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How to Leverage Big Data Security Analytics in the Finance Market

May 14, 2017

How to Leverage Big Data Security Analytics in the Finance Market


While Big Data security analytics can benefit just about any organization with a significant technology investment (or willingness to make that investment), they're especially applicable to the finance market. If you have any customers in financial services, make sure they know about these three ways to leverage Big Data security analytics in the finance market.

1. External fraud detection

As any financial services firm knows, fraud is a major concern. Identity theft is on the rise, with a new victim hit every two seconds as of February 2014. All those victims must be compensated for the losses they suffer when cybercriminals make fraudulent charges to their accounts, and all those fraudulent charges can add up to a major loss for the organization over time. Big Data security analytics can help to more quickly identify suspicious or fraudulent activity by establishing a baseline of normal behavior and detecting and alerting anomalous activity as it happens.

2. Internal fraud detection

Cybercrime from the outside is one thing, but financial services firms must also worry about theft from within. All the background checks in the world are unlikely to weed out every single unscrupulous job candidate, and those who slip through the cracks and into the organization may discover numerous opportunities to profit at the expense of the company or its customers. Simple theft is just one way an insider threat can take advantage of privileged access to accounts. Insiders may also exfiltrate consumer financial data and sell it, leading not only to monetary loss but to severe brand damage when the breach is disclosed. As with external fraud detection, Big Data security analytics can help detect and prevent insider data exfiltration by establishing a baseline of normal behavior and compare it to user activity in real time, identifying suspicious file access or transactions as they happen.

3. Proactive security monitoring

Big Data security analytics can extend far beyond the experiences of the firm itself, of course. One of the latest and most promising trends in cybersecurity is the development of large-scale threat intelligence databases accessible to solutions configured to leverage them. These databases can provide access to an enormous number of attack signatures, forensics, and other security incident data gathered from organizations all over the world, enabling enterprises to secure their own data more proactively rather than having to wait to react to incidents only after they happen.

Regulatory compliance alone demands that financial services firms pay particularly close attention to their data security efforts, and the massive financial and brand damage that can result from a data breach makes proactive security an even more urgent goal. Big Data security analytics can be an invaluable tool in the fight against cybercriminals and insider threats.

Are you ready to discuss Big Data security analytics with your financial services customers? If you need to learn more, get in touch with one of our security experts today.