The ability to analyse information from multiple data sources has obvious benefits for wealth and asset managers, although many firms lack the infrastructure to extract business intelligence from their data. What are asset managers doing currently with business intelligence and what more can they do? Paul Golden speaks to industry experts to outline best practices
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The 2015 EY report Winning the Global Regulation Game noted that asset managers across the globe have been forced to look at restructuring their data architectures in order to address regulatory requirements.
The report acknowledged that managing new regulations while controlling costs was a formidable challenge in both data management and process automation, but also suggested that the right data management strategy could also be readily leveraged to manage risks and win the business development game.
Many leading asset managers and private banks are enhancing their business intelligence capabilities and beginning to adopt predictive analytics, according to Rob Toguri, UK data and analytics leader at EY.
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By GlobalData"Enhanced compliance and monitoring with much faster identification of potential issues is often a key goal," he says. "One powerful application is much more comprehensive trade surveillance to detect and prevent market abuse and fraud by merging trade data with other data sources.
"We are also starting to see banks make use of these latest tools and techniques to move trader surveillance and supervision towards the front office, which can also help drive down the overall cost of compliance."
Better safe than sorry
Steve Young, principal at consultancy firm Citisoft, says business intelligence enables asset managers to better interrogate their positions and investment decisions and should enable them to analyse how different scenarios will affect their portfolios.
However, Young also notes that few firms have so far used business intelligence tools specifically to monitor compliance and regulation.
"Most of the work so far has been on aiding the investment decision process and improving distribution. Whilst most firms will have compliance checking in the investment decision process, this tends to be using specific processes at various points and utilising compliance rather than business intelligence tools," he says.
Instead, an inverted relationship exists where asset managers use data collection and reporting after a breach has been identified to support what they are saying in conversations with regulators or customers, adds Vincent Kilcoyne, capital markets industry lead SAS UK & Ireland.
"To identify any irregularities in their processes, asset managers need to be able to monitor for suspicious activity and ensure due diligence on customers," he says.
"As a result, firms should be using business intelligence to identify normal business behaviour and practices. Organisations need to start by analysing customer activity and risk characteristics in order to monitor customer activity more effectively."
By grouping segments of customers or accounts together based on inherent characteristics, for instance the 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, continues Kilcoyne.
"Asset managers can then 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.
"Once armed with this information, it is possible to identify any variations and understand the elements that can lead to a potential breach so asset managers can continuously evaluate the firm’s risks, identify emerging trends and report malicious activity," explains Kilcoyne.
Explosion of compliance data-points
According to the EY report, the type of data that regulators ask firms to collect and report for analysis is often similar to the data institutional investors will seek to collect and analyse.
The good news is that insights from business intelligence technology can be quickly applied operationally, says Lexalytics CEO, Jeff Catlin.
"There is typically a hierarchy of response times – certain actions flag for immediate response, other patterns are only discovered when all communications are examined at the end of a day or at the end of a week," he explains.
"That is why doing this mechanically is important – so that you can look on different timescales and find anomalous communications patterns that extend across a set of exchanges and not just inside a single email."
Catlin refers to developments in compliance-specialised solutions to maximise the recall that is going to the compliance analyst, while Toguri refers to a future where asset managers utilise and merge big data from new sources such as systems process logs, voice, email and overlay it with powerful machine learning and cognitive techniques to improve their understanding of behaviours across business processes.
However, Young observes that while there are some firms looking to use business intelligence tools as part of their oversight obligations over third party suppliers, in many cases this is not sufficiently sophisticated.
"Business intelligence tools are predominantly used on known data to review past performance – we are yet to see these tools being widely used proactively to predict and manage upcoming issues and opportunities," he says. "Until then there will not be the pressure to create more sophisticated functions to specifically deal with asset management issues."
Beyond scratching the surface
Technology can provide much more functionality than is currently being realised by asset management firms, agrees Kilcoyne.
"Data volumes are only going to continue growing and problems are increasing in complexity while performance expectations are rising. Decision-making windows are shrinking and regulatory requirements are growing and ever-changing."
He is confident that technology has the capacity to highlight practices that could create regulatory issues within an organisation before they come to the attention of regulators, since irregularities in financial controls can usually be found in the ecosystems that surround a transaction.
"By consuming the vast quantities of structured and unstructured data that exist in and around the relationship between asset managers and their clients, it is possible to identify potential breach situations that arise from any communications or actions which are in close proximity to a customer interaction," says Kilcoyne.
Toguri says firms are also using analytics to "improve the client experience by building decision models visualised in dashboards, so as to target activity more appropriately and to identify, for example, the clients most at risk and actions to reduce this risk".
However, the challenge is moving insight into ‘business as usual’ in a more structured way, he concludes.
