How Predictive Analytics Work

Predictive analytics use sophisticated models, a set of mathematical equations designed to forecast future behaviors based on current or historical data. Models are built to identify precise, reliable behavioral patterns that are clearly understood. Once built, a predictive model can instantly execute a complex analysis of data, such as transaction or account data, in order make a forecast of the future, or classify current behavior.

Many predictive models can express extremely complex and interrelated relationships between dozens, hundreds, and even thousands of pieces of data as a single number, a score. They help organizations manage complexity by distilling the meaning from a large body of data. The scores in predictive models can indicate the likelihood of a certain behavior or event occurring in the future, with the highest number indicating the greatest degree of risk.

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For instance, a predictive model built to analyze workers' compensation claims can produce numerical scores that show which people are most likely to commit fraudulent activities. Each score can be accompanied by reasons for the score, which help users understand why the model determined the score, and help them determine what action to take, such as routing high-scoring claims to appropriate specialists for case management or fraud investigation.

Predictive analytics often utilize neural network models that can look at thousands of claims variables simultaneously, recognizing complex patterns and their comparable risk. New information from these comparisons is then used to refine the historical profile, a vast database of past claims, which is used to train the models. The more historical claims data that the predictive models can mine, the more accurate they can become in scoring claims to identify high-risk, fraudulent and abusive claimants.

Predictive analytics help businesses with a range of problems, from airline security to infectious disease control. They have become the standard for combating fraud in the credit card, health care and telecom industries. And now, predictive analytics are playing an increasingly important role in today's stepped-up efforts to fight workers' comp fraud.

November 1, 2005

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