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.
Presidion can help you maximise your customers value and minimize claims risks/costs by integrating real-time analysis into existing systems and processes.
Our Solutions
Marketing and Customer Experience
The Insurance Industry is one of the most competitive ones with high customer costs 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.
Case Study
Swedish insurance company shifts from two nationwide direct marketing campaigns a year to 13 a day thanks to IBM SPSS predictive analytics software
- Enhanced efficiency of the analyst team
- Qualitative improvement of the campaign selection process, with results that are up to four times more reliable.
- Moved from two nation wide direct marketing campaigns per year to 13 unique, customer-specific campaigns a day which are used for face-to-face meetings with customers.
White Paper
Maximize customer value and reduce costs and risk
Learn how Predictive Analytics can help you lower costs, increase profitability, improve efficiency, acquire and retain the most profitable customers and reduce fraud.
Fraud Detection and 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.
Case Study
Infinity Property & Casualty Corporation (IPACC)
IPACC deployed SPSS to reduce its payments on fraudulent claims and improve its ability to collect payments from other insurance companies.
- 400% ROI with six months of implementation
- Increase of $12 million in subrogation recoveries
- Increase in success rate in pursuing fraudulent claims from 50% to 88%
White Paper
Using data mining to detect insurance fraud
Learn how Predictive Analytics solutions for insurance fraud detection can compare historical and current data, discover relationships and patterns, and analyze predicted and actual discrepancies.
Fraud Visualisation and 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 error and abuse.
- Implement fast, typically within weeks.
- Reduce the time, costs and complexity associated with fraud detection and investigation.
Case Study
Outsmarting fraudsters with fraud analytics – IBC protects honest policyholders by detecting and prosecuting organized insurance fraud.
- Quickly found suspects and their claims reducing investigation efforts
- Found a previously unidentified suspect fraud ring
- Gathered more information against suspected fraudsters with a higher degree of confidence
White Paper
Fraud Intelligence Analysis Solution
Identifying, investigating and disrupting fraud in insurance:
- Rapidly investigate and document financial crimes to deter fraudsters
- Analyze and visualize complex, cross-channel fraud to improve controls
- Cumulatively build and leverage a fraud intelligence repository to identify emerging and repeat attacks
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