About a-team Marketing Services
The knowledge platform for the financial technology industry
The knowledge platform for the financial technology industry

A-Team Insight Blogs

Counterparty/Client Data Efforts Kicked Up a Notch to Support Proactive Risk Management, Report Finds

Subscribe to our newsletter

Proactive risk management is a key driver for investment in improving client and counterparty data, finds a new report from A-Team Group, sponsored by GoldenSource. While it has been well publicised that regulations like KYC and AML have forced firms to pay tactical attention to client and counterparty data, it is now clear that there is a move towards more “defensive” management to ensure compliance through proactive risk management. Firms want to achieve full awareness of potential exposure, on an ongoing basis. The recent “credit crunch” has only served to reinforce this trend, the research report suggests.

Eighty-seven per cent of respondents to the research, carried out among banks, broker/dealers and asset managers, cited compliance as the most important reason for aggregating customer data, followed closely by risk (73 per cent), then credit (60 per cent), with a minority (36 per cent) selecting performance measurement (analysis and service reporting) as most important.

The report – New Wave for Counterparty and Client Data: Traditional Methods Make Way for Proactive Risk Management & Compliance – finds that firms have been focused in the past few years on getting internal counterparty data cleaned up and organised. Ninety-three per cent of respondents said they have centralised or plan to centralise management of client/counterparty data; 92 per cent have or plan to have new processes for maintaining this data and defining more rules. Impressively, some two-thirds have completed those modifications.

While most respondents have modified or plan to modify their inhouse solutions (76 per cent), or legacy systems (72 per cent), 38 per cent have implemented a third-party solution to address the issue. A-Team suggests firms favour using legacy inhouse systems for client/counterparty data for three reasons: first, the nature of the data is such that, unlike instrument data, it is fundamentally tied to an institution’s business practices and strategy. Therefore, firms have traditionally managed this information inhouse and treated it confidentially; second, over the years, firms have created new businesses, expanded geographically, and merged with other firms – resulting in a variety of legacy systems to track client/counterparty data. Part of the investment made during the past few years has been in organising cross-business and cross-regional information to get a better picture of exposure, as well as reducing duplicate effort; and third, there are no generally accepted, standardised sources for legal entity data, in part because of the proprietary nature of the data.

It is possible that as senior managers seek flexibility, consistency and scalability in managing client/counterparty data alongside reference data repositories, this bias towards use of inhouse systems may be challenged, A-Team reckons. This could also be encouraged by the ongoing maturity and general acceptance of third-party data management solutions, it adds, coupled with the need to include client/counterparty data in order to achieve the overall risk profile afforded by centralised reference data repositories. In parallel to the growing acceptance of external data management solutions, third-party sources for counterparty data are beginning to resemble those in the more established “product reference data market”, A-Team believes.

In fact, the report contends that the lines between instrument and counterparty data repositories are blurring, as the need for the two types of data to be integrated increases. “By way of illustration, the importance of accurately modeling relationships in complex collateralised debt transactions with ‘nested’ levels of repackaging and redistribution is manifesting itself in the credit markets currently and demonstrating the interrelated nature of instrument/product and counterparty data,” A-Team writes. “Close integration between the two data areas – both in technical design and enterprise deployment – is needed to provide a solid foundation and the depth of awareness required for firms to actively manage the risk/reward trade-offs these products bring.”
This report is the second in a series being undertaken by A-Team on behalf of GoldenSource. The first focuses on instrument data. To view the full results go to www.a-teamgroup.com/research.php

Subscribe to our newsletter

Related content

WEBINAR

Recorded Webinar: Data Standards & Identifiers: Where are they helping and what more can be done?

Beyond regulatory compliance, what are the opportunities for leveraging standards to improve operational efficiencies? Financial institutions are starting to realise there are clear benefits in taking a strategic approach to data standardisation as they move to more data driven approaches which require good quality, accurate data for analytics and AI programmes. This webinar will review...

BLOG

Reframing Corporate KYC: Encompass Targets Back-Book Exposure with Scalable EC Review

For many SME focussed banks, KYC investments have streamlined the onboarding journey but legacy KYC records – the back-book – often remain dormant until a regulatory inspection, or an enforcement case at a peer institution, forces a wholesale review. The challenge that follows is how to remediate at scale, with urgency, and without the need...

EVENT

RegTech Summit New York

Now in its 9th year, the RegTech Summit in New York will bring together the RegTech ecosystem to explore how the North American capital markets financial industry can leverage technology to drive innovation, cut costs and support regulatory change.

GUIDE

The Reference Data Utility Handbook

The potential of a reference data utility model has been discussed for many years, and while early implementations failed to gain traction, the model has now come of age as financial institutions look for new data management models that can solve the challenges of operational cost reduction, improved data quality and regulatory compliance. The multi-tenanted...