Warranty Fraud Detection & Prevention Venky Rao North American Predictive Analytics Segment Leader
Agenda IBM SPSS Predictive Analytics for Warranties: Case Studies Why address the Warranties process: Opportunities How to address the Warranties process: the IBM SPSS Predictive Analytics solution 2014 IBM Corporation 2014 IBM Corporation 2
IBM SPSS Predictive Analytics for Warranties CASE STUDIES 5/6/2014
BMW identified anomalies in production, improved overall quality and reduced warranty claims Quickly Identified root cause of quality issues 23% reduction in warranty claims per vehicle 30 million savings in 1 st year of deployment Generally speaking, it is a question of making various processes transparent. Where data is generated, success becomes measurable. The long-term goal is, of course, to improve the performance of BMW in all sectors and thus to achieve more success, according to Michael Unger, Key Account Manager of Predictive Analytics at IBM SPSS in Germany. Business challenge: Classic BI methods only allowed for simple analyses such as identifying selected vehicle component failure. Growing volumes of data made it difficult to manually filter out anomalies and identify trends. Standard tools did not allow use of all data. The solution: Created AVAQS (Advanced Quality System) which embedded complex analytics flow into other processes. Processes are accelerated quickly. Performed automated root cause analysis to quickly pin-point exact cause of production line quality issues. Identified specific combinations of vehicle options that led to excessive warranty claims. Identified operational issues that lead to premature part failures. 2014 IBM Corporation 4
IBM SPSS Fraud Solutions help mitigate fraud risk and deliver more positive customer experiences Business outcomes Loss avoidance through significantly improved fraud detection Operational effectiveness through a dramatic reduction in false positives and an efficient collaborative investigation process Improved customer engagement through fast tracking of legitimate customer transactions 90% reduction in process time for low-risk claims $2.5 million saved in six months All amounts are in US dollars. 2014 IBM Corporation 5
Infinity Property & Casualty Corporation optimized claims processing while reducing loss adjustment expense and fraud 403% return on investment 95% reduction in referral of questionable claims $1 million increase to the company s bottom line I was looking for a product for the enterprise, one that we could use for a variety of predictive analytics. Primarily, I was interested in speeding the settlement of claims that did not contain elements of fraud. [IBM SPSS ] was the clear winner in meeting all of our requirements. Bill Dibble, SVP claims operations, Infinity Property & Casualty Corporation Business challenge: Infinity wanted to submit fraudulent claims to its investigative unit faster, speeding the payment of legitimate claims and lowering its high monthly costs for subrogation, the process of collecting damages from the at-fault insurance company. The solution: Through automated data analysis and predictive modeling, the insurance company can more effectively spot suspicious claims early. The solution allows it to expedite payments of legitimate claims, thereby improving customer satisfaction and loyalty while reducing third-party collection fees. All amounts are in US dollars. 2014 IBM Corporation 6
A nonstandard insurance company in the United States flags five times more claims for fraud investigation 10% increase in the number of claims subject to special investigation Expedited processing of legitimate claims Expanded into new market segments by better assessing regional risk The solution s intelligence allowed the insurer to redesign the claims-handling process. Now the company can not only identify claims that most likely require investigation but can also give legitimate claims the express treatment. Business challenge: Adjusters at a nonstandard insurance company in the United States reviewed hundreds of claims for suspected fraud yet flagged only 2 percent for further investigation. The culprit was a manual review process that not only was tedious and time-consuming but also failed to identify hidden, more sophisticated instances of fraud. Given the alarming statistics, the company knew there was a much higher potential of loss it wasn t capturing. The solution: This insurer is winning the battle with a solution that applies predictive analytics and a complex suite of business rules against customer and claims data to flag claims suspected of fraud. As adjusters collect and enter claimant information, the solution automatically begins rating the claim, applying scores from 1 to 500 based on business rules. 2014 IBM Corporation 7
Why address the Warranties process? OPPORTUNITIES
The exposure to fraud exists across the entire warranty value chain from sales to underwriting to claims Which parties are valued customers / agents, or are skilled fraudsters? Which claims are valid? Which bills are for legitimate services rendered? Which warranties should never have been issued in the first place? The ultimate differentiator today......having the insight to make more informed decisions with confidence, to anticipate and shape business outcomes 2014 IBM Corporation 9
Proactively addressing fraud can translate into opportunity Operational effectiveness IBM client IBC reduced the time to detect a $1 million fraud ring by more than 99 percent from years to days 1 Loss avoidance Reduce false positives Focus investigations on high-risk cases to improve efficiency Improved customer engagement IBM client Santam delivered a 70 times faster settlement of legitimate claims 2 Deliver an optimal experience to legitimate customers Protect customer data Deter suspicious transactions with confidence Brand value Reputation declines an average of $332 million as a result of an IT breach of customer data 1 Protect your brand reputation Engender trusted client relationships Support regulatory compliance obligations 1 Ponemon Institute, Reputation Impact of a Data Breach: U.S. Study of Executives & Managers, November 2011. All amounts are in US dollars. 2014 IBM Corporation 10
How to address the Warranties process? THE IBM SPSS PREDICTIVE ANALYTICS SOLUTION
Predictive Analytics Process Detect & Capture Analyze & Predict Engage & Act Transactions Demographics Interactions Opinions Predictive Modeling Data Mining Text Analytics Social Network Analysis Statistical Analysis Prediction Rules Optimization Process SMA Statistics Modeler Decision Management Data Collection Catalyst Collaboration and Deployment Services 2012 IBM Corporation
The IBM SPSS Solution offers distinctive and robust capabilities Operational systems Advanced Analytics Data models Predictive models Rules Reports Process External fraud data and more Real time In time Back-office analytics Detect Respond Discover Investigate Report Predictive analytics Observations Rules Decision management Operational system integration Action Guidance Rules Selection Evaluation Anomalies Identification Context analytics Relationship visualization Forensic analysis Dashboards Operational reporting Case briefing Feedback Observation space Information domains Internal sources External sources Evolving unstructured sources Fraud use case libraries 2014 IBM Corporation 13
Gartner s Inaugural Magic Quadrant for Advanced Analytics Platforms 2014 2014 IBM Corporation 14
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