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How AI is Enhancing Underwriting
Underwriting is made more efficient with the advent of AI's precise pricing and risk assessments.
FERMONT, CA: Underwriting allows a company to choose who and what will be covered by the insurance company based on risk assessment. An underwriter is a risk assessment specialist and makes policies based on the insurance agents' information. However, a lot of underwriting is becoming automated with an exponential increase in data in the last few years. Forcing firms to leverage technologies such as artificial intelligence (AI) for the purpose is the extraordinary complexity involved in underwriting. These are areas where Artificial Intelligence will influence the insurance industry.
Assessment of Potential Risks
Insurance underwriters evaluate and measure the agents' data to determine the potential risks involved. Every time, however, the data is not necessarily sufficient. An applicant, for example, may hide some vital information, leaving the analysis of the underwriter ineffective. By incorporating natural language understanding (NLU), which is a subset of machine learning (ML), insurance underwriters will have increased access to various information sources, thus revealing more about a potential customer.
See Also: Top Underwriting Solution Companies
For insurance companies, fraudulent claims are one of the biggest challenges. Many see it as a common practice that is hard to eradicate. In contrast, fraudulent activity greatly undermines the underwriting effort and efficacy. Nonetheless, through identifying patterns and correlations that are often associated with fraudulent practices, technologies such as AI and ML algorithms can tackle the problem more effectively. As a result, many insurance companies have already started integrating AI technology into their operations for fraud prevention.
Streamlining Error-Free Insurance Processes
While human underwriters are prone to mistakes, digitalizing the process will provide an effective alternative. In addition, the system's efficiency can be further enhanced if the system is combined with AI capabilities. For example, in contrast with human efforts, Machine Learning algorithms assess and detect errors in the data faster and with high precision. Not only will an error-free system streamline insurance processes, but it will also allow firms to offer better customer service.
AI technology will improve insurance underwriting efficiency and effectiveness. The software can help the underwriters understand their targeted customer base and develop economically viable policies.