Analytics trends 2014
In 2014, eight business analytics trends will rule the day - or will they.
When an insurance company wanted more discipline in underwriting
Deloitte Analytics used predictive models to maximize the value of their data
For insurance companies, few innovations are more important than predictive modeling, especially when it comes to underwriting and pricing.
When a major U.S. insurance carrier wanted to improve its underwriting and pricing discipline, it looked for a professional services provider that could not only develop algorithmic and predictive modeling capabilities but also deliver, integrate, and deploy an end-to-end business solution across a range of product lines.
How analytics helped
The member firm team first worked to develop and implement predictive modeling solutions to improve the underwriting and pricing discipline as it entered a soft underwriting and pricing market cycle. They helped to create and deploy solutions for its Errors and Omissions and its Workers’ Compensation lines of business. Predictive models were deployed, which are actuarial and statistically derived multivariate formulas that relate predictive underwriting variables to predicted future policy profitability.
Building on the success of the initial project, a second phase was initiated to develop predictive underwriting models and scoring engines for the member firm client’s Business Owner’s Policy, Commercial Automobile and Commercial Package (General Liability and Commercial Property) lines. The scoring engine that was developed was a combination of IT infrastructure and software that generates the predicted profitability score and lets the company monitor the effectiveness of business strategies derived from the models.
Once the predictive modeling solution was fully integrated into the insurer’s technical and business infrastructure, the member firm team assisted in the business implementation of the models and the development and delivery of training content for regional underwriting offices.
Today, it is possible to effectively assess policies for risk quality, price adequacy, customer retention, agency management, and underwriting decision compliance. They can also flag policies for follow-up attention in areas such as claims handling, agent training, and customer service.
The insurance carrier is able to measure the benefits of its predictive models and implemented methods, learning from past data and responding proactively to future needs.
Learn how analytics can help to optimize operational efficiency which in turn can improve performance and drive shareholder value.
Learn how risk managers have applied analytics to better understand their risk exposure and to more effectively manage risk on an enterprise scale.
Learn how organisations have applied analytics to better understand the present, and more accurately predict the future.
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