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Articles Tagged with: Operational Risk

GSE: Earnings Forecasting Framework Development

A $100+ billion government-sponsored enterprise with more than $3 trillion in assets sought to develop an end-to-end earnings forecast framework to project and stress-test the future performance of its loan portfolio. The comprehensive framework needed to draw data from a combination of unintegrated systems to compute earnings, capital management requirements and other ad hoc reporting under a variety of internal and regulatory (i.e., DFAST) stress scenarios. 

Computing the required metrics required cross-functional team coordination, proper data governance, and a reliable audit trail, all of which were posing a challenge.  

The Solution

RiskSpan addressed these needs via three interdependent workstreams: 

Data Preparation

RiskSpan consolidated multiple data sources required by the earnings forecast framework. These included: 

  • Macroeconomic drivers, including interest rates and unemployment rate 
  • Book profile, including up-to-date snapshots of the portfolio’s performance data 
  • Modeling assumptions, including portfolio performance history and other asset characteristics 

Model Simulation

Because the portfolio in question consisted principally of mortgage assets, RiskSpan incorporated more than 20 models into the framework, including (among others): 

  • Prepayment Model 
  • Default Model 
  • Delinquency Model 
  • Acquisition Model: Future loans 
  • Severity Model  
  • Cash Flow Model 

Business Calculations and Reporting

Using the data and models above, RiskSpan incorporated the following outputs into the earnings forecast framework: 

  • Non-performing asset treatment 
  • When to charge-off delinquent loans 
  • Projected loan losses under FAS114/CECL  
  • Revenue Forecasts 
  • Capital Forecast 

Client Benefits

The earnings forecast framework RiskSpan developed represented a significant improvement over the client’s previous system of disconnected data, unintegrated models, and error-prone workarounds. Benefits of the new system included:  

  • User Interface – Improved process for managing loan lifecycles and GUI-based process execution  
  • Data Lineage – Implemented necessary constraints to ensure forecasting processes are executed in sequence and are repeatable. Created a predefined, dynamic output lineage tree (UI-accessible) to build robust data flow sequence used to facilitate what-if scenario analysis. 
  • Run Management – Assigned a unique run ID to every execution to ensure individual users across the institution can track and reuse execution results 
  • Audit Trail – Designed logging of forecasting run details to trace attributes such as version changes (Version control system – GIT, SVN), timestamp, run owner, and inputs used (MySQL/Oracle Databases for logging)  
  • Identity Access Management – User IDs and access is now managed administratively. Metadata is captured via user actions through the framework for audit purposes. Role-based restrictions now ensure data and forecasting features are limited to only those who require such permissions 
  • Golden Configuration – Implemented execution-specific parameters passed to models during runtime. These parameters are stored, enabling any past model result to be reproduced if needed 
  • Data Masking – Encrypted personally identifiable information at-rest and in transit 
  • Data Management – Execution logs and model/report outputs are stored to the database and file systems 
  • Comprehensive User and Technical Documentation – RiskSpan created audit-ready documentation tied to logic changes and execution. This included source-to-target mapping documentation and enterprise-grade catalogs and data dictionaries. Documentation also included: 
      • Vision Document 
      • User Guides 
      • Testing Evidence 
      • Feature Traceability Matrix 

New Capital Planning Expectations for Large Financial Institutions and What It Means For You

The Federal Reserve Board (FRB) recently released regulatory guidance outlining its capital planning expectations for large financial companies. The guidance addresses many areas of the capital planning process where regulators are looking for continued improvement within large bank holding companies and attempts to clarify differences in the Fed’s expectations based on firm size and complexity. The guidance is effective for the 2016 CCAR cycle.

The Federal Reserve has provided separate guidance for two different categories of large financial institutions:

  1. LISCC Firms1 and ‘Large and Complex’ firms were provided capital planning guidance under SR 15-18, and
  2. ‘Large and Noncomplex’ firms were provided capital planning guidance under SR 15-19.

SR 15-18 Summary

Specifically, SR 15-18 applies to firms that:

  • Are subject to the LISCC framework,
  • Have total consolidated assets of $250 billion or more, or
  • Have consolidated total on-balance sheet foreign exposure of $10 billion or more.

For the largest and most complex firms, the guidance clarifies expectations that have been previously communicated to firms, including through past Comprehensive Capital Analysis and Review (CCAR) exercises and related supervisory reviews.

SR 15-19 Summary

SR 15-19 applies to firms and ‘Large and Noncomplex’ institutions that:

  • Are not otherwise subject to the LISCC framework,
  • Have total consolidated assets between $50 billion and $250 billion, and
  • Have total consolidated on-balance-sheet foreign exposure of less than $10 billion.

Implications of these capital planning guidelines

Both sets of guidelines (SR 15-18 and SR 15-19) lay out the governance, risk management, internal controls, capital policy, scenario design, and projection methodology expectations relating to the capital planning process. They also lay out some important distinctions between the two institution types relating to how models and model risk management are expected to be used.

We summarize some of the key differences between what is required of these two institution types in the table below. 

Current 2017 LISCC Portfolio Firms

According to the Federal Reserve, here are the current LISCC firms:

  • American International Group, Inc.
  • Bank of America Corporation
  • The Bank of New York Mellon Corporation
  • Barclays PLC
  • Citigroup Inc.
  • Credit Suisse Group AG
  • Deutsche Bank AG
  • The Goldman Sachs Group, Inc.
  • JP Morgan Chase & Co.
  • Morgan Stanley
  • Prudential Financial, Inc.
  • State Street Corporation
  • UBS AG
  • Wells Fargo & Company

[1] Large Institution Supervision Coordinating Committee (LISCC) – the Board of Governors of the Federal Reserve has the responsibility for the supervision of systemically important financial institutions, including large bank holding companies, the U.S. operations of certain foreign banking organizations, and nonbank financial companies that are designated by the Financial Stability Oversight Council (FSOC) for supervision by the Board of Governors. A list of LISCC firms can be found at http://www.federalreserve.gov/bankinforeg/large-institution-supervision.htm.


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