Understanding exposure to LIBOR and the risk associated with it is a critical first step. Firms will need this information to better understand potential outcomes, allowing them to better determine action steps for their businesses, operations and clients. Many firms will use existing systems containing structured data to capture a notional value or risk value of exposure. Such an assessment can provide an initial estimate of the challenge ahead, but not a full understanding of the range of possible outcomes.
Refining exposure and risk must go beyond straightforward system value to include consideration of contractual and legal risk, and economic exposure. These elements are best evaluated when combining structured data (from systems) with unstructured data (from contracts and other documents). Information such as consent, termination rights and cessation language are some of the details needed to truly develop an accretive action plan. The immediate challenge for many firms will be to gather, organize, analyze and manage this additional unstructured data.
Organizing, analyzing and managing data from structured sources, while complex, is a well-understood task that can be accomplished via data engineering tools and approaches. In contrast, organizing information from unstructured sources poses new challenges.
The new challenges are manifold and can almost seem insurmountable. Unstructured data can exist anywhere – in risk and accounting systems, spreadsheets and filing cabinets. The quality of the data can vary considerably – from digitally pristine to indecipherably handwritten. Data for financial contracts may not be located in a single system or even one location and, in some cases, deals may have been largely disaggregated into component pieces, making recombination quite aggravating. And any changes to contracts in the form of amendments may not be linked in ways that create a transparent association.