Committee to Establish the
 
National Institute of Finance
Providing the data and analytic tools needed to safeguard the U.S. financial system
Depth
Could costs be reduced by collecting smaller volumes of aggregated data, rather than larger volumes of granular data?  E-mail
To the contrary, it is actually easier, both for regulators and financial firms, if data are collected in the same forms in which they are generated originally. Once data reporting processes are standardized, the least costly and least burdensome way to report transaction data is with the equivalent of an electronic “cc” automatically attached to each trade confirmation message. A requirement that firms aggregate data prior to transmission would actually increase the burdens on firms. 
 
Won’t the NIF simply be swimming in data when crucial answers are needed?  E-mail

By providing common reference databases and a common reporting language, the NIF will be able to integrate the data it collects in an automated fashion. Because the NIF will require entities to send electronic cc’s for all of their transactions, on a regular basis, the NIF will always have a current view of the financial system. Because these data will be properly organized and tied together in a consistent manner and because the NIF will have dedicated high performance computing resources to process the data, the NIF will be able rapidly to provide decision-makers with needed summaries and aggregations – especially during a time of crisis.

 
Are there situations where the NIF would collect or use aggregated data? When and why?  E-mail

Wherever practicable, the NIF would collect data at the most granular level. Aggregation is a one-way street: granular data can be aggregated, but the original detail ordinarily cannot be recovered from aggregated data. Collection of granular data is recognized as a best practice, and it governs data collection strategies at most financial, commercial and telecommunication companies today. It is facilitated by advances in data storage and data access software. Once collected, however, the same data might be used in aggregated form for any number of purposes, such as calculating regional summary statistics, or peer group benchmarks for industry subgroups. “Tick” (or trade-level) data is a good example: data on each trade enables analysis at the most granular level (trade detail), as well as at aggregated levels (end-of-day, quarter by quarter, year over year, etc.).

 
How will granular or contract-level data help regulators deal with the growing complexity of financial contracts?  E-mail
Some of the risks that are hardest to measure are those associated with highly complex and innovative financial instruments whose payoffs depend on other financial instruments, assets, or external factors, often in intricate ways.  Without detailed, granular data, it can be difficult or impossible to understand the risks involved with such complex instruments.  For example, shocks to the value of underlying collateral at the bottom of a complex structured product (e.g., mortgage-backed or asset-backed structured products) can result in “toxic assets” that cannot be priced. In order to understand the risk to solvency of financial entities that hold these complex instruments, and the risk in turn to the counterparties of these entities, the NIF must be able to see how all of these complex financial instruments connect to their underlying collateral. This capability depends on access to granular, contract-level data.
 
How will granular or contract-level data help regulators understand an emerging crisis?  E-mail
The NIF must be able to understand the capacity of the financial system to manage and distribute risks; to monitor how risk flows through the financial network, and to identify potential points of failure. This understanding can only be built up based on a detailed view of market liquidity (how frequently and deeply instruments trade), and a clear analysis of the obligations and rights of liquidity providers. For example, financial entities that are under stress are forced to sell assets, which can lead to a fire sale and a lack of liquidity. As liquidity disappears in one market they are forced to sell other assets, which can quickly lead to a lack of liquidity in other markets. The failure of multiple markets can cause a widespread lack of confidence, resulting in runs on the entire market.
 
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