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It was like watching a Lamborghini fall apart. Over just a few weeks this year, the supposedly precision-engineered global financial system failed spectacularly 鈥� and the influential 鈥渞ocket scientists鈥� employed by banks to forecast risk didn鈥檛 see it coming.

Colossal losses on dodgy home loans drove giant financial firms to the brink of disaster, and sometimes beyond. Governments had little choice but to intervene, at huge cost: bailing out banks, guaranteeing loans and slashing taxes and interest rates. Their desperate efforts may yet fail to fend off a downturn to rival the Great Depression.

How could it all have gone so wrong? After all, bankers have invested a lot of time and money in mastering financial risk, and built elaborate mathematical models that should have highlighted the potential for disaster. But as conditions worsened, those models proved hopelessly inadequate.

Basic assumptions made by the modellers about house prices and borrower behaviour were wrong; financial sleight of hand that was intended to turn risky credit into rock-solid investments failed. Meanwhile, dizzyingly complex financial instruments designed to spread the risks across the financial system worked all too well 鈥� they meant everybody was affected.

Some argue a crisis might have been averted had the banks and their supervisors paid more attention to the fact that they could lose access to ready money, and that trouble at one bank might spread to others. Other critics reckon that modellers didn鈥檛 pay enough attention to extreme events, dismissing them as episodes that posed no real threat.

There are also those, like Nassim Taleb of the London Business School, who are ill suited to these subjects. Markets and economies might just be too complicated and mercurial to ever be truly predictable. Yet optimists hope we might find answers by looking further afield 鈥� at complex natural systems such as swamps, for example. If they are right, the banks of the future may be staffed not with rocket scientists but with ecologists.