Real analysis of VaR models, credit models and balance sheet numbers

Numbers are alluring. They are seductive and they are universal. Mind Your Language was not set in a maths class.

When young graduates anywhere in the world are recruited into Risk Management, they face a mighty struggle to grasp all the complexities of the institution and the markets that they land in. The temptation is to stay in their comfort zone. For maths or accounting graduates, that means the numbers that they know how to deal with from their text books at school. In Risk Management, be it in market risk with VaR, in credit risk with credit ratios or in modelling, that comfort zone is never far away.

Are the best market risk analysts also the best mathematicians? Are the best credit analysts also the best accountants? We all know that the correlations are weak (see – numbers again). So, as we are in the business of providing global risk managers with great young analysts in India or China, what is the secret sauce?

Let’s say up front that nothing happens without great technical foundations. The huge competition for places at the top schools in India ensures that their graduates are smart. Affording them is never an issue for G7 financial institutions , but understanding them well enough is…

Once you have smart kids in hand, and their technical foundations are checked and developed, it’s crucial to connect those technicals to what is real. “This desk’s VaR number has gone up 1.2%”. “The leverage ratio of this company has risen 0.2 turns”. “Credit card delinquencies have gone down in Manhattan and the Canary Wharf area by 12bp this quarter”. OK – but what does that mean?

Step one to enlightenment, of the ancient Indian and the Leipzig varieties, is to introduce a whole new set of technical knowledge. Mathematicians, in order to manage risk properly, need to understand what traders trade. Accountants and MBAs need to understand that sabre rattling in a potential conflict zone might affect the oil price. Where are Manhattan and Canary Wharf anyway? (No-one is born knowing this, by the way).

That’s still not enough to make a great young Risk Management analyst. Beyond knowing what a trader trades, they need to know how and why. Sabres are rattled all the time – which ones will hit the oil price in a lasting way? What was the bonus round like this year in the City, and will London bankers use them to pay down debts this year?

It’s at this point that training gets seriously into the tacit and judgmental. We all learned how to approach these things through a long apprenticeship, served under a master banker. Such people are not readily available in India. The only way that’s going to happen is if your off-shoring provider employs a group of veteran analysts in NY, London, HK and other major global centres. (How solid can your analysis be if you learned it from another kid?). This is how Frontline Analysts approaches things – in the good old way, with apprenticeships (Indian) served under masters (global capital markets veterans).

So, there is no good risk management analysis, even in quantitative fields, without getting behind the numbers to what produced them, and then understanding why the causes move as they do. I wonder whether, if this rather simple philosophy had been applied to the number-driven, dodgy balance sheet, meaningless model output cock-ups of the past 25 years, things would not have turned out better for all.