Applying Predictive Analytics to Improve Risk Management, Part Three

Posted by Paradigm on August 7, 2012 under General | Be the First to Comment

In this third part of our series, we explore how applying predictive analytics to the claims process can improve risk management and care for the injured person.  Since claims are the biggest single outlay for an insurer, and roughly 20 percent of claims drive 80 percent of losses and expenditures, identifying and properly managing those with the highest potential for loss can significantly benefit a company’s financial performance.

Identify Complex and Costly Claims

Predictive analytics combines data gleaned from various internal and third-party sources to find commonalities that indicate the likelihood that a claim will be elevated in severity, duration or cost.  Proactively managing these commonalities will improve risk management efforts, and result in lower costs for the insurer as well as improved quality of care and service to the patient.

Predictive analytics is being used successfully in the areas of underwriting and pricing, and has just recently become a claims management practice.  According to a report issued by Deloitte & Touche, LLP, companies using predictive analytics to improve risk management in the claims process:

• Reduce annual loss and expenditure 4 percent to 8 percent.
• Improve nurse-managed claims by 3 percent to 7 percent.
• Improve outcomes by 5 percent to 10 percent in claims managed by fraud investigators.

By applying statistical algorithms and data mining techniques to the empirical data compiled from each claim, analysts may effectively forecast the likely outcome of a claim as soon as it is filed.  Similarities to other complex claims signal insurers to focus appropriate resources on the most difficult cases for improved medical and financial outcomes.  The type of response may vary from enhanced medical management, to litigation management, to fraud protection.

Preparing for Future Claims

By examining a large collection of past claims, predictive analytics ultimately offers a guide to managing future cases.  This global review of valuable data would not be obvious or even possible for claims managers working with individual variables.  The findings can then be weighed and acted upon based on the objectives of the insurer and employer to improve risk management through advance preparation.

The effectiveness of predictive analytical tools will improve as managers become more effective at recognizing and using the data.  The result is a reliable statistical method for identifying complex cases, more efficient claims management, better allocation of resources, and a more customer-centered recovery process for the injured person.

Complex Claims and Paradigm

Since catastrophic cases are often very distinct in their severity and likely risks, anticipating complications and resource needs can be far more difficult than routine claims.  Paradigm helps clients meet this challenge by relying heavily on analytic models.  Our predictive engine, called Paradigm Analytics, is unmatched in the industry.  Used in combination with the clinical expertise of our injury management teams, this model draws from a proprietary data set with nearly 20 years of catastrophic and complex case data.

For more information on how we can assist you with identifying high risk claims, contact us via our website www.paradigmcorp.com or call 888-621-6602. We also invite you to join our social communities on LinkedIn, Twitter, Facebook and YouTube.