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How Stanford Is Using Analytics to Detect Fraud and Abuse

Blog: Enterprise Decision Management Blog

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A new article in eCampus News reveals how Stanford University is solving a Big Data problem using FICO analytics.

“How do you identify fraud, waste, and abuse when your procurement office handles more than a million transactions a year and $2.2 billion in disbursements?” the article asks. “Manually, if you’re Stanford University, just like most institutions of higher education do. But, faced with a changing audit landscape, the California school is now looking to analytics to help detect transaction irregularities.”

Stanford is using FICO Falcon Assurance Navigator to analyse each transaction that requires a payment from Stanford. The university is now in phase two of the project, which will apply FICO’s machine learning technology.

“What’s really exciting is that it’s going to look at receipts, images, and very unstructured data, and begin to make sense of them,” Ben Moreno, chief procurement officer for Stanford, told the eCampus News. “It will start to look at free-text fields and begin to mine them for intelligence in potential fraud, waste, and abuse cases.

“The tool is built in such a flexible manner that it’s constantly learning and getting smarter. You can add or edit rules. As the federal government makes changes to the regulations, we have the ability to make those edits along the way.”

This technology has benefits for any organization that wants to control expenses or meet federal guidelines for use of its funding. Stanford’s case study provides a good look at the future of expense controls.

The post How Stanford Is Using Analytics to Detect Fraud and Abuse appeared first on FICO.

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