Regulatory pressure forces data rethink

Regulatory pressure forces data rethink

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Asset managers have much to gain from applying business intelligence processes – and specifically more sophisticated analysis of data – to their compliance regime.

To effectively comply with new regulatory initiatives, asset managers are restructuring enterprise-wide data architecture and systems to increase data, reporting and record-keeping capabilities, including near-real time reporting, according to the EY report Winning the global regulation game.

Predictive analytics is being used to enhance business intelligence capabilities, explains Rob Toguri, UK data and analytics leader at the professional services firm. “One powerful application is more comprehensive trade surveillance to detect and prevent market abuse and fraud by merging trade data with other data sources.”

Firms are introducing analytical models and reporting dashboards to address a range of key compliance risks, for example performing automated analyses of key client documentation to automatically identify specific requirements. “Asset managers are also introducing more sophisticated visualisations such as consistent inputs to their regulatory reporting and internal reports, to more efficiently and effectively ensure the required quality level across these aggregated datasets,” says Toguri.

Business intelligence enables asset managers to better interrogate their positions and investment decisions and, if used well, can show in advance how compliance and regulatory requirements are affected by these decisions, or by market movements or other changing factors, adds Steve Young, managing partner at Citisoft.

“Technology can play a huge part in highlighting practices that could create regulatory issues within an organisation before they come to the attention of regulators,” he says. “It is already a significant element of the management of regulatory issues, but as firms gain greater expertise and experience with these tools this can only improve and extend.”

Vincent Kilcoyne, capital markets industry lead SAS UK & Ireland, observes that compliance with regulations such as MiFID and anti-money laundering requires asset managers to effectively manage vast amounts of data from trading systems, internal spreadsheets, emails, chat and voice communication. “To identify any irregularities in their processes, asset managers need to be able to monitor for suspicious activity and ensure due diligence on customers.”

Kilcoyne suggests managers should start by analysing customer activity and risk characteristics. “By grouping segments of customers or accounts together based on inherent characteristics – for example, average transactional volume or net worth – asset managers can easily identify customers who are expected to behave in a similar fashion to other customers but don’t and risk-rank each alert based on a variety of factors, from the number of past alerts to the possibility that the alert will result in a regulatory filing.”

Unstructured data

The transformation and analysis work that is being doing on data ahead of representing it as a report or visualisation is particularly significant, suggests Lexalytics CEO Jeff Catlin. “One area seeing significant advancement in capabilities is the analysis of unstructured data (emails, social media posts, images) and correlating it with structured data such as phone logs and trade activity. Legacy text analytic systems have been programmed to find certain key words related to how someone might violate regulations, but those do not take into account changing language and some of the differences in medium, author, message or context.”

If a manager has a centralised system monitoring communications that is constantly kept up to date, it can flag when someone is starting to go down a path that is not going to end well, he adds. “Sometimes people make mistakes or aren’t aware of a change in the laws. By capturing information in an automated, consistent fashion, they can be retrained early before a misunderstanding becomes a regulatory problem.”

The challenge for most asset managers is to take advantage of the opportunities available while budgets and margins are under pressure from competing investment demands, says Toguri.

In the future, it is likely that asset managers will increasingly use technology to help reduce their operational risks relating to regulatory issues, he concludes. “They will utilise and merge big data from new sources such as systems process logs, voice and email and will overlay this with powerful machine learning and cognitive techniques, which will help them better understand behaviours across business processes.”

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