Artificial Intelligence Based Automated Actuarial Loss Reserving Model for the General Insurance Sector

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Abstract We developed an Automated Actuarial Loss Reserving Model using Artificial Intelligence based machine learning methods since the traditional actuarial reserving techniques are no longer compatible with the increase in technological advancement currently at hand .We have also conscripted the introduction of bancassurance services to general insurance companies which involves automation of microfinance services into the car insurance process. The introduction of the base rates, variable rates and final rates on this model to policyholders significantly reduces lapse rates and brings together a combination of new and existing policyholders in the insurance company. We have extended the frequency severity models using eight machine learning algorithms and derived the Automated Actuarial Loss Reserving Model adjusted to inflation which remarkably performed well with Random Forests models being the best model among the machine learning models used in the study.

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