Automating Underwriting Approval Processes With a Human Touch: 4 Things to Know

As technology continues to advance, the insurance industry is seeing a shift toward automated underwriting approval processes. This trend has been gaining momentum over the past few years and is expected to grow as insurers seek to streamline their operations and reduce costs without losing the human touch.

Traditional underwriting processes often come up short on operational agility, resulting in lengthier time to quote and a poor customer experience. As insurers look to increase efficiency and agility, they should turn to emerging technologies like machine learning, intelligent document processing (IDP), artificial intelligence (AI), and process automation to augment the capabilities of human underwriters and free them up to focus on more high-impact tasks.

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It’s hard to talk about automated underwriting without talking about data. In fact, data is the lifeblood of automated underwriting, and its quality and accuracy are paramount to the success of the process. But it’s essential for insurers to have access to high-quality and accurate data when making underwriting decisions. 

While the type of data you’ll need varies based on the insurance policy and specific underwriting requirements, it could include everything from personal information (e.g., age, gender, occupation, etc.), credit and claims history, medical and lifestyle factors, and driving records. Claims history helps with evaluating the risk profile of a customer. Using algorithms to quickly analyze all of these data points enables insurers to make faster and more accurate underwriting decisions.

On the flip side, automated underwriting has raised concerns related to data privacy and security. It’s important for insurers to comply with data protection laws to ensure customer data isn’t vulnerable to cyber threats such as data breaches and hacking attempts. In addition, insurance providers need to be transparent in how they use customer data so customers feel confident that their data is safe. Ultimately, data quality, accuracy, privacy, and security are critical success factors in automated underwriting. 

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With AI-driven risk assessment models, insurers can quickly and accurately predict the likelihood of claims, resulting in more accurate underwriting decisions and faster turnaround times. But critics worry about fairness and bias. So, insurers are under increasing pressure to ensure that AI models used in underwriting are transparent and explainable to avoid perpetuating biases that may lead to unfair outcomes.

Long story short, automated underwriting can bring next-level accuracy and speed to the underwriting process and transform the customer experience. But successful automated underwriting also hinges on whether an insurer takes a human-centric approach to automation—one that is developed ethically and transparently to maintain the integrity of the underwriting process while providing a superior customer experience.

This includes ensuring that underwriting approval processes comply with relevant regulatory requirements, such as data protection and anti-discrimination laws. Transparency is also critical to ensuring customers have visibility into how their data is used. Insurers must also develop a framework for ethical decision-making that avoids perpetuating biases. These are must-haves for creating underwriting processes that are transparent and compliant with industry regulations while also increasing customer trust and driving business growth.

A solid implementation and integration strategy is essential to getting the most out of automated underwriting. The first step is to find a system that fits your organization’s underwriting goals. This involves understanding your business requirements, assessing your current IT infrastructure, and selecting a system that meets your specific underwriting needs. Consider the level of automation needed, all the data sources required, and whether the system you’re evaluating is flexible enough to easily integrate with your existing technology stack.

Once you’ve selected the right system, the next step is to integrate it with your existing IT infrastructure and processes. This requires a thorough understanding of your current technology stack, including your CRM, policy administration systems, claims systems, advanced data sources (telematics, IoT, etc.), and other critical applications. Getting this right means closely working with your IT team and your vendor's implementation team to ensure a seamless integration that does not disrupt your existing business processes.

Finally, it's important to consider change management and employee training. Implementing automated underwriting will inevitably require changes to your existing business processes, and having a plan in place will help you manage these changes effectively. This may involve providing training to your employees to ensure they understand the new system and how to use it effectively.

It also pays to have a clear communication plan to keep employees informed of changes and updates throughout the implementation process. Prioritizing change management and employee training is essential to making a smooth transition to automated underwriting and maximizing the benefits it can provide.

The insurance industry is facing a serious talent crunch as it scrambles to attract and retain skilled staffers in the face of rapidly changing demographic and technology trends. For perspective, the National Association of Mutual Insurance Companies predicts that in just over a decade, 50% of the current insurance workforce in the US will retire, leaving more than 400,000 open positions unfilled.

But it’s not just about simply hiring more workers. Insurers need to figure out how to improve employee satisfaction, attract and retain talent, and scale their existing resources. Automation can help. 

For example, routine policy reviews can be automated. Automation can also help reduce workloads by handling rote, repetitive tasks—things like reading massive amounts of lengthy, complex documents, processing claims, and wrangling and interpreting disparate data to speed more accurate decision-making by claims adjusters. And as part of a talent augmentation strategy, automation can boost job satisfaction for younger employees by shifting mundane tasks to machines so the employees can engage in more value-added work. 

Here’s the bottom line: The insurance industry is facing a talent crunch brought on by a confluence of demographic shifts, digital transformation, and ever-changing consumer demands. Whether insurers choose to hire and train more people, invest in their current workforce, augment the capabilities of staff with automation, or do a combination of all three, the time to act is now. 

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Before we call it a day, let’s recap four key takeaways for automating underwriting approval processes with a human touch:

1. Go to school on the importance of data quality and accuracy.
2. Use AI and machine learning to drive efficiency and productivity while staying transparent and compliant. 
3. Implement solid implementation and integration strategies.
4. Use automation to help your organization attract and retain top talent.
    

What it all comes down to is this: taking a human-centric approach to automating underwriting approval processes isn’t just a luxury, it's a necessity for insurers that want to stand out from the competition now and in the future.

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