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 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.

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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.

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White Paper

Learn how Predictive Analytics can help you lower costs, increase profitability, improve efficiency, acquire and retain the most profitable customers and reduce fraud.

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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.

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Case Study

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%

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White Paper

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.

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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.

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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

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White Paper

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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Related Resources

Download your info-pack for Insurance!

Gain access to the latest Predictive Analytics Case studies, White Papers and Reports in your industry!

  • "Our people at the front-lines taking claims are now making decisions that adjusters in the field would have made in the past. To make it work, we needed to balance that extra empowerment with a greater degree of accountability—and employees who were comfortable with that new balance."

    Bill Dibble
    Infinity Property & Casualty
  • "With predictive analytics, we were basically able to close a hole in our pocket where money was leaking out steadily. We were also ready to show that this was just the beginning."

    Bill Dibble
    Infinity Property & Casualty
  • "The efficiency of the analyst team has been enhanced significantly since the new solution was implemented – analysis work which used to take a week can now be done in a day and a half. We have also seen a qualitative improvement, with analytical results that are up to four times more reliable and accurate."

    Ola Gustafsson
  • "IBM SPSS predictive analytics software has given us the means to learn systematically from our experience. By learning from the history, we can know today who will buy a given product in the future."

    Ola Gustafsson

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