Automation plays a significant role across the entire economy, particularly in the insurance industry, where insurers have been using it to transform the traditional underwriting process. It can help them optimize repetitive tasks and gather data-driven insights promptly.

However, there are some limitations of this advanced technology that highlight the need for people power to remain in these processes. Below, we’ll explore what automated insurance underwriting looks like, some of its limitations, and the synergy that insurers can uncover when they balance people power with automated insurance underwriting.

Understanding Automated Underwriting

Automated insurance underwriting systems utilize machine learning or artificial intelligence algorithms to analyze an applicant’s data and predict future risks. They can determine whether or not to approve the applicant for an insurance policy, what types of policies they should be offered, and the premium they should be charged.

As such, these systems are designed to assess data from multiple data sources, including applications, credit reports, medical records, driving records, and more, to identify the risk of insuring the individual and the likelihood of a claim being made.

Underwriting automation is becoming increasingly utilized in the insurance industry because it can execute faster decision-making, provide more accuracy than manual underwriting, and reduce costs for the insurer.

The Limitations of Automation

Though automated underwriting can help insurers become more efficient in some ways, this approach has some drawbacks, including the following.

Lack of Personalization

An automated underwriting process relies on data and algorithms to make policy recommendations, meaning it likely doesn’t consider a policyholder’s unique circumstances or personal situations like a human underwriter could. This lack of personalization can lead to unfair or inaccurate decisions, especially for people with more complex or unusual applications.

Lack of Transparency

One of the most significant issues that automated insurance underwriting poses is the lack of transparency regarding how the system comes up with results. Automated systems can be difficult to understand or audit, especially when complex algorithms are in play. The lack of transparency can make it difficult for insurers to identify and correct errors or biases in the system.

Limited Scope

Machine learning-based systems are typically built to focus on a narrow range of factors to complete risk assessments, including age, gender, and other pertinent data to the policy, like health history or driving records. Manual underwriting can consider more nuanced factors impacting an individual’s risk profile, such as lifestyle choices or family history. In many cases, underwriting automation isn’t built to do this, meaning underwriting decisions could be impacted.

Data Quality Issues

Data quality can have major implications for the accuracy of decisions that are made by the program. Data errors, incomplete data sets, or biased data can lead to incorrect conclusions and unfair outcomes from underwriting automation. This is worrisome for insurers and policyholders; insurers need to trust that their underwriting process properly assesses risk, and policyholders want to ensure they get a fair chance at being approved for a policy.

Is Customer Data Secure with Automated Insurance Underwriting?

Like the adoption of any other digital solution, there is a heightened concern around the secure use and storage of consumer data with automated insurance underwriting. Underwriting requires sensitive data, so policyholders want to make sure their information is properly safeguarded from unauthorized access. 

Though individual security measures will vary depending on each automated solution, there are widespread data privacy regulations in place to help protect consumers in this regard. These tools will need to comply with the relevant standards in order to operate. Typically, automated underwriting solutions utilize security features like data encryption, access controls, and secure hosting to protect policyholder data. 

What Role do Algorithms Play in Automated Underwriting?

Algorithms are what make it possible for automated underwriting solutions to accurately process and derive valuable insights from large datasets. 

Automated underwriting solutions leverage AI-powered algorithms to accurately assess an applicant’s risk based on various factors like credit history, financial data, health information, and demographics. With this, they can use algorithms to predict the likelihood of a claim being filed, and what the cost of that claim might be. 

Based on these results, the automated solution can make important underwriting decisions, including the level of insurance coverage, premiums, and policy terms that should be offered to the applicant. 

How Accurate are Automated Underwriting Decisions?

A big question many policyholders have around the use of automated underwriting is whether they will be fairly and accurately assessed. Specifically, will they receive the same kind of pricing and policy recommendations from an automated system compared to a manual underwriting process?

The truth is, it depends. Automated solutions can provide more accurate outcomes in certain cases, as they’re able to process much larger amounts of data than humans can. But, there are many factors that contribute to the accuracy of automated underwriting decisions, including the quality of data being inputted into the system, and how the system is designed and validated. 

For these reasons, the best underwriting outcomes stem from using automation and human decision-making together, combining the data-processing power of automation and the nuanced experience that humans provide. 

The Importance of People Power in Underwriting

Despite the growth of underwriting automation, there is still a need for people power to ensure fairness and accuracy in underwriting decisions. Humans can provide additional insights, judgment, and expertise that automation cannot. Where automated insurance underwriting has shortcomings, human underwriters can account for the more nuanced side of risk assessment.

By supplementing automated underwriting with human expertise, insurers can make sure that they’re making accurate and fair decisions. They can rely on experienced underwriters to review complex cases, ask the right follow-up questions, and make informed judgments and recommendations.

Moreover, human oversight can help prevent the development of biased algorithms that unfairly discriminate against certain groups of policyholders. By maintaining some level of a manual underwriting process, insurers can monitor and audit automated underwriting systems to ensure they’re following ethical and regulatory guidelines and intervene if necessary.

Some examples where human decision-making is particularly relevant for insurance underwriting include:

Complex medical histories: Underwriting automation may not accurately assess the risk of insuring individuals with complex medical histories or multiple pre-existing conditions. Human underwriters with medical expertise can review a policyholder’s medical records and provide additional context to create a more accurate risk profile for them.

Non-standard/high-risk occupations: Life insurance providers may need to utilize manual insurance underwriting to account for the unique risks associated with non-standard or high-risk occupations (pro athletes, stuntmen, etc.) before approving them for a policy.

Unusual/high-value assets: When an insurer is approached to cover unusual or high-value assets, like fine art collections or vintage cars, it requires a more nuanced approach than standard policies. Human underwriters can provide expert advice and make informed decisions about appropriate coverage and premiums.

The Benefits of Combining People Power and Automation

Manual and automated insurance underwriting each provide benefits and drawbacks to insurers. Striking the right balance can offer some unique advantages, including:

Better Accuracy

Underwriting automation makes it possible to quickly analyze large amounts of data in a way that wouldn’t be possible for humans. But, human underwriters can offer additional insights, expertise, and judgment that AI-based programs cannot. Both methods can lead to more accurate risk assessments and insurance coverage.

Improved Efficiency

Insurers can streamline the application process by quickly analyzing data and completing a standardized risk assessment with automation, then humans can focus on the more complex cases where additional context is needed. Manual underwriters can benefit from a reduced workload, focusing instead on higher-value tasks.


Automated underwriting offers speed and efficiency, while human decision-making can offer personalized advice and support to account for an individual’s unique circumstances. Balancing both approaches enables insurers to provide more personalization with their policy recommendations.

Better Policyholder Satisfaction

Another benefit of using human decision-making and automation together is boosting policyholder satisfaction. With a more efficient application process and personalized advice and support, policyholders face less friction when applying for a policy, which promotes a better policyholder experience overall.

Regulatory Compliance

With humans revising the policy recommendations of automated systems, insurers can ensure that they’re following ethical and regulatory requirements. The goal is to reduce the risk of discriminatory or unfair practices, which can help insurers comply with the law and avoid regulatory penalties.

The Bottom Line

Manual and automated underwriting processes each produce a unique set of benefits. The traditional approach incorporates human expertise and nuance in key decision-making that technology cannot offer, while manual data processing speeds are no match for the impressive efficiency of automation. 

Undoubtedly, emerging technologies like AI and automation will continue to take hold in all industries, including insurance. However, there will always be a necessity for the human touch in critical insurance processes like underwriting, which automation can complement, but never replace. 

Striking a Balance in Automated Underwriting

Striking the right balance between automation and human decision-making requires having the right team of experts – experienced professional underwriters who understand the complex nuances of the assessment process. This combination can ensure insurers receive a blend of speed, efficiency, and accuracy.

Insurers looking to enhance their underwriting capabilities and boost efficiency can partner with a Business Process Outsourcing (BPO) partner for all their people power needs.

At Covenir, we have extensive onshore experience in underwriting support and other premium services. We’re not just an extension of your team-we are your team. When you partner with us, you can feel confident that your policyholders are receiving the reliable service they’ve come to expect from you, though you’ll have more time to work on strategic initiatives that move the needle forward for your business.

Contact us today to see how our turnkey solutions can give you the people power you need to enhance your underwriting processes.