Risky business

Every time a bank is approached by a customer for a credit card or loan, there is a gamble involved on their part. They must weigh up the odds of how long it will take the individual to pay the money back, how likely it is they will miss a payment, or if they will default altogether.

The same goes for a healthcare insurance provider. How likely is a customer to get ill? Is it likely to be a critical illness? How long are they likely to live? These are the questions insurance firms seek to answer before approving any policy.

In making these decisions, companies rely on statistical analysis, technology that allows them to sift through huge volumes of historical data looking for patterns or anomalies in customers’ behaviour, which subsequently provide insight into how they are likely to behave in the future.

One company, US-based SAS Institute, has largely been responsible for the development of proliferation of statistical analysis, sometimes referred to as ‘business intelligence’, across industries from banking, to healthcare, to telecommunications, to government.

The technology is used in everything from calculating the probability of a potential customer defaulting on credit card payments, to insurance providers seeking to detect fraudulent claims and governments to prevent tax evasion before it actually happens.

Since being founded in 1976, SAS has grown into a close-to-$3bn-per-year business and the world’s largest privately owned software firm. SAS’s technology is now used by four out of every five companies on the Fortune 500 and it employs more than 13,000 people.

In the three-and-a-half decades since its inception, SAS has recorded positive growth every single year, which has helped make founder and CEO Dr James Goodnight an extraordinarily wealthy individual. Forbes magazine estimates that his fortune currently sits at a handsome $7.3bn, making him the 43rd richest man in the US and 125th in the world. To add to this, SAS has also been voted as the world’s best multinational company to work for in the world on several occasions.

The origins of SAS can be traced back to the late 1960s, when Goodnight was studying towards a doctorate in statistics at North Carolina State University. Far from its current status as a technology for detecting exotic crimes like money laundering and fraud, SAS in its beginnings was used for the more mundane task of analysing crop treatments.

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