Did they know what was going on? Did they have a choice?

 Office of the Comptroller of the Currency workshop, Feb Proposed National Institute of Finance (NIF) Collect system-wide data, build analytic tools and monitor systemic-risk  Committee to Establish a NIF Broad collection of concerned citizens Legislative Response – OFR is now law

 Office of Financial Research works for the Financial Stability Oversight Council Better data and analysis tools Long-term research Regulatory Commons Independent voice  Two components Data Center Research and Analysis Center

 Data Center Reference data  Financial Companies  Financial Instruments Reporting standards Collect system-wide, granular data (positions) Keep data secure Share data –  Member Agencies  General Public

 Research and Analysis Center Develop monitoring systems (financial stability) Measure and report on financial stability Evaluate stress-tests Policy advice Best practices in risk management Conduct, coordinate and sponsor research Investigate and report on financial disruptions Share tools and findings with member agencies

 Authority of the OFR Set reporting standards Require data (subpoena power)  Independence of the OFR Director appointed by President for fixed term Director makes key decisions (budget, hiring) Director testifies without prior review Funded by Fed first 2 years, after that by large financial institutions 50b+

 What would we do if data and resource barriers were removed?  Two time frames Short-term (2 years)  Initial risk monitoring efforts  Existing or easily obtained data Long-term (2+ years)  Research projects  Granular (position) data

 Know it when you see it?  Intermediation markets break down, impacting broader economy  Disruption that requires Gov. intervention

 Origins of stress or shocks Aggregation, crowded trading, leverage, bubbles Environmental, geopolitical or economic events  Propagation of shocks Interconnections and counterparty network Domino Effect and Repeated Fire Sales  Breakdown of markets Flight to safety, collapse of capacity

 Primary OFR Objectives Establish reference data Achievable risk-metrics, integrated into an initial ‘risk dashboard’ Establish a vibrant research capacity

 Build up of risk – looking for triggers Models based on existing data, default Bubble identification, monitoring leverage Aggregation in exposures  Network propagation Understanding the reaction function Pre-reference data network – marks, risk reports  Market breakdowns Mapping existing market structure and capacity Post-mortem of last crash

$3T CDS Notional outstanding AIG goes down, who else goes? $185b Gov. Loans

 Loss Distribution Tail events are rare – very little data Typically strong model assumptions

 Loss Distribution Tail events are rare – very little data Typically strong model assumptions Liquidity Failures  Can’t hedge  No replicating portfolios  Mean & Variance  Game Theory We are not in Kansas anymore

 Loss Distribution Tail events are rare – very little data Typically strong model assumptions Liquidity Failures Scenario Analysis  Linkages – rights, obligations (Not Netting!)  Granular Macro Economics  Reaction Function

 Loss Distribution Tail events are rare – very little data Typically strong model assumptions Liquidity Failures Scenario Analysis Economic Impact  CaR – Credit at Risk  DoL – Distribution of Loss

Confidence in the market is gone, no-one knows who is solvent

Flight to quality (US Treasury), credit markets freeze How long can companies ‘hold their breath’?

 Collecting network data Collect self-reported valuations (or marks) and risk summaries (derivatives or expected cash flows, by market shock) for each position, by counter-party (OFR glues this together). Complement with OTC – trade warehouse data… Establish unique identifiers – collect self-reported data (less glue needed). Have firms provide positions to third-party vendors, who then report to the OFR (more consistent) Have firms report positions to OFR.

 Capacities developed or enhanced (longer-term) Risk dash board Interactive scenario analysis: ‘flight simulator,’ ‘war gamming’ Identify rogue traders or rogue institutions. Detect and test the effect of a new financial instrument or new trends in financial behavior Facilitate secure distribution and sharing of data Make appropriately anonymized data available to public Crisis response teams Post mortem teams in the style of the NTSB Identify the questions that no one is thinking about, but that the OFR should be thinking about

 Competitive OFR risk dashboard Ongoing Development Initial Establishment Modeling Competition EvaluationEvaluation EvaluationEvaluation Visualization Competition Ev alu ati on Prototype Teams Primary Teams Risk Dashboard

 Related policy discussions Review establishing risk dashboards Year 2 report to Congress Establish a research management approach/infrastructure – portfolio of approaches Engaging the broader research community Legal scope of companies who must report Identify other data initiatives Data security, management and disclosure International data relationships (reference data, reporting standards, regulatory data)

 Dodd Frank Act becomes law  Treasury sets up initial OFR  Key Initiatives Reference data Common computing and data infrastructure Build initial risk monitoring system Key long-term research efforts Investigate past crisis