By James Kwak
Last week I wrote an Atlantic column about the fundamental reasons why big banks are always screwing up. In particular, given the effects of leverage and the short-term incentive structure, it pays to have lousy risk management systems, and it pays for frontline traders to evade those systems—even for the CEO, in the short term.
Today the Wall Street Journal reports evidence that the London Whale was told by his boss to boost the valuations of his trades; according to inside sources, “the favorable valuations might have been aimed at giving the losing trades time to recover and avoid setting off potential alarms at the bank.”
This is clear evidence for the too big to manage hypothesis: not only traders but heads of trading desks manipulating marks to take risks that the bank as a whole might crack down on. But we’ve known for decades that rogue traders (Nick Leeson, Jérôme Kerviel) are out there. The question is why bank managers don’t do a better job putting in place systems and processes to detect them. The most plausible answer is that they don’t want to because, in the short term, they have the exact same incentives as those traders: they like the risk and the higher expected returns it generates. It’s only when things blow up that they act all shocked.
The Importance of Excel
By James Kwak
I spent the past two days at a financial regulation conference in Washington (where I saw more BlackBerries than I have seen in years—can’t lawyers and lobbyists afford decent phones?). In his remarks on the final panel, Frank Partnoy mentioned something I missed when it came out a few weeks ago: the role of Microsoft Excel in the “London Whale” trading debacle.
The issue is described in the appendix to JPMorgan’s internal investigative task force’s report. To summarize: JPMorgan’s Chief Investment Office needed a new value-at-risk (VaR) model for the synthetic credit portfolio (the one that blew up) and assigned a quantitative whiz (“a London-based quantitative expert, mathematician and model developer” who previously worked at a company that built analytical models) to create it. The new model “operated through a series of Excel spreadsheets, which had to be completed manually, by a process of copying and pasting data from one spreadsheet to another.” The internal Model Review Group identified this problem as well as a few others, but approved the model, while saying that it should be automated and another significant flaw should be fixed.** After the London Whale trade blew up, the Model Review Group discovered that the model had not been automated and found several other errors. Most spectacularly,
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Tagged JPMorgan, software, technology