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Life Health > Life Insurance

5 ways to improve underwriting rules engines

By Mike Taht, Phil Murphy

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Underwriting rules engines have been used in the life insurance industry since the advent of jet underwriting programs. The concept is relatively simple: design rules such that underwriters spend as little time as possible on clean cases and focus more of their time on complicated cases.

However, in practice, the use of rules engines has many challenges. For underwriting rules engines to materially change the life insurance underwriting paradigm, they must do more than just automate a simplified issue questionnaire. They must align with and balance the needs of applicants, underwriters, producers and actuaries.

Here are five characteristics the underwriting rules engines of the future must possess:

1. Short, well-written questions

Answering underwriting questions has been, and continues to be, the most cumbersome part of the life insurance sales process. The goal of the underwriting rules engine should be to gather all relevant underwriting information in as few questions as possible.

To achieve this goal, they must consider not only what is asked, but also how and when a question is asked. Questions must be scripted such that the answers provided are specific enough for an applicant to provide an equally specific response. The more specific the response, the more effective the underwriting rules engine is at selecting good risks.

Underwriting rules engines must also be structured so that the questions asked are asked only once and use all information available. If structured appropriately, sufficient information will be gathered in a manner that is least intrusive to the prospective buyer. The result is an improved sales process that will increase placement ratios and persistency rates while keeping producers satisfied and loyal.

 2. Smarter data use

In order to get an answer as quickly as possible, underwriting rules engines must use all available information to make a decision. The availability of digitized data that can influence an underwriting decision in the U.S. market is immense. An effective underwriting rules engine must use all available electronic data and adapt to the information gained from these other sources. If you know the applicant is on medication for high blood pressure, this knowledge should be used in both the type of question you ask and your decision.

See also: The next generation of insurance technology: Are we ready?

This can be a challenge since not all electronic data is always available instantaneously. Consideration must be given to the type of data available, its impact on both the underwriting decision and the types of questions asked, and the time it takes to obtain such information. The resulting perspective must then be balanced with product pricing and the desired customer experience.

3. Full integration with the sales process

As alluded to above, an effective underwriting rules engine enhances the sales process from both the agents’ and policyholders’ perspectives. Therefore, an underwriting rules engine must be fully integrated into the sales process. If it is used as a standalone tool for a single product, it will not achieve its full potential.

In the sales process, applicants may initially want one product, and then determine that another better meets their needs. Applicants may also want access to better risk classes in order to get a better rate, in which case the tool needs to be designed to cut off the opportunity for anti-selection.

If an underwriting rules engine — and more broadly, the entire insurance program — does not support this, there is a real risk for customer dissatisfaction. This can not only impact a single sale, but also result in distributor dissatisfaction, which can reduce future sales.

Flexibility and ability to support multiple products is important, but integration is also critical from a risk management perspective. Products, price points and underwriting rules must be aligned to mitigate anti-selection. Applicants should not be permitted to move among different underwriting paradigms within a product portfolio until they find the situation that is most advantageous for them. A quality underwriting rules engine accounts for this, and the delicate balance of the stakeholders continues.

 4. Increased adaptability

Underwriting is constantly evolving. Change may be driven by new research, tools, products or philosophies. Regardless of the reason for change, an underwriting rules engine needs to be easily updated in order to adapt.

Interfaces with third parties need to be easy to configure, and underwriting rules need to be easy to change. Changes to rules should be in the hands of underwriting management and include appropriate documentation and peer reviews. This allows rules to be in production as quickly as possible while still maintaining proper change management controls. Delays in rule changes or in configuring to new data sources can quickly cost companies in terms of missed opportunities to put good business on the books, or, worse, putting poor business on the books while rules wait to be changed or anti-selection continues.

5. An expanded role

Quality underwriting rules engines produce more than just an underwriting decision. They are data facilitators, productivity enhancers and quality controllers.

  • Underwriting rules engines enhance the underwriting process by allowing the right case to get to the right underwriter with the right information at the right time.
  • Data is leveraged to render decisions and transferred downstream for practical reporting and business analytics in order to monitor the business in real-time, allowing companies to take full advantage of rules that are easy to change.
  • Consistency in decision making will help companies avoid putting bad business on the books, while ensuring the proper classification for the cases that are approved. This will not only deliver predictable results, but also mitigates “noise” in the data when considering changes to improve the system and process over time.

Other characteristics are important to a quality underwriting rules engine, but covering the five described here will go a long way to insure long-term success with your underwriting rules engine. Customer-friendly, flexible and scalable are the broad traits that allow you to strike the  balance required to manage profitable business through technology that saves time and money while supporting a great customer experience.

As “Big Data” gains traction and advanced technology leads to new risk management tools, tomorrow’s underwriting rules engines will become increasingly important when it comes to reducing unit costs, driving consistent mortality and morbidity results, and enhancing the agent and client experience. Will you be ready?

For more on life insurance underwriting, see:

Life insurance underwriting: The questions matter

The effects of marijuana use on life insurance rates

Win more premium cases with ‘reverse underwriting’

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