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Simon White

Principal Consultant – Data & Predictive Analytics, Liverpool

Simon is able to assist clients in any sector and any jurisdiction to devise, build and deploy data-driven solutions.
Simon White


Simon has an extensive background in the insurance industry and initially began to deploy data and predictive modelling techniques within that sector to both profile opponent behaviours and to devise analytics-driven toolkits to improve human decision-making leading to better, quicker decisions on insurance claims and measurable cost savings. Whilst still practising within insurance, he has also widened his scope to work with clients in other sectors, leveraging data analytics to provide an end-to-end service to optimise client performance – from initial diagnosis of sub-optimal performance areas, through deep-dive insight and root cause analysis to working with our lawyers to devise, deploy and measure the effectiveness of improvement strategies.

Simon is now involved at any or all stages of the development of data-driven solutions for clients – from meeting with clients to understand their specific challenges and requirements, to conceptualising, scoping, designing solutions, managing data requirements and analysis, as well as building, deploying and measuring results.

His skills act as a highly effective bridge between clients' own data teams and technical subject matter experts to provide recommendations and solutions that key stakeholders intuitively understand. He works closely with DWF client partners to understand their clients' businesses and data so that the end analytical product carries real transformational meaning for clients.

Recent Cases

Recent examples of Simon's work:

  • Produced a detailed claimant solicitor behavioural data profiler within the insurance sector to identify existing, changing and new risks in the market and enable insurer clients to tackle those risks effectively and reduce claims spend.
  • Predictive modelling within the prison population to identify prisoners at high risk of self-harm to enable the prison service to reduce incidents of prisoner self-harm.
  • Designed, built and deployed algorithms for application to insurers' new personal injury claims to predict likely claims behaviours and route the right claims to the right claims handlers – allowing the quick settlement of low risk claims and effective tackling of high risk claims, reducing claims spend.
  • Devised, scoped and designed a data-driven solution to tackle the issue of contract divergence for a construction company.
  • Scoped and designed a data-driven solution to evaluate the performance of a technology client's in-house legal team in order to improve that performance and identify risks.
  • Advised a Local Authority on data-driven solutions to improve their cash collection. 
  • Designed and produced data models and forecasts including 'what-if' scenarios for a range of scenarios, especially with regards to civil litigation and the effects of legislative reform.