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Data and Analytics

The proliferation of data available to insurers presents new and exciting opportunities across the value chain. Willis Towers Watson helps clients to exploit this data using advanced analytics algorithms and machine learning techniques, significantly benefiting risk selection and management, and operational effectiveness and efficiency.

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Life and P&C insurers are already beginning to use this wealth of data to improve decision making in marketing, pricing, underwriting, claims and retention activities. Their use of machine learning techniques facilitates data mining of both structured and unstructured data, allowing them to make better decisions for the benefit of the business and consumers alike.

Willis Towers Watson supports insurance companies meet their data mining and model implementation objectives. Our global analytics team includes data engineers, data scientists, software engineers and IT practitioners, all of whom have essential deep insurance expertise. And we have developed our own proprietary Advanced Analytics University, which is one of the tools we use to ensure our global consulting network maintains the cutting edge data mining, programming and analytics skills needed to provide best-in-class analytics support to our clients.

These analytics and IT skills are augmented by functional experts that understand how to use analytics to solve real business problems, allowing us to ask the right questions and propose solutions to their problems.

Our software suite includes automated machine learning tools, which incorporate proprietary algorithms designed specifically for the insurance sector, and model deployment technologies to facilitate rapid, accurate model implementation.

Our insurance analytics services include:

  • Analytics strategy development and best practice advice
  • Proof-of-concept design and support services
  • Natural language processing, including data preparation advice
  • Automated machine learning software and associated deployment support
  • Data enrichment services and strategy development
  • Model implementation and monitoring support

We have worked with a large number of insurers in the European Union and U.S. on a wide range of projects including:

  • Complete redesign of an insurer’s claims triage processes and operating model using (a) the right mix of functional claims practitioners and data mining experts to identify opportunities that could be exploited and lead subsequent analytics activity, (b) machine learning and data mining techniques to optimise predictive models, (c) data enrichment, and (d) natural language processing techniques to exploit unstructured text data.
  • Motor insurance pricing projects using a wide range of machine learning algorithms on traditional and enriched insurance data sets
  • Claims fraud process improvements using a mix of network analysis, unstructured text analytics and machine learning modelling to improve our client’s ability to predict fraudulent claims. The resultant models were then implemented into a redesigned fraud detection process.
  • Use of semi-structured clickstream and unstructured on-line data to improve cross-selling targeting activities for a multi-line insurance company.
Advanced analytics and the future: Insurers boldly explore new frontiers

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