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The Risky Game of Credit Underwriting

The Risky Game of Credit Underwriting

Credit underwriting decisions are a cornerstone of any economy. Made wisely, they can assist entrepreneurship, promote economic growth, and generally ensure that capital is allocated to its highest and best use. On the other hand, poor credit underwriting decisions can negatively impact an industry or the economy as a whole.  Recent troubles in the U.S. economy are directly tied to the poor credit decisions of lenders to support prospective home owners who had little money and provided little information about their financial strength in an over-inflated housing environment. Recent failures of banks such as IndyMac are partly tied to poor credit underwriting decisions and over-leveraging.  The failure of banks to consider the full range of construction risk is leaving many banks high and dry due to the recent spate of construction business failures, with many more to come. The five consecutive years of recent losses in the surety industry was directly related to poor credit underwriting decisions. With all of these losses you have to wonder what is going wrong. The answer is twofold: an unusually high tolerance for risk and credit decisions based upon insufficient data.

Creditors

In the case of mortgages that went bad, because loans could be packaged and resold, an anything goes atmosphere developed and many risk management practices were thrown out the window. Many loans were provided based on simple applications that provided minimal financial information. The fallout of this lending environment is showcased on Mortgage Lender Implode-o-Meter. In the case of IndyMac, a large portfolio of non-performing Alt-A loans, sometimes called liar loans, and risky construction and land development lending, left the bank with very little cushion in a falling housing market. Other banks impacted by losses only relied on financial data, failing to consider all the risks of lending to high risk industries such as construction and auto dealerships.

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Yin and Yang of Credit Underwriting

Yin and Yang of Credit Underwriting

This title seems especially appropriate following the recent Beijing Olympics. But today we are not talking about Chinese culture, we are talking about qualitative data and quantitative data, risk data and financial data, causes for success and causes for failure. What do these have in common? As the Chinese definition goes, they are two complimentary qualities that, when put together, form the whole.

Yin-yang Symbol

At the end of the day, business is about achieving profitability, which is defined as the ability of an enterprise to generate revenues in excess of the costs incurred to produce those revenues and is often measured by a rate of profit or rate of return on investment. Credit underwriters also seek to achieve profitability, and that means avoiding large, unforeseen losses. To maximize profitability, underwriters need to find the optimal balance between premiums charged and risk present.

Unfortunately, as discussed in The Risky Game of Credit Underwriting, underwriters are often working with insufficient, inadequate, or obsolete data so measuring the “risk present” becomes quite a tall order, and many times involves outright guessing. They have no way of knowing where the applicant lies in the ERM – Business Success Matrix. Fortunately, with the advent of a standardized mean to collect and analyze qualitative data, most of these underwriting deficiencies can be overcome. In this post, we’ll discuss how qualitative and quantitative data fit together to form a complete picture of an applicant during the credit underwriting process.

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