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Apart from cyber threats, economic uncertainty, and climate change, one of the most challenging things for life insurers is to make the underwriting process highly efficient. The lengthiness, complexity and high chances of manual errors make life insurance underwriting a herculean task for life insurers. However, imagine you could save 40% of your time by simply incorporating AI in the underwriting process. The insurance industry is already employing AI at a rapid pace in its operations. A study found that 77% respondents in insurance industry have incorporated AI in at some stage in their value chain. It is safe to say that AI is going to have a major role in life insurance underwriting and other process of the value chain. Let's explore the role of AI in life insurance underwriting after an introduction to the basics. What is Life Insurance Underwriting? Life insurance underwriting is a comprehensive process that companies use to evaluate whether an applicant qualifies for coverage and helps them set the right amount of premium. This process involves two main approaches: Medical underwriting assesses an individual’s health and lifestyle, including factors like age, personal habits, occupation, usage of tobacco, and medical history to assess the risk to the insurer. Financial underwriting that ensures the coverage amount matches the applicant’s financial situation. Insurers review applicants’ income, debts, assets, credit history, as well as any existing insurance coverage. In a nutshell, the goal is to make sure the insurance amount is appropriate to maintain a balance between being over-insured and providing a helpful safety net. Factors Influencing the Life Insurance Underwriting Process It won’t be wrong to say that the purpose of life insurance underwriting is to estimate how long the applicant might live. If the applicant is healthy, they may get more insurance options and lower rates. However, if there are factors that increase the risk of an early death, they might face higher rates or even rejection. Here are the key factors insurers consider when making their decision. Medical Factors Applicant’s height and weight Family medical history Use of prescription or recreational drugs, including marijuana Smoking habits History of medical conditions like heart disease or diabetes Lifestyle Factors Applicant’s driving record Risky hobbies like scuba diving or flying Criminal history International traveling routine/history Financial Factors Applicant’s income and job Previous financial issues like bankruptcies Underwriting Classes: Why are They Important? Insurance companies generally use four risk categories: super preferred, preferred, standard, and substandard. Each category has specific criteria, but requirements can vary slightly by company. Super Preferred This is for people in excellent health conditions and who do not engage in risky activities or have dangerous jobs. They must be tobacco-free for five years and drug or alcohol-free for ten years. Also, they must have no history of serious illnesses or early family deaths from certain diseases. Preferred This category includes people who are generally healthy but might be on medication for conditions like high blood pressure or have a family history of health issues. Well-managed diabetes and some mental health conditions may also qualify. Standard Applicants falling into this category may have a higher BMI, take multiple medications, or have some health issues. Their driving record and job may not be perfect, and they need to be tobacco-free for just one year. Most of the applicants fall into this category. Substandard As the title suggests, this rating is for people with significant health problems or those with a short history of managing health issues. Examples include severe asthma or untreated serious conditions. Underwriting helps decide if the applicant gets a life insurance policy and how much it will cost. If the applicant is considered low-risk, they will most likely get approval and have lower premiums. If they are high-risk, they might face higher premiums, exclusions (where some conditions are not covered), or additional riders (extra features for more coverage). In simplified words, underwriting decides: Whether the policy is accepted, The cost the applicant will pay, and What is included or excluded in their coverage How is AI Revolutionizing Life Insurance Underwriting? A report from Accenture shows that insurance underwriters use 40% of their time on tasks that are not core elements of their work. This inefficiency could cost between $85 billion and $160 billion over the next five years. Meanwhile, AI technology has greatly improved over the past five years, which insurance underwriters can use to maximize the ROI. Here are the top reasons why AI is a game changer in life insurance underwriting. 1. Minimization of errors AI significantly reduces human errors in insurance underwriting as it accurately processes large amounts of data and learns from past mistakes. Instead of handling all tasks manually, underwriters can use AI to automate routine work and focus on analyzing outcomes and making informed decisions. This makes the underwriting process faster, more efficient, and more scalable. 2. Reduced chances of cyber threats Dealing with rising cyber threats is a constant challenge for insurance companies. However, machine learning can help by detecting fraud more effectively. AI-powered underwriting improves security and offers advanced insurance coverage options to handle these threats in better ways. 3. Task Automation Underwriting requires reviewing lots of data and documents to assess risks for new policyholders, which involves manual work like data entry and validation. AI can automate these tasks, cut costs and reduce errors by quickly extracting necessary information. For example, a major US insurer used AI to handle over 100,000 policy adjustments more efficiently by automating data extraction. 4. Fair Pricing AI automatically assesses risk profiles which leads to fairer pricing and removing any biases. It also gathers data from various sources that give agents a complete view of the customer. This helps in accurately determining the risk profile and setting more reasonable premium rates. 5. Customer Satisfaction Generative AI can study people’s behavior and preferences to provide insights that help insurers customize their policies, terms, and pricing. This allows insurers to offer personalized services quickly and effectively, which leads to higher customer satisfaction and builds stronger brand loyalty. Conclusion Implementation of AI into insurance underwriting can save up to 40% of time spent on non-essential tasks. It can potentially save the industry $85 billion to $160 billion over five years. AI helps by minimizing errors, automating routine tasks, and improving security against cyber threats. It also ensures fairer pricing by assessing risk profiles accurately and enhances customer satisfaction through personalized services. With 77% of insurance companies already using AI, it is clear that AI is transforming underwriting and boosting efficiency.

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