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Document Risk: Taming the Paper Tiger

Thanks to new regulations - written more often in gray than black white - investment firms are suffering from document risk, or poorly archived documents and information. While it may not have the white-hot urgency of liquidity or credit risk, document risk is still a source of confusion for today’s firms. WST spoke with Mahesh Muthu, associate principal at eClerx, about the ways firms can stay ahead of their documentation dilemmas.

Wall Street & Technology: Please explain what document risk is. How important is it to the compliance of financial firms?

Mahesh Muthu, eClerx: Document risk is made up of two components. One component is a subset of operational risk and is the risk that people, process, or technology related to documentation may fail. Typical examples include coding information from a document into a system incorrectly or failing to archive executed documents due to poor document lifecycle management. Although seemingly trivial issues, they can have a very large impact in areas such as derivatives trading.

The second component is “basis risk” between the document as executed and its representation within a system. This risk is related to a financial firm’s inability to code information at the granularity required due to limitations on the internal data model and also the inability to represent nuanced legal language which may be present in negotiated documents, such as those related to relationship or trade agreements.

The issue is important to the compliance of financial firms from the perspective of demonstrating to supervisory authorities the financial institution is running a controlled operation and thereby accurately managing it’s broader business risk, from a data sufficiency and decision analytics perspective.

WST: Is document risk a serious concern inside investment firms? Do they take it seriously compared to other forms of risks?

Muthu: Yes, it is a serious concern within firms, however as opposed to firms being continuously aware of the risk, as is the case with market and credit risk, the risk makes itself visible through operational losses which tend to be distinct events, often times related to large market events. It is in these stress cases that the level of documentation risk is tested.

Firms do take the risk seriously, but given that it is more difficult to detect and monitor then other forms of risk, they may have less sophisticated methods of controlling the risk and address it on a reactive, rather than proactive basis.

WST: How are most firms dealing with their internal document risk?

Muthu: Firms are dealing with document risk in several ways. They’re performing department-wide exercises to agree comprehensive data models and data dictionaries per document type and to understand downstream consumption. They’re also conducting risk reviews on legacy document populations to populate such data models and compare to existing data-sets, resolving any discrepancies. Many are overlaying such reviews with analytic dashboards to understand trends in agreements, outliers which may need to be renegotiated, and taking a portfolio view of the information in the agreements to understanding how to better manage day to day business, and potentially capitalize on the information.

At the same time, they’re standardizing documentation via industry initiatives and working on standard clause libraries across document types and creating centralized shared services teams to manage documentation with a consistent set of policies and controls per the steps above

WST: Please share a specific example of how your solution helped a real life investment firm. What problems did it solve? How did it help?

Muthu: A large Asian bank had tens of thousands of International Swaps and Derivative Association (ISDA) Master Agreements (MAs) and Credit Support Annexes (CSAs) which it did not have stored internally in a database format. As a result, it was not able to optimize its collateral, automatically identify which assets in inventory could be used to optimally satisfy outgoing margin calls on a day to day basis.

Because of that, the bank used primarily cash, resulting in millions of dollars of avoidable funding costs, which obviously decreased the profitability of each trade. We worked with the customer to create a granular data model, and leveraged a combination of people and technology to accurately mine the information from the agreements and structure it in such a format it could be loaded into the customer’s newly created golden source repository.

Using this digitized document information, and combining it with margin call, inventory, and pricing information, the firm was able to construct a collateral optimization program, significantly decreasing funding costs and as a side benefit, decreasing credit, legal, and regulatory risk.

Phil Albinus is the former editor-in-chief of Advanced Trading. He has nearly two decades of journalism experience and has been covering financial technology and regulation for nine years. Before joining Advanced Trading, he served as editor of Waters, a monthly trade journal ... View Full Bio

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