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

Data Practices Have to Change to Support Risk Management, Says A-Team and GoldenSource

Subscribe to our newsletter

Given the current financial climate, a large proportion of the financial services industry is engaged in changing its approach to data management in order to better support risk management, according to recently published research by A-Team Group. The research, which was commissioned by EDM vendor GoldenSource, indicates that there is a general feeling within the industry that data practices have to improve.

Of the global tier one and two bankers and broker-dealers that responded to the survey, 66% indicated they were changing their approach to data management to support risk management. “With the goal of raising risk awareness, chief risk officers are emphasising data availability, timeliness and depth,” explains Angela Wilbraham, CEO at A-Team Group.

The resounding theme for risk management is that data practices have to change for the better, says Maryann Houglet, senior vice president of strategic consulting at the research and publishing group and contributor to the report. “Perhaps to no one’s surprise, the focus of this paper is on how data practices may be changing to support increased risk management,” she says.

The report, “Risk Management Drives Cross-enterprise Data Connections”, involved structured discussions with a global sample of senior individuals either directly responsible for risk controls or supporting practices, says Houglet. The majority of these individuals resided in tier two banks and broker-dealers, with a small sample of individuals at the tier one level banks to see if there were differences in data management preferences, she continues.

The focus of the report was to find where current data practices were considered insufficient to support desired risk controls. It also examines whether the industry is focusing on specific shifts in data practices to facilitate risk management and prepare for the future.

It is the chief risk officers that are driving forward change in the area of data management, according to 89% of the respondents to the survey. The findings of the report also indicate that these chief risk officers and their senior level risk officers need the ability to identify the firm’s exposure to external – market, industry and economic – events at any time.

There was a trend towards centralisation within data management identified by 60% of the respondents to the survey, but there were concerns raised about the cost of such projects.

All of the respondents ranked valuations, issuer and entity identification and counterparty data at least average in importance for assessing exposure. Holdings information received the top ranking, with 64% identifying it as the area of highest importance in terms of risk management.

The focus is also on timeliness, according to the report. One respondent, a risk officer at a North American bank, stated: “Firms absolutely have to go to real-time data in markets as volatile as these, so you can capture every instance of change important to the firm’s exposure.”

In order to achieve this goal, the report identifies the five characteristics in data management practices that chief risk officers are looking for in the current market. First of all, they are looking for access to more timely and, where appropriate, real-time data. They are also seeking to establish linkages across data types and asset classes and increased depth in information behind investments.

According to the report, they need flexibility in the data management systems in order to be able to aggregate and roll-up data, such as counterparty and industry data. There must also be support for various hierarchies of risk measures in these data management systems, the report asserts.

As one respondent put it: “We really need real-time to keep up with volatility and the market risk that volatility brings. Credit risk measures need at least intraday data.” This sentiment was consistent across interviews, says Houglet.

The research confirmed that risk officers and their support teams are clearly reviewing their firms’ data management solutions to facilitate risk practices and keep management informed, she explains. It also confirmed that future solutions will require more timely data, flexibility, links across data types, and adaptability to ongoing change. These requirements, coupled with industry consolidation, may push a larger number of institutions to consider external vendor alternatives, the report suggests.

Subscribe to our newsletter

Related content

WEBINAR

Recorded Webinar: How to optimise SaaS data management solutions

Software-as-a-Service (SaaS) data management solutions go hand-in-hand with cloud technology, delivering not only SaaS benefits of agility, a reduced on-premise footprint and access to third-party expertise, but also the fast data delivery, productivity and efficiency gains provided by the cloud. This webinar will focus on the essentials of SaaS data management, including practical guidance on...

BLOG

Data Products: Transforming Fraud Detection in Financial Services

By Suki Dhuphar, Head of EMEA, Tamr. Cybercrime assumes many shapes and forms. As a result, it’s often challenging to identify fraudulent behaviour and subsequently address it. Traditional methods frequently fail to detect and combat illicit activities, leading to financial losses and eroded trust. Yet, even today, one of the most prevalent solutions to enhance...

EVENT

Data Management Summit London

Now in its 14th year, the Data Management Summit (DMS) in London brings together the European capital markets enterprise data management community, to explore how data strategy is evolving to drive business outcomes and speed to market in changing times.

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...