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May 5, 2016updated 28 Mar 2017 4:26pm

Using big data for intelligent compliance in financial services

By John Oates

The world of financial services has changed radically since the crisis of 2008. Regulators, backed by a less forgiving public, are on the alert for dodgy dealing. Ongoing scandals like fixing of the Libor rates and of currency exchange fraud mean more and markets are coming under scrutiny. New directives, or guidelines on how to ensure compliance, are being imposed almost every day.

Companies not only have to closely follow the new rules they have to prove that they’re following them.

The cost of failure is very high – recent research from Morgan Stanley found global financial firms have paid £180bn($260bn) in fines since 2009.

Financial organisations are looking to intelligent software to help them ensure compliance with the ever-growing demands of regulation. Hewlett Packard Enterprise is one of the vendors offering big data analysis to help companies reduce the compliance workload.

HPE’s software aims to take a broader view of fraud and possible malpractice by grabbing data from right across the enterprise.

It uses machine learning to sift this data for patterns suggesting criminal or non-compliant activity. The solution is equally at home dealing with very structured data like deal history as it is with less structured information from call recording, instant messaging and social media use.

Laura DuBois, Group Vice President, Enterprise Storage, Servers and Infrastructure Software at IDC, said: “An ever-increasing amount of enterprise data combined with escalating fines and sanctions is creating a risk threshold that organizations are no longer able to ignore, particularly in highly regulated industries,”

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“A software solution like the one from Hewlett Packard Enterprise, which delivers insight into both structured and unstructured data – to not only identify and analyze risk events, but also take action to prevent them – is quickly becoming an industry mandate.”

The hosted solution, called HPE Investigative Analytics, combines data typically kept in silos within financial organisations to create a ‘curated data lake’. This source is then used by the machine learning analytics system, utilising human behaviour models, to assess risks and warn of potential problems or conflicts.

Tom Lewis, UK Head of Data Analytics at PwC, said: “Following recent high-profile allegations and fines, many of our clients are seeking a comprehensive analytical solution to improve their ability to identify non-compliant or fraudulent activities,”

“With Hewlett Packard Enterprise, we are leveraging their communication-centric analytics platform to help clients deploy a framework of sophisticated analytical and investigative applications and processes.”

HPE believes its solution analyses more data at a deeper level than rivals.

HPE Investigative Analytics also secures and audits access to the data lake as well as providing analysis to create actionable insights. It creates Key Risk Indicators – flagging up potentially problematic communications or trading behaviours. These indicators can either come ‘out-of-the-box’ or be defined by the customer.

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