• Direct players and price comparison websites lead to higher price transparency
• Entry of new players -specialized insurtechs, non-traditional players- increase competition
• New customer behaviors of digital-natives require speed and individualization of pricing
• Low interest rates increase of pressure on insurance products’ profitability
• Cloud processing power and new external data sources push adoption of advanced analytics
• Regulators demand more transparency and explicability of pricing models and variables
In this context actuarial organisations are under pressure to accelerate pricing time to market, secure models performance and consistency and embed additional source of data to improve accuracy through new variables - but always keeping transparency and interpretability of the models.
AKUR8 PRICING SOLUTION
The Akur8 AI pricing solution embeds all steps of the pricing process in one integrated and collaborative solution - from data set preparation to commercial pricing optimisation and execution - leveraging the Akur8 Engine™.
Akur8’s technological edge allows insurance carriers to improve their profits with models created and updated in hours instead of months. The disruptive technology developed by our R&D team allows to combine machine learning and actuarial worlds. Akur8 developed cutting edge algorithms - the Akur8 Engine™ - to revolutionize insurance pricing.
GLM (Generalized Linear Models, also known as Additive Models) is a well-established technique that answers all risk modelling constraints: it is easy to understand and enables a clear validation process. But the creation of GLMs is manual. Iterations and discoveries are long and slow, involving a large number of actuarial resources. Using cutting edge machine learning, Akur8 has automated GLM modelling. From variable selection to geographic smoothing, you decide the tradeoff between clarity and performance. You can immediately spot anomalies and discover new patterns. With Akur8, you can improve your models Gini and your new business Loss-Ratio.
GLM vs MACHINE LEARNING