Question

Cracking Fraud with Government’s Big Data

What are some ways that data mining could be used to detect fraud in health insurance claims?

How could private insurance companies and public government agencies collaborate to combat insurance fraud?

What types of business skills would be necessary to define the rules for and analyze the results from data mining?

What business processes are necessary to complement the IS component of data mining?

Answer 1

What are some ways that data mining could be used to detect fraud in health insurance claims?

            Data mining has been used to recover billions of dollars on detecting fraud in health insurance claims. “They arm the insurer’s special investigative units with information about potential fraudulent billing patterns buried in millions of legitimate claims, spotting unusual trends that no human being working along could ever see” (Wallace, 2013, pg.239). Some healthcare services have implemented in software that can detect fraud health insurance claims. “Fraud detection systems aims at real-time analysis to build predictive models that can detect fraud and stop it before it occurs. Conducting investigations and decisions making regarding fraud is carried out more quickly than before, as the classification system is automated to avoid labor-intensive work” (Dr.Zikos). One major step in data mining is to spot the fraud before any claim is paid.

How could private insurance companies and public government agencies collaborate to combat insurance fraud?

            Private insurance companies and public government agencies are able to share data analytics in order to combat insurance fraud. One the website www.hhs.gov, it is mentioned that “new partnership is designed to share information and best practices in order to improve detection and prevent payment of fraudulent health care billings”. They will be able to share information and insights in order to make suspicious activities easier to identify. “Government agents go after scammers once they see a pattern of abuse, but if the money was already paid, it is difficult claims. Fraud detection systems, on the other hand, can operate quickly enough to catch suspicious claims before they are paid” (Wallace, 2013, pg. 239).

What types of business skills would be necessary to define the rules for and analyze the results from data mining?

            In order to define the rules and analyze the results from data mining, there has to be special business skills that need to be applied. These special skills take training in order for investigators to understand data mining and analytics. “The analysts must work closely with investigators to apply human judgment as they create new rules and follow data leads. Ongoing training is essential, especially because the fraudsters continue to launch novel and increasingly complex schemes, changing their tactics to step or two ahead. Knowing when, where, and how to drill down into the data to see meaningful patterns is a skill that agents must learn” (Wallace, 2013, pg.239).

What business processes are necessary to complement the IS component of data mining?

            Statistics and modeling techniques is a processes that is seen to complement the IS component of data mining because you are able to see “real patterns-ones that probably did not occur just by chance” (Wallace, 2013, pg. 219). “Investigators who master these skills will be able to combine their own experience and judgment with an immensely powerful information system to help reduce health care costs for everyone” (Wallace, 2013, pg. 239).