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How many decimal places in the right answer?

Following up on my recent post on the value of Big Data in assessing risk, it seems that recent discussions about international capital and related risks have never been more lively. (And who even remembers the Great Ruble Crash of Two Thousand And Last Week?) The Argentinians are still adamant that it’s not a default if they don’t call it one. The Greeks are still arguing amongst themselves about a Euro exit while banks all around the world scramble to run all the scenarios. Even the folks running casinos are struggling to get it right these days. (Meanwhile, scientists have claimed to have perfected an infallible strategy that guarantees you will never again have to lose at Heads Up Limit Hold’em).

So where and how does a bank, or a country for that matter, place their bets?

The big currency news this week, of course, is that the Swiss have unpegged their Franc from the Euro, and thus have chosen in favor of their Foreign Exchange reserves (it would have cost a giant portion of them to continue to defend their peg) over, likely, their export-dependent economy, at least in the short term. (Did you know that the Swiss, behind only the Chinese, the Japanese and the Saudis, possess more ForEx reserves than any other country?) It’s hard to know how to place ones bets in this sort of situation. Do you look at that pile of cash (A full half a TRILLION!) and appreciate most the power that conveys? Or do you fear for your shares in UBS and Credit Suisse, and watch with trepidation for what the Swiss National Bank might do next because of the volatility in CHF? I know, if I were a banker trying to assess the creditworthiness of my counterparty or loan applicant, I would be paying a lot closer attention today if they would happen to be Argentinian, Greek, or Swiss. (Or Russian, or Saudi–let’s not forget what’s happening to oil prices these days, either–or fill-in-the-crisis-of-the-week-country-here, etc. etc.)

If only there were a computer simulation that was as good at international finance as the folks in Alberta, Canada have proven to be at poker…

Either way, some prominent banks aren’t waiting for definitive proof to be making some big investments in analytics technology. Duncan Kerr’s latest analysis in Euromoney talks about several examples of big bets being made in the confidence that better analysis will yield better outcomes. And it’s not just investing in mass personalization and customer-oriented analysis. (See Chris Skinner’s contributions to those discussions, also on
Banking View here and here).

Financial institutions are seeing the value of better insight into their biggest problems. It’s not clear if this increase in computational firepower is going to result in highly precise wrong answers, but you only need the slightest of statistical advantage in margins in order to beat the house. (Just ask Caesar’s).

For more perspective on the opportunities, have a look at this recent survey by the Economist Intelligence Unit about Big Data and Risk in Retail Banking.

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