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Underwriting – Manual Vs Artificial Intelligence

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Underwriting is the process of evaluating, accepting, or rejecting risks to determine whether or not to insure them. In the past, underwriting was a manual, time-consuming process that involved significant human effort. However, with the advent of artificial intelligence (AI) and its applications in underwriting, the process has become more efficient and accurate. This white paper aims to explore the advantages and disadvantages of using AI in underwriting compared to the traditional manual approach.

Manual Underwriting

Manual underwriting has been the standard practice in the insurance industry for many years. It involves evaluating an individual or organization’s risk factors, such as their financial history, health, and past insurance claims, to determine their insurability and insurance premium. This process is done manually by underwriters, who are trained professionals with knowledge and experience in assessing risks. They use their judgment, intuition, and expertise to decide whether to accept a risk, what coverage to offer, and at what premium rate.

Advantages of Manual Underwriting

One of the key advantages of manual underwriting is the human element involved in the process. Underwriters have the ability to understand complex situations and assess risks based on multiple variables that may not be captured by algorithms. This aspect enables underwriters to take a more comprehensive and personalized approach, resulting in more accurate risk assessments. Additionally, through manual underwriting, underwriters can tailor coverage to the specific needs of an individual or organization, taking into account their unique circumstances.

Another advantage of manual underwriting is the ability to handle complex and non-standard cases. In certain situations, such as high-risk policyholders or unique insurance requests, relying on AI may not yield the most appropriate solutions. A skilled underwriter can evaluate unique situations and provide custom coverage that may not be available through automated processes.

Limitations of Manual Underwriting

The main limitation of manual underwriting is the time and resources involved. Underwriting a single case may take several days or even weeks, depending on the complexity of the risk. Additionally, manual underwriting is prone to human errors, which may result in incorrect risk assessments and premiums. This possibility of error may result in higher costs for both the insurer and the insured.

Artificial Intelligence in Underwriting

The use of AI in underwriting has gained immense popularity in recent years. AI algorithms use vast amounts of data to identify patterns and make predictions, enabling underwriters to process large volumes of data quickly and efficiently.

Advantages of AI in Underwriting

The most significant advantage of using AI in underwriting is its ability to process vast amounts of data in a short period efficiently. This capability allows underwriters to analyze data from various sources and make more informed and accurate decisions. Additionally, AI does not suffer from the limitations of human bias, fatigue, or errors, resulting in consistent risk assessments and premiums across similar cases.

Moreover, with AI, the underwriting process is less time-consuming, and it can be completed in a matter of minutes instead of days or weeks. This speed and efficiency have contributed to improved customer satisfaction and increased revenue for insurers.

Limitations of AI in Underwriting

One of the major limitations of using AI in underwriting is its lack of personalized and human touch. AI algorithms may not take into account personal circumstances, which may result in unfair or inaccurate risk assessments. This drawback is especially true for unique cases that require human judgment and intuition to determine the appropriate coverage and premium rates.

Another limitation of AI in underwriting is its dependence on data availability and quality. If the data used for training an AI algorithm is inaccurate or biased, this may result in incorrect predictions and risk assessments. Additionally, AI relies on historical data, which may not account for future events or disruptions, making it challenging to predict risks accurately.

Manual Vs. AI underwriting: A Balanced Approach

 When discussing manual underwriting versus AI, it is important to note that these two approaches are not mutually exclusive. In fact, the most effective underwriting processes involve a combination of manual and AI methods, with underwriters using AI as a tool to support their decision-making.

Underwriting requires a balance between personalized, human expertise, and advanced technological capabilities. While AI can process vast amounts of data quickly and efficiently, it cannot replace human intuition, empathy, and understanding of complex situations. A balanced underwriting process can leverage the strengths of both approaches, resulting in more accurate risk assessments, personalized coverage, and efficient delivery.


In conclusion, the adoption of AI in the insurance industry has revolutionized the underwriting process. However, it is essential to recognize that manual underwriting still plays a critical role in ensuring accurate and personalized risk assessments. AI can support underwriters, but it cannot replace the unique advantages offered by human expertise. A combination of manual and AI underwriting provides the best solution, resulting in efficient, accurate, and personalized risk assessments for insurers and insureds alike. As the landscape of underwriting continues to evolve, it will be important to find this balance to achieve the best possible outcomes.

About Apoorva: 

Apoorva is a technology services company that assists software products with ideation, developing prototypes, programming, creating a digital marketing presence and accelerating sales through direct contact. Over 150 for-profit and non-profit organizations, such as Xcel Energy, PeopleCare Health Services, Frontier Airlines and Centers for Spiritual Living have trusted Apoorva to build software. 

Apoorva was founded in 2001, has more than 50 employees, and uses proprietary and proven methodologies to bring technology products to the market. Contact us /  Visit for more information.

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