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The leading knowledge platform for the financial technology industry

A-Team Insight Blogs

Data Management Summit: Regulation and Risk Require a New Approach

Regulation and risk are driving a new approach to data management across financial markets, but they are not the only drivers as firms seek cost reductions, operational efficiencies and a means of using data as a business asset.

These issues and more were debated by a panel of experts at last week’s A-Team Group Data Management Summit in New York. Moderating the panel, Sarah Underwood, editor at A-Team Group, asked panellists to describe how regulation and risk are driving data management, which regulations are proving particularly onerous and what technologies and strategies data management practitioners can use to support change programmes.

Predrag Dizdarevic, partner at Element22, acknowledged that regulation and risk are the drivers behind most firms’ data management initiatives, and explained: “Many risk and regulation processes collect data from different silos, so it is a challenge to consolidate data and if it can’t be cross-referenced there is a problem. Because risk and regulation are a must do, data management programmes addressing them are being funded.”

Devesh Shukla, global head of reference data product development, Enterprise Solutions, at Bloomberg, pointed to the need for data management that provides ‘one version of the truth’. He added: “Historically, data has been seen as a cost of doing business, but we are starting to see firms viewing it as an asset, which is also driving data management change.”

Shukla went on to list the many regulations that firms must comply with today and those that will soon come into force, including Dodd-Frank, MiFID II, AIFMD, Basel III, Solvency II, EMIR, the Patriot Act and FATCA. He suggested that all touch the front, middle and back office and that all include three types of data – identification, classification and valuation data. He commented: “If a firm can manage all of these, it is in good shape.”

Mark Sutera, director of business development and sales, North America, at DTCC, described the regulatory problem, saying: “We will never be in short supply of government mandates, they will just keep on coming. The problem with them is that they all have specific templates and identifiers, so the question is how can the templates be centralised and all the data linked together. We help clients do that to make managing multiple regulations easier.”

While risk and regulation requirements are driving change, so too are business drivers including the need to reduce the cost and increase the quality of data. Sutera said the need is to find a happy medium between cost and quality, and not fall into the trap of putting more effort into building systems than managing content. Again, the need is for equilibrium if a firm is to avoid the enduring problem of garbage in, garbage out.

Regulations that require capital to be withheld at a level suitable to risk exposure were also cited by panellists as a cost of doing business that business could drive down with data providing one version of the truth. Taking this approach, business can also benefit from increased operational IT efficiencies, reduced operational risk and better decision making between offices.

Stepping back in time, Dizdarevic described previous data management practices in many firms as ad hoc initiatives designed to solve problems, which created problem silos. He also noted the vision of some companies to set up integrated environments, which required less change as new data was added, but pointed out that these platforms are now about 20 years old and also need to be renewed. Moving forward to managed services, he described the difficulty of providing economic value to clients who must still pay for data sourcing and technology infrastructure. Looking at the next wave of technology and considering data utilities, he commented: “Again the challenge is data sourcing, as utilities have to deal with the same problems posed by data vendors as end users.”

Despite these difficulties, he added: “Over the past few years, regulation has driven more investment in underlying data infrastructure. It is too soon to see the real results of this, but if nothing else, regulation has led to realisation at executive level that data management must be addressed.”

Technology to help resolve the data management issues of regulation and risk is emerging quickly and reflects requirements to acquire, integrate and move data. Shukla noted emerging solutions including private clouds based on managed services, distributed processing frameworks that allow the use of computing power as needed, and open source application programming interfaces (APIs) that support the movement of data.

He explained: “Clients are becoming more interested in managed services for functions such as Know Your Customer. In house, the need is often to organise data in four databases holding instruments, positions, entities and prices. With a flexible platform and open APIs it is then easy to use and move data around an organisation.”

Looking at the practicalities of implementing data management systems that will deliver consistent and high quality data, the panel agreed that governance is critical, as is buy-in from senior management and, potentially, a chief data officer. The panel also agreed that the process is long and includes many stakeholders, although there is a place for quick wins.

Sutera said: “There is a need for ownership of a programme as large as this and it has to be championed by someone at a senior level. From a practical perspective, the need is to look in the mirror and understand what is happening in data management, what is working well and what is not, and make rules that everyone in the firm must abide by.”

Dizdarevic suggested a pragmatic approach to building a centralised data management solution, including small steps that show results and demonstrate the value of data. He added: “It is important to establish why a firm is running a data management programme and to have a data management strategy. If you can’t explain it, you can’t sell it. The data management strategy needs to be defined on the basis of the business strategy and must reflect business priorities.”

Answering a final question on whether changes in approaches to data management for regulation and risk have made financial markets a safer place, the panel concurred that yes, new approaches have financial markets safer, but only a little.

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