AI Leap Insurance


Why Using Artificial Intelligence in Reinsurance Process?

Reinsurance became popular in the end of 90’s when some insurance companies carried huge losses due to a series of events and litigations and some even went bankrupt. The goal of reinsurance is to reduce the risks of the prime insurer in a variety of policies: fire, flood, earthquake, casualty, etc. Lately reinsurance became a lucrative business with many major banks and hedge funds involved in some form. In the latest edition of the Aon Benfield Aggregate (ABA) report, which analyses the financial results of the world’s leading reinsurers in 2012, Aon Benfield Analytics estimates that global reinsurer capital totaled a record $555 billion at December 31, 2012, an increase of 11 percent, compared to $500 billion on December 31, 2011. “This calculation is a broad measure of capital available for insurers to trade risk with and includes both traditional and non-traditional forms of reinsurance capital,” said the announcement.
 

Current Reinsurance Concepts and Process

Usually a party in need of full insurance coverage contracts the prime insurer (sometimes it’s an inbound insurer, i.e. a legal entity formed within the company) to solicit quotes from 3rd parties for 3 tiers of each of required insurance coverage: casualty, fire, earthquake, flood, etc. First tier covers first $5-10M, second tier goes up to hundreds and third tier stretches into millions or even billions of losses insured. Sometimes the inbound insurer covers parts of first tier itself.

Quotes are collected either by phone or email and entered into a spreadsheet. Then, the task of the coordinator of the reinsurance process is to perform follow-up negotiations and to select the best combination of reinsurance coverage for all types of insurance, for all tiers. This is a very complex, lengthy, tedious task for a person making 7-digit decisions often under the pressure of deadlines. After several rounds of negotiations the selections are made and the contracts are send out to be signed. The decision maker in most cases has a very limited visibility of what is covered and what is not, and how much the decision maker could spend.

What often happens next year is that an event occurs which triggers the policy coverage investigation and the prime insurer finds out that there is a gap (lapse) in a second or third tier and the prime insurer is liable for covering that gap, which is prohibitively costly.

AI Leap Reinsurance Solutions

AI Leap offers the solution that assists the decision maker in resolving the complex process of reinsurance and achieving the two main goals, which are the completion of the coverage and the optimized pricing. The AI Leap Reinsurance application also guides the decision maker in the negotiation process by suggesting preferred rates for the existing gaps or better quotes based on the existing quotes and historic data.
 
Some insurance companies have access to regional repository of existing policy rates and potential quotes from competitors for auto, motorcycle, boat, house, etc. insurance. AI Leap may assist insurance companies in deriving premium pricing and selecting current policyholders that would benefit from switching to their insurances, especially in multi-policy cases.