Claims Management
Use predictive analytics to help you minimize costs while improving your claim-handling process
Claims management costs comprise a significant amount of some insurance companies’ operational expenses, encompassing up to as much as 20%. Considering that the claims process directly affects customer satisfaction, claims management is one of the most critical functions of your business. Reducing claims management costs, even by a small amount, can have a significant, positive impact on your company’s performance.
Using a combination of rules, modelling, text mining, database searches and exception reporting to identify fraud sooner and more effectively at each stage of the claims cycle.
Primary Claims Management Solutions
Version 1’s SPSS experts can consult and deliver a wide variety of Claims Management solutions. Read more within the sections below.
Claim Fraud
Claim fraud is increasing and the focus on claim fraud is increasing as well. 1 out of 10 insurance claims is fraudulent. How do you spot those before a hefty payout is made? Most fraud solutions on the market today are rules-based.
Unfortunately, it is too easy for fraudsters to manipulate and get around the rules. Predictive Analytics, on the other hand, uses a combination of rules, modelling, text mining, database searches and exception reporting to identify fraud sooner and more effectively at each stage of the claims cycle.
Claims Processes
Combine risk profiles with business rules to resolve legitimate claims in as little as one phone call.
Streamline claims processes and decision-making, and implement continuous process improvement.
Suspicious Activity
Make better use of skilled investigators by enabling your staff to focus only on complex claims or high-value suspicious claims.
Minimise claim payments and reduce fraud with real-time alerts of suspicious activity.
Customer Service
Improve customer service and keep costs down by streamlining the claim handling process; for example, industry studies show that fast-tracking legitimate claims reduces customer frustration and minimises the likelihood that policyholders will take negative action.
Decrease the amount of time it takes to process a claim by several days on average by improving claims routing, providing adjusters with suggested tasks and real-time assessment of adjuster statistics.
Claim Scoring
Build and use methods for scoring claims particular to state differences, lines of business, or times of catastrophe.
Improve subrogation results by focusing on the claims more likely to pay you back.
Claims Management Case Studies
Case Study – Insurance Bureau of Canada
The insurance industry is constrained by the manual and ad hoc approach to detecting and investigating potential fraud. To address its objective of automating the detection of potential claim fraud and the identification of possible fraud rings, IBC engaged IBM to perform a Proof-of-Concept project using IBM® InfoSphere® Identity Insight and IBM SPSS® Modeler. The benefit IBM POC quickly found suspects and their claims reducing investigation efforts; found a previously unidentified suspect fraud ring; and gathered more information against suspected fraudsters with a higher degree of confidence.
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Case Study – Insurance Bureau of Canada
The insurance industry is constrained by the manual and ad hoc approach to detecting and investigating potential fraud. To address its objective of automating the detection of potential claim fraud and the identification of possible fraud rings, IBC engaged IBM to perform a Proof-of-Concept project using IBM® InfoSphere® Identity Insight and IBM SPSS® Modeler. The benefit IBM POC quickly found suspects and their claims reducing investigation efforts; found a previously unidentified suspect fraud ring; and gathered more information against suspected fraudsters with a higher degree of confidence.
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Version 1’s SPSS experts can consult and deliver a wide variety of analytics solutions across a broad range of industry sectors. Find out more at the links below.
