Insurance Claims Management With AI
Insurance companies are in the business of risk assessment and they evaluate the number of claims that’re likely to occur and how it’s going to affect the insurance pool (Total value of premium collected). Insurance companies have fail safe which means they take insurance on their own uncertainty such as a natural calamity that would create a bigger demand for claims.
More people they bring into the insurance pool, the entire stack can stay healthy to pay for claims, management cost, operational cost and profits of the company. Economy can also have a impact when there is a end of business cycle causing a recession or stagflation causing increase the number of claims coming through.
Modeling AI
When predicting number of claims that’re likely to happen over the next year or insurance cycle, there are number of factors to consider:
Customer Attributes → it can be predicted from previous data by finding the parameter similarity in the claims data.
Economic climate → it’s harder to predict since there are few variables that can define how an economy functions like GDP, Interest Rates, Per capita income Growth, Jobs growth, Economic freedom.
Weather Condition → With the advent of IOT devices. Weather data is available to model likely weather condition over a period of time and the number of claims due to its change.
Policy Parameter — This represents the how the claims are structured for during the initial creation of the policy. How the damages are classified & percentage of amount allocated to the claims.
Operational & Management Cost → Premium collected has to validate for operational, regulations and management cost which are rapidly changing year over year which needs to be accounted for.
PWC report shows the Insurance companies are concerned about the changing technology, competition, customer expectation and regulatory changes.
The rise of insurtech companies can affect the premium collected since more competition means sufficing customers would be a battle of customer services, quality of product and cost. Some of the Insurance companies have resorted to incubating the Insurtech companies so that they can have the competitive advantages.
Deep learning models can evaluate these feature parameters to find patterns and correlations between different events that can lead to claims. Point here is not mitigation of claims but anticipating/predicting how the next policy cycle is going to impact the business in a more accurate way.
Insurance companies adapting AI would have better advantage in managing the overall health of the insurance. As more players come into this sector, consumers are going to get better choice. Employers can form association to add more people into the insurance pool to drive the cost down.
In this Series
1 . How Insurance Can Enhance Customer Experience Using AI
2. Insurance Underwriting And Claims With AI
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