Transforming Underwriting: Why Automation is the Path Forward – and How Data Can Get You There

By: Joe Polizzano, Principal, Data & Technology

It’s not a hard sell to insurers to shift to automated underwriting. A process once laborious and time-consuming could be cut in half, allowing resources to instead focus on bringing innovative new products to market faster. Automation also allows for more self-service and real-time capabilities, ultimately enhancing the customer experience. And, reducing and removing manual processes slices risk and increases response rate speed.

However, it can often be difficult getting there. Despite potential challenges like redefining processes and implementing emerging technology, data is where things can get complicated when it comes to automated underwriting. A recent survey of 400 insurance executives by Intelligent Insurer cited “data” in four out of the top five challenges when implementing new underwriting technology.

They are:

1. Data quality

2. Legacy systems

3. Data acquisition

4. Unstructured data

5. Data management

Automation technology can only succeed when it can truly harness the value of data. After decades of helping insurers leverage the latest technologies to optimize underwriting, here are NEOS’ top 5 considerations for insurers tackling underwriting technology:

1. Data quality: assess and pull together a data governance plan

Before beginning any modernization effort, take time to thoroughly understand and organize the data that will be used by automation technology to make a decision. This means taking time to tag, govern, and curate the data that is used to make a decision. Insurers should also put in place a data governance program to centralize how data is organized, analyzed, and used most effectively for the business.

2. Legacy systems: construct a data migration strategy

Forging a path from old to new technology can be difficult, especially when it comes to data migration. Highly sophisticated, poorly documented legacy systems are par for the course for many insurers, and the volume of data and potential loss during migration can be overwhelming. As you plan your strategy, ensure it contains data mapping, extraction, and delivery. During the process, data should be analyzed and cleansed before leveraging it in the new system.

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3. Data acquisition: have a review process, analyze the data, then save (or dump) it

When insurers improve their data collection by employing a more structured process and better analysis tools, they ultimately can improve their business. The amount of data that insurers have been able to attain in recent years has primarily grown (hence Big Data) due to advancements in new technology. This is good news considering that leveraging all of the capabilities automation can offer requires data—and a lot of it. However, insurers can’t rely on traditional methods to cleanse and store (or dump) this data. Insurers should set a review process and invest in better analytical tools to best feed their automated underwriting engine.

4. Unstructured data: examine your data for a better understanding of customers and prospects.

Unstructured data can be a goldmine for insurers—if it’s used correctly. Insurers still using traditional technology can’t take advantage of all that this data—such as social media, internal information, reviews, and comments on public sites, etc.—has to offer. If you don’t have your arms around this type of data, you’re likely still limited by only using CRM, policy, and claims data. To maximize automation—and especially AI—consider a strategy around analyzing unstructured data. Information gleaned with this data will help paint a much better story—ultimately allowing you to offer better, more relevant products and services to customers.

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5. Data management: treat your data like it is gold—because it is

Some of the most mature insurance organizations hold and protect their data like it’s their most precious asset—because it is. When you consider data this way, how deliberately are you protecting it, analyzing it, and storing it? Also, when it comes to automated underwriting and as new customer data is collected, it needs to be leveraged for new insights that may be gleaned from it. To maximize your data assets, consider appointing data stewards that are responsible for the definition, quality, and lineage of your most important assets.

5. Maximize your full potential by harnessing the power of data

While the biggest challenges outlined by executives in the survey above related to data, so do the most significant opportunities. As a provider with years of experience integrating emerging technology in the insurance industry, it would behoove all insurers looking to leverage the full potential of automation in underwriting—or any emerging technology—to follow these steps. Failure to get your data in gear before adding new technology could spell disaster—wasted resources and budget, poor analytical capabilities, and ultimately failing to deliver upon a business goal.

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