Here’s an insurance claim: The bedrock of any great insurance company is a phenomenal ability to assess risk.
Skilled risk assessment relies on a company’s predictive abilities.
This is because A.I. is inhumanly talented at making predictions. To find out more about A.I.’s prediction power is changing the world of insurance, read on below.
A.I. and Prediction
Here is a quick and easy A.I. lesson: At the end of the day, the task that the vast majority of A.I. systems do is make predictions.
The process that these A.I. platforms go through involves receiving input data, analyzing that input data, and offering a prediction (sometimes in the guise of a “Hey, do this” solution), often called the “output data”.
In other words, this is just a machine version of the information processing and analysis that us humans do pretty much all day, every day. In this world, we experience events as input data, and we mostly make predictions about how the world works, why something happened, etc., based on our interpretations and conclusions regarding this sensory input.
What makes A.I. such a fast-growing field is that A.I.’s prediction power far outstrips any human underwriter’s prediction powers, no matter how much “Underwriter of the Month/Year/Decade/Century/History of the World” hardware that underwriter has on the office shelves.
A.I. and Insurance
In the context of insurance, you want to be able to harness the power of any tool that can assess whether a potential insured customer is a risk or not, and if so, how much of a risk so that you can offer the right price for your insurance plan.
For this reason, any insurance company should want to take advantage of artificial intelligence for the sake of getting better, more accurate risk assessments of potential and existing clients.
The input data for an A.I. risk assessment platform would be data about the applicant. A well-trained A.I. platform will have gone through the process of analyzing this kind of data countless times, so it will be familiar with what data is the most significant (e.g., car crashes where the applicant was at fault) in assessing risk.
All that training enables the generation of quick and accurate assessments regarding how much an insurance company should charge the applicant or whether the applicant should face rejection.
And, with machine learning capabilities, A.I. platforms are able to continually improve their prediction abilities by learning from each task performed.
Other Applications for A.I. In the World of Insurance
Using A.I. in insurance extends far beyond risk assessment prediction.
For one, you can set up a chatbot on your website so that you can always have the option for site visitors to ask questions about your company and receive answers at any time of the day.
A chatbot is basically a 24/7 customer service representative that can have multiple conversations at once, fielding the easy questions so that your team is freed up to answer the more complex, I-need-a-human-being questions that customers may have for your company.
Something else that you can do with A.I. is customer churn prediction. An A.I. platform will analyze your company’s historical data and broader market data to provide strong predictions about which customers you are at the highest risk of losing.
Yet another use for A.I. for insurance companies is price prediction tools, where you can find the best price points to offer your clients based on A.I.’s analysis of the insurance industry as a whole. With A.I., you will be able to find the best premiums to offer your clients.
A free A.I. platform that you can try out is ChatGPT, which you can use to quickly generate blogs, social copy, internal memos, etc. for your customer outreach and internal communications.
However, please be aware that you should always proofread and fact-check the output of the A.I.
Why You Still Want Human Underwriters On Your Team
Just as marketing companies are starting to realize that chatbots like ChatGPT are not suitable replacements for human copywriters, but are more like writing assistants, so the same holds in the world of insurance.
A.I. is best used when it is treated like an assisting tool to existing employees instead of an independent employee.
For this reason, you will want human underwriters to sort through the recommendations and rejections for applicants. A.I. here functions as a second set of eyes for screening applicants, but the human underwriters should ultimately be the decision-maker, not A.I., which has been seen to sometimes inadvertently discriminate against minority groups.
For this reason, you want to survey A.I.’s work so that you can make sure you are making the right decisions when it comes to who does and does not get approved for a policy.
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