and servicing segments of the mortgage business. Further distinguishing the two firms is their differing reliance on analytic methods and data. X Bank has employed for several years relatively sophisticated data mining and simulation-based techniques to assess risk. Meanwhile Z Bank has just begun to develop risk data warehouses and building modeling capabilities to assess mortgage credit risk. It normally used simple measures of default risk that do not take into consideration possible changes in market conditions that could affect future credit risk outcomes. In its place, Z Bank has come to rely on the expertise of former underwriters put into their Quality Control department. Their job principally has been to perform postorigination reviews of originated mortgages and determine whether there have been any defects in the underwriting process that could pose risk to the firm.
In deciding whether to take on additional credit risk, X Bank relies on what it believes to be its comparative advantage: risk analytics. With losses on riskier segments of their business extraordinarily low, X Bank is satisfied that its estimates of credit risk are stable and reflect the underlying conditions in the market. Given this view, X Bank elects not to build up much of a quality control unit or to integrate their findings into credit-risk discussions. Z Bank, on the other hand, recognizes its limitations in its analytic capabilities and that even if it had such an infrastructure, it would be of limited value since the current environment is completely unlike any seen in recent memory. Consequently, they believe that using analytics exclusively to assess the amount of credit risk in their portfolio would need to be augmented by other factors including input from seasoned underwriters who have experience originating riskier mortgages.
The decision framework that both firms use to determine the amount of product risk each is willing to take on is dependent upon the common and unique set of circumstances (the situation) each bank confronts. X Bank believes it has better information and analytics by which to expand its business and be more competitive against other firms like Z Bank. At the same time, the QC department of Z Bank has concluded that the risks involved in expanding the product underwriting criteria are not sufficiently well understood to warrant taking on what appears to be higher risk. Z Bank management concurs with this conclusion despite the toll on market share this decision will cause, based on an understanding of the limitations of their data and analytics to accurately assess the amount of credit risk that could potentially accumulate should market conditions appreciably change.
By late 2007, the results from X and Z Banks’ decisions are clear. In the years following the original decision, the economy stalled, leading to one of the worst housing markets since the Great Depression. With home prices depreciating at double-digit rates and unemployment rising to 10 percent, credit losses on the riskier mortgages grew to levels that were multiples above what X Bank had estimated them to be in 2004. With their loan-loss reserves well understated for this risk and their capital levels weakening, X Bank experiences a run on its deposits that eventually leads to the closure of the bank by its regulator. In the years leading up to this event, X Bank had become the dominant mortgage originator, but did so at the expense of good risk management practices. Meanwhile, Z Bank largely avoided the mortgage credit meltdown by staying the course with its existing product set. That strategy wound up costing the firm several points of market share, but in the aftermath of the crisis the bank managed to pick up a major mortgage originator and through that combination regained a top-three position in the market while effectively managing its risk exposure.
A lesson from this example is that risk management decisions are highly dependent on the unique situation of the firm and it is essential that risk managers have their pulse on the factors that drive risk-taking. Dissecting the hypothetical case, X Bank risk managers relied too heavily on analytics at the expense of seasoned judgment, which in a period of unusually good credit performance should have signaled a greater emphasis on understanding the processes and controls underlying the underwriting activity. The situation in this case for X bank featured an accommodating economic environment, strong analytic capabilities based on historical information, aggressive management orientation toward market share at the expense of prudent risk-taking, and a limited appreciation for underwriting experience. Z Bank, facing the same economic conditions, came to a different conclusion and set of outcomes as a result. But in several important respects its situation was much different. It recognized its limitations in data and analytics and acknowledged its prowess in understanding the underwriting process and controls required to originate mortgages that could withstand different market conditions. Futhermore it had a management team that embraced its risk manager’s recommendations – not an insignificant factor that led to Z Bank’s making the right risk decision in the end.
Situational risk management thus is a case-by-case assessment of the factors influencing risk decisions. Figure 2.2 provides a framework for conceptualizing situational risk management. The primary activities of the risk manager of identifying, measuring, and managing the various risks of the company are influenced heavily by a number of internal and external factors at any moment. Clearly market, industry, and political forces establish an economic and regulatory environment that serve as a backdrop to risk management activities. The period leading up to the financial crisis of 2008–2009 was characterized by robust economic growth, relatively relaxed regulatory oversight, and fierce competition among financial institutions. This environment influenced corporate attitudes and perspectives on risk-taking and risk management. With markets and assets performing relatively well during the period, risk outcomes in the form of credit losses and other measures of risk performance were unusually low. Coupled with strong competitive conditions, risk management took on a secondary role to growth and financial performance prime directives. In such an environment, the risk manager faces significant headwinds in outlining a case for maintaining risk discipline when historical measures of risk are low and competition is high. Consider a risk manager’s situation in 2005 in establishing a view of mortgage credit risk for X Bank. As shown in Figure 2.2, home prices in the years leading up to 2005 had shown remarkable appreciation at the national level with most markets performing well above the long-term average. Armed with a formidable array of quantitative analytics to estimate expected and unexpected credit losses on the bank’s portfolio, the data would suggest that such a strong housing market would lead to low credit losses for the portfolio. Management during such periods can be biased against activities that will raise costs or impede business objectives, as reviewed in more detail in Chapter 3. While a strong risk culture and governance process can significantly mitigate management tendencies to marginalize risk departments, the risk management team must remain vigilant in the performance of its core activities and in regular and objective assessment of future performance. During such times, pressures to accede to business objectives rise, placing countervailing motivations on the risk manager that can influence his interpretation of risk-taking and prospective risk outcomes. Once the crisis began, as unprecedented risks emerged and many financial institutions failed, external conditions promoted a very different climate for risk management, where regulatory oversight of the financial industry stiffened and banks retrenched in an effort to stave off financial collapse as their capital deteriorated under the mounting pressures of large credit losses. In such an environment, greater focus on risk management, in part out of regulatory and financial necessity, becomes of paramount importance. Such vastly different internal and external conditions may introduce a set of tendencies for management, regulators, and risk managers to overreact. In such circumstances, underwriting standards may tighten to abnormal levels, resulting in a procyclical response that exacerbates the market downturn. Risk managers can seize this moment to strengthen not only the firm’s risk infrastructure but to shore up any deficiencies in governance and culture that may have been lacking previously.
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