Predictive Analytics for
Insurance
Maximise your customers’ value and minimize claims risks/costs by integrating real-time analysis into existing systems and processes.
In today’s volatile market, insurance claim losses and unprofitable customer relationships can quickly overwhelm an insurance provider. To transform these potentially costly challenges into opportunities, many insurance companies are harnessing advanced analytics to improve their daily operations.
Eight out of 10 telecommunication services companies on the S&P 500 use software from SPSS.
Predictive Analytics for Insurance
In today’s volatile market, insurance claim losses and unprofitable customer relationships can quickly overwhelm an insurance provider. To transform these potentially costly challenges into opportunities, many insurance companies harness advanced analytics to improve their daily operations.
Predictive analytics for insurance can help you maximise your customers’ value and minimise claims risks/costs by integrating timely analysis into existing systems and processes. Predictive analytics solutions can assist with marketing and customer experience challenges and fraud detection and prevention solutions.
Primary Analytics Solutions for Insurance
Design the analytical solution that is best for your business.
Marketing & Customer Experience
The Insurance Industry is one of the most competitive ones with high customer cost acquisitions and significant customer turnover. Advanced Analytics can deliver the following key capabilities relating to Customer experience and Marketing:
- Reduce Acquisition costs by understanding who your most valuable customers are and how to best reach them
- Best serve your customers with the products they need using their preferred channels
- Improve cross and upselling through effective segmentation to target those with the greatest propensity to take up an offer.
Fraud Detection & Prevention Solutions
Predictive Analytics Solutions for fraud detection and prevention helps you:
- Accurately determine which claims should be settled quickly – and which require additional investigation – even in firms with very high claims volumes.
- Detect fraud consistently throughout the life of a claim, to predict and prevent fraud at each stage.
- Automatically detect new forms of fraud with analytics that “learn” from your data.
- Support the overriding claims adjusting goal of moving claims to closure quickly, keeping costs down while providing a high level of service.
Fraud Visualisation & Analysis
The fraud visualisation and analysis solution is designed to provide critical insights to aid in investigating complex incidents, producing actionable visualisation of critical people and events and documenting results for potential litigation. Benefits include:
- Analyse and visualise complex cross-channel attacks across multiple sources of data and systems.
- Uncover hidden patterns and relationships in data by performing advanced analytics.
- Identify and disrupt fraud errors and abuse.
- Implement fast, typically within weeks.
- Reduce the time, costs and complexity associated with fraud detection and investigation.
Insurance Case Studies
Case Study – Lansforsakringar
Länförsäkringar wanted a more systematic way to analyze its wealth of customer data and to generate insights that would help optimize marketing campaigns and other customer interactions. Länsförsäkringar implemented IBM SPSS predictive analytics software to analyze large quantities of data from various data sources and effectively identify different patterns of customer behavior
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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