LexisNexis® Optimal Decisions Toolkit Reduce combined ratios by up to 6% without giving up growth.
The LexisNexis® Optimal Decisions Toolkit integrates useful component functionality into a complete price optimization solution. The Rater, Modeler, Simulator, and Optimizer help insurers answer the question: What is the best combination of pricing and marketing actions for my book of business in the evolving competitive environment?
- Better understand losses and profitability by segment – Without a detailed understanding of losses, price competition in some segments can become a competition to lose money.
- Restrict discounting to customers where it matters the most – Not everyone reacts the same way to pricing differences between insurers.
- Work with experts – LexisNexis pricing optimisation consultants have advised 9 of the top 15 US property & casualty insurers and leading insurers in the UK Australia and India.
- Pricing Designer – Designed specifically for the current market conditions, this component allows insurers to combine a quantitative loss analysis with qualitative market insights to make a united pricing decision across underwriting, actuarial, marketing and sales functions.
- Rapid Modeller – Use segment-level inputs direct from existing management reports to create simulations and optimisations, significantly reducing the data required to begin analysing elasticity-based pricing optimisation.
- Modeller – Diagnose your data, examine explanatory factors, and train generalised linear models (GLMs) or non-linear elasticity models to predict losses, conversion and retention.
- Simulator – Explore the ramifications different pricing scenarios on the multi-year value of your portfolio by combining elasticity models with claims loss, expense and marketing information. Compare scenarios side-by-side to consider a variety of options.
- Optimiser – Specify a business objective and constraints, and then the advanced algorithms automatically find the optimal changes to your current pricing.
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Did You Know?
Pricing optimization can reduce combined ratios by 2-6% without giving up growth.
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