Borrower Beware: Lessons in Lending from the Subprime Crisis


We have often heard it said, “Something too good to be true probably is.” And so it applies to the way loans were issued in the years leading up to the subprime lending crisis. Political forces identified a need for low-income home-ownership and impressed on capital institutions the importance of more engagement with a high-risk market. Some simply blame the loan crisis on banks and greed. “The greater the profitable opportunities, the greater the coercive force. Ethics be damned” (Watkins, 2011, pp. 365).

The trouble with this view is that the forces of politics and greed are always upon us and crisis is not. Greed and politics have been with us for millennia and the subprime loan crisis was entirely new and episodic. A more sensible view is that a shift in forces created new dynamics for which the assessment of risk was extremely inadequate and undeveloped.

“Banks pursued making subprime loans to tap a new source of income without regard to the effect such loans might have on debtors” (Watkins, 2011, p. 363). Such a cynically exploitative view belies the fact that banks even had so little regard for what these high-risk loans might actually do to themselves.

It is important to recognize this financial collapse was not the desired outcome of politics, greed, or the borrower and lender. It is ultimately the truth that risk is poorly understood and ineffectively mitigated. “The three main rating agencies, Moody’s, Standard & Poor’s, and Fitch, have been scorned and vilified for their bad performance in rating subprime securities. They gave AAA ratings to securities whose quality was far lower” (Hill, 2010, p. 585).

So, “If the ultimate holders of credit risk do not completely appreciate the true credit risk of mortgage loans, then it is easy to see the resulting dilution in the originator’s screening incentives” (Purnanandum, 2011, p. 1882). Studies now show how the risk screening models failed. The “econometric default risk models based on historical data can be unstable over time, while Logit models of “loan data can generate over 40% fewer defaults than the actual number” (An, Deng, Rosenblatt, & Yao, 2010, p. 546).

Financial experts continue to struggle with risk models even to protect their own continued existence. So borrower beware when those desires most out of reach are conveniently met again with “something too good to be true.”


An, X., Deng, Y., Rosenblatt, E., and Yao, V.W. (2010). Model Stability and the Subprime Mortgage Crisis. Journal of Real Estate Financial Economics, (45, pp. 545-568). DOI: 10.1007/s11146-010-9283-y

Hill, C. A. (2010). Why did rating agencies do such a bad job rating subprime securities? University of Pittsburgh Law Review, (71, pp. 585-608).

Purnanandam, A. (2011). Originate-to-distribute Model and the Subprime Mortgage Crisis. The Review of Financial Studies, (24:6, pp. 1881-1915).

Watkins, J. P. (2011). Banking Ethics and the Goldman Rule. Journal of Economic Issues, (XLV:2, pp. 363-371). DOI: 10.2753/JEI0021-3624450213