AI-Driven Super Powers Recreating Underwriting

By Insurance CIO Outlook | Friday, August 23, 2019

With the advent of artificial intelligence, the insurance industry is witnessing many digital revolutions, and the foremost thing that has totally transformed into an advanced form is insurance underwriting.

FREMONT, CA: Artificial Intelligence (AI) might make us recall movies which featured machines behaving like humans and humanoid robots walking around with jackets and guns- could be a paranormal thought though! But, in real-world, AI has far more practical application than these mystic thoughts, especially in insurance underwriting. AI has the brilliance to game plan insurance firms where health underwriters are quickly analyzing massive health data, commercial underwriters incorporating data from various external agencies, and so on. AI is now able to predict losses better, provide advice, and help prevent risks, ultimately offering more significant benefits than ever before. No doubt that AI will fundamentally disrupt and transform insurance underwriting. Insurance firms are heavily investing in this technology, expecting that this could increase profitability, which means that the AI revolution is advancing and the insurance underwriting is never going to remain the same. Here is more to it!

• Risk Assessment

The underwriting process involves analyzing and evaluating the potential risks involved. Previously underwriters had to depend on the information submitted by the applicant for risk assessment. In this process, there is no assurance that the information provided by the applicant is accurate. In cases where false information is given, or applicant purposefully misses vital information in the application, the value of an underwriter is invalidated as using wrong information. This is a real challenge. With the integration of AI-powered Natural Language Processing (NLP)underwriters can have access to more sources of information for getting more insights about clients and thus an adequate risk assessment. The sources of information offered can even be from social media platforms. NLP has improved the efficiency of the risk assessment process by providing relevant information through its data sources. Being able to consume more data can bring customization, and customers will benefit by paying for coverage they genuinely require.

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• Fraud Detection

The insurance industry is continuously poisoned with fraudulent claims, and AI is a perfect solution for this. Machine learning algorithms can detect interrelations and patterns which may go unperceived in the evaluation processes carried out by human underwriters. Besides identifying fraudulent claims, the algorithms can offer an assessment of the repair cost, the liability of the claims and control measures to combat further fraudulent claims filing. Insurers believe that AI is set to transform the insurance industry, and many have already begun fraud prevention operations powered by AI. The accuracy rate of capturing fraudulent claims with the help of AI is more than 75%. With all these insurance, underwritings are not solely depending on the applicant anymore.

• Customer Value

Real-time analysis and visualization are changing the relationship between insurers and insured. Insurers are leveraging AI and data analytics to optimize their operations and influence customer behavior. The availability of data with the help of AI is leading underwriters into a new reality, where streams of data are continuously collected and fed to AI algorithms and machine learning tools which convert them into immediate, actionable insights. The outcome of this process is a multi-dimensional, interactive view of claims that will change the way underwriting is carried out.

• Enhanced Efficiency

With information streaming in from both traditional and non-traditional sources, underwriters are presented with lengthy, more dynamic, complete picture of applicants. Tools that can access and analyze this information can only enable development. Human-based systems are always prone to errors, and on the other side, a digitized system performs more accurately and efficiently. AI contributing to the machine potential. The machine learning algorithm is assessing for errors in the information presented in a shorter time than it would take for a human underwriter to do. Besides checking for disparities promptly, machine learning algorithms will also eliminate the need for third-party operations between the insurer and the insured. This effectively enhances efficiency and the relation between provider and client for better products and services. Fundamentally, an error-free system means accurate information, proper evaluation, and more efficient customer service.

The insurance space is changing so rapidly as underwriters started increasingly interacting with AI. With this, there emerged a significant need for new skills to develop, including open-mindedness and mental agility, and old tactics are becoming outdated. AI adoption must be done constructively. The entire insurance industry needs to get trained about AI for them to be part o defining their future. Rather than leaving it to the hands of technology vendors or losing out to competitors cannot be afforded. Equipping underwriters with AI tools to access and analyze massive information will facilitate the development of accelerated solutions where underwriting can be done dynamically, based on customers' behaviors over time, through a more frictionless, consumer-friendly process. Every insurance companies these days is using its own AI tools and is improving the underwriting process.

The insurance industry is in a race to cope with all the possibilities of digitalization, especially artificial intelligence. As it is one of the critical components of digital age insurers are employing prospects, it holds for the industry. It has become crystal clear—with the integration of technologies, including artificial intelligence, advanced data analytics, machine learning— that the age of digital insurance is approaching at a rapid pace.

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