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Data & Analytics

10:51 PM
George Travers, Partner, Deloitte & Touche, and Andrew Tyrie, Principal, Deloitte Consulting
George Travers, Partner, Deloitte & Touche, and Andrew Tyrie, Principal, Deloitte Consulting
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Monitoring Credit

Sophisticated analytics and credit derivatives are helping banks stay solvent.

Rising consumer debt levels in many countries have led to concerns about deteriorating credit quality. To mitigate their exposure, leading banks are employing sophisticated analytical techniques to improve underwriting, while also managing risk better through the use of credit derivatives.

While the quality of corporate debt appears to be generally strong, the soaring debt burden for consumers has raised red flags. Facing the prospect of rising interest rates or unsustainable property prices, banks need to manage greater risk in their global consumer lending portfolios.

After generally trending downward during the '90s, total U.S. household debt as a percentage of financial assets climbed to roughly 27 percent in 2003, although it moderated somewhat in 2004. The number of personal bankruptcy filings in the U.S. has risen 20 percent since 2000 to reach a record of approximately 1.5 million in 2003.

Rising debt levels come at a time when more banks are focusing on sub-prime borrowers, who have a greater chance of default. If done correctly, banks can profitably serve this segment. But for banks that have grown through acquisitions and maintain multiple credit and collections systems, sub-prime lending becomes more expensive and riskier. Separate credit systems may evaluate the same customer in different ways for a similar product, which can lead to sub-optimal decisions.

Rise of Predictive Analytics

Banks are using predictive models of consumer behavior to gain a deeper understanding of the credit risk associated with individual borrowers, rather than simply relying on broad underwriting criteria. These tools allow banks to make better decisions, not only in approving applications, but also in developing and pricing products.

The latest models take into account factors such as likely expenses, credit score, use of other products, loan repayment history and the current state of the housing market. Also, Fair Isaac compensates for customers lacking credit histories by using data from checking and savings accounts, payday loans, book or record clubs, furniture lay-away plans and rent-to-own programs.

Managing Risk Through Credit Derivatives

To mitigate credit risk, banks have increasingly used credit derivatives, instruments in which another party insures the bank against the default of a borrower or a portfolio of loans. According to the IDSA, the credit swaps market doubled in just one year to reach $5.4 trillion outstanding in the first half of 2004 (see chart below). Deloitte's 2004 Global Risk Management Survey found that roughly 60 percent of financial institutions with more than $100 billion in assets planned to use credit derivatives.

While the benefits are clear, there are risks. First, there is counter-party risk. The purchaser of the credit derivative may not be able to honor the obligation, or disputes can also arise over what constitutes a default.

Credit derivatives are used to create collaterized debt obligations (CDOs), portfolios of credit risk that are sliced into tranches of different levels of risk and sold to investors. Some CDOs - known as "Russian dolls" - contain investments in other CDOs. Some are even actively managed, as a mutual fund would be, so that the underlying portfolio can change. The complexity of one Russian-doll CDO led to a lawsuit in 2004 against a major global bank alleging that the credit derivative was misrepresented and badly managed.

Traversing the credit landscape will be more treacherous in the year ahead. Adopting the latest predictive modeling tools and the prudent use of credit derivatives can help banks make it through the woods safely.

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