Even before Big Data became the buzzword du jour, tech companies studied how data analytics could be used to manage and regulate businesses’ financial systems. There’s potentially a lot of money in that segment, as most businesses would pay through the proverbial nose for a solution that can store and crunch multiple financial databases with ease—and alert executives to any fraud and malfeasance.
The IRS already uses predictive analysis to rank tax returns on the likelihood of fraud; Oracle, Hewlett-Packard, and other firms are all exploring how to best leverage analytics toward client firms’ financial concerns.
Now IBM is jumping into that arena, with a new Signature Solution for risk management that monitors a company’s credit risk. In theory, financial executives and CFOs can use the platform’s dashboard to view customer and credit exposures from across an organization, and make decisions based on that information to improve profitability and dampen losses.
Managing credit risk is a complicated task for larger firms, which must coalesce financial information from disparate systems spread across a whole organization. With the judicious application of data analytics, however, what might have taken a roomful of accountants several days (and a whole lot of paper, antacids and coffee) can be done in relatively short order by a specifically tailored software platform.
In addition to managing risk and merging data from multiple silos, such a software platform could help a company follow all the necessary financial regulations. Breaking down data silos also has the superior benefit of surfacing any irregularities in accounting or cash flow, alerting financial managers to possible fraud.
That’s not to say that such systems are foolproof: an analysis is only as good as the dataset that feeds it, and many Big Data systems have issues with merging and analyzing multi-formatted datasets in ways that produce meaningful results. But if more IT vendors are producing financial-analysis tools, it could make the business of money management that much more efficient.
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