Big data helps financial centers mitigate fraud

Financial institutions are finding numerous ways to leverage big data solutions and applications into meaningful results. Data analysis software has helped many banking enterprises gain an edge in their marketplace and alter their operations to better engage and serve their clientele. ITWeb's Admire Moyo covered a recent seminar held by the Information Systems Audit and Control Association, which found that analytical tools could be used to help financial centers combat customer churn, enhance marketing endeavors and mitigate risky ventures. Perhaps the most intriguing application of big data tools in the financial sector mentioned, however, was its capability to prevent fraud.

One of the speakers at the seminar, Microsoft Software Assurance Solution Specialist Filip Vanden Hout, touted the ability of Hadoop architecture to house applications that specialize in identifying clients who are attempting to defraud a bank. Analytical tools cans gather and process information regarding earnings, transaction patterns and spending habits to determine if a customer is engaging in fraudulent activity.

Advanced Trading contributor Andrew Waxman agreed that big data analytics tools could be utilized to identify investment salesmen who peddle Ponzi schemes and other financial frauds. Mining data contained in futures brokers' records, including patterns of asset transfers, could help banking centers identify illegal activity. The ability of insider traders to operate undetected could also be limited with data analytics software by catching trades made outside of an employee's range of knowledge or which are conveniently executed before a major market announcement.

Using big data analytics, financial centers can significantly mitigate the amount of damage fraudsters can wreck. With software built upon Hadoop clusters, banking institutions can further enhance their efforts to combat financial misdeeds. The technology can reduce bottlenecks and return actionable results quickly, helping officials identify potential frauds before they can be fully executed.

Categorized by :
Big Data

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