Bank of America avoids gridlock in credit-risk scoring, forecasts using SAS®
Modeling portfolio credit risk is a fundamental function in banking today. Loan products, such as lines of credit, mortgages and credit cards, entail a high degree of risk for banks, and on a large scale, especially in turbulent economic periods -- defaults produce difficult situations and huge implications for both the lender and the borrower. Banks regularly employ credit-risk management processes to monitor and assess credit portfolios, to make certain estimates, and to understand their risk position and value of assets at any given time. In today's complex and ever-changing financial system, powerful, rigorous and accurate credit-risk management processes and technology play a critical role in mitigating a lending institution's exposure.
Bank of America is one of the world's largest financial institutions, serving individual consumers, small- and middle-market businesses and large corporations with a full range of banking, investing, asset management and other financial and risk management products and services.
With approximately 59 million consumer and small business relationships, 6,000 retail banking offices and more than 18,000 ATMs, Bank of America is among the world's leading wealth management companies and is a global leader in corporate and investment banking and trading across a broad range of asset classes.
The Corporate Investments Group (CIG) manages Bank of America’s available-for-sale portfolio and is responsible for modeling and calculating the probability of default (PD) on the 9.5 million mortgages it services. In addition, the group calculates the market value, prepayment speeds and sensitivity to changes in interest rates and hedges these risks for the $19 billion mortgage-service-rights asset. Recently, CIG began assisting with the task of forecasting loan losses for the bank’s credit card portfolio.
The need for speed
"We needed a solution that addressed today's business problems, as well as a solution with the flexibility for any future business requirements," says Russell Condrich, Senior Vice President, Corporate Investment Group. "Processing large, multi-terabyte datasets in a quick, efficient manner was a key requirement for us and SAS performed flawlessly. Without SAS, processing times would be longer, hedging decisions would be delayed and, ultimately, the bank would be behind the market."
SAS® and IBM show results
The platform pulls data from eight systems of record (SOR), amounting to hundreds of millions of records, or 30 terabytes of source data, and allows the SAS environment to consume 3.9 gigabytes of I/O throughput per second from IBM's XIV storage environment. Approximately 30 users now have unfettered access to the environment, as opposed to the shared services environment of the past, in which user time was competitive and response times varied dramatically due to the high number of jobs being executed.
As an example, Lange adds, "we have to score a particular portfolio of 400,000 loans with our suite of models, using multiple scenarios, and we need to run it over the 360 months of the mortgages' life. That process used to take three hours, now it takes 10 minutes because of the parallelization capabilities of the grid. The ability to go from three hours to 10 minutes on a job demonstrates a tremendous increase in our ability to deliver information and make decisions."
“The bank has a strong desire to enable loss forecasting as accurately and quickly as possible, right up to the senior executive layers of the organization,” says Lange. “The only way we can do that is to have sufficient IT resources to score loans and appropriately assess risks. The partnership between SAS, IBM and our internal technology group has provided a platform for us to demonstrate risk management leadership.”
The results illustrated in this article are specific to the particular situations, business models, data input, and computing environments described herein. Each SAS customer’s experience is unique based on business and technical variables and all statements must be considered non-typical. Actual savings, results, and performance characteristics will vary depending on individual customer configurations and conditions. SAS does not guarantee or represent that every customer will achieve similar results. The only warranties for SAS products and services are those that are set forth in the express warranty statements in the written agreement for such products and services. Nothing herein should be construed as constituting an additional warranty. Customers have shared their successes with SAS as part of an agreed-upon contractual exchange or project success summarization following a successful implementation of SAS software. Brand and product names are trademarks of their respective companies.
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Bank of America
The Corporate Investments Group needed to reduce processing time for credit-risk modeling, scoring and loss forecasting and increase ad hoc analysis time, while ensuring business continuity and guaranteed "up-time" for these mission-critical functions
SAS Enterprise Risk Management on SAS Grid Computing and SAS Scalable Performance Data Server on a 224 core IBM BladeCenter® grid and the IBM's XIV® Storage System
The solution has reduced the banking group's probability of loan default calculation time from 96 hours to just four and reduced its scoring routine of 400,000 loans from three hours to 10 minutes. Processing time for any given project has been reduced by 90 percent, is three times faster, yields timely decisions around defaults, helps minimizes losses and can handle new growth opportunities for bank's loan portfolio
“Without SAS, processing times would be longer, hedging decisions would be delayed and, ultimately, the bank would be behind the market.”
Senior Vice President, Corporate Investment Group
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