vice president of worldwide services at MapR Technologies, said in a statement. “With this new Risk Management Quick Start solution, we have created a proven, repeatable and demonstrable approach to identifying fraud and other illicit activities using the scale and reliability of the MapR Converged Data Platform.”
MapR describes the Risk Management Quick Start Solution (QSS) for Financial Services as a “data-driven” platform that provides a working data science model to detect anomalies, as well as consulting services with MapR’s data scientists.
The solution offers two separate “paths” forward, including a fraud detection path and an anti-money-laundering path. The former model uses predictive analytics models to deal with vulnerabilities that go beyond fraud.
“The same data science feature extraction, machine learning modeling work, and creation of transaction fraud thresholds can be applied to other important problems such as identity theft, and insurance claim fraud,” the company said.
As for the anti-money-laundering path, this involves advanced anomaly detection to identify more difficult to detect risk management challenges. As well as using this approach to detect money laundering, financial firms can also spot rogue trading and terrorist financing activities, monitor network security and also tackle complex regulatory compliance issues.
“Both paths include a discovery process with a MapR data scientist and culminate in a demonstration of the precise incremental monetary value to the business of the fraud detection and the clear identification of suspicious and actionable alerts from anti-money-laundering algorithms,” the company said.
The new service is available from today.
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