Automated underwriting rule sets have been utilized in underwriting rules engines for years in the United States. Those rule sets are being offered from many sources, including reinsurers, IT vendors and consultants, as well as being developed in-house by the direct carrier. The scripted rules are part of the automated underwriting process delivered through call-center tele-interviews, websites or agent delivery.
Not all rule sets are comparable or perform in the same manner. Poorly crafted rule sets can be the garbage in/garbage out definition of poor computer programming. The right questions in the right order offer protective value.
Good rule sets need to be carefully crafted by experienced personnel with many underwriting criteria, parameters, market characteristics and attributes taken into consideration. The direct carrier’s target market, market niche, distribution channels, marketing and product parameters (e.g., line of business, plan types, face amounts, issue ages) all play a significant part of the rules design process.
The basic aim of all underwriting rule sets is to reduce the number of applications that require manual underwriting at the first stage of assessment. Reducing that number provides four key benefits:
- Speed: A higher rate of immediate acceptance means less time spent on manual underwriting assessment with the additional effect of reducing “not taken” rates.
- Cost savings: A reduction in costs associated with both manual underwriting assessment and obtaining further evidence.
- Consistency: Anomalous and erroneous judgments made by underwriters are avoided.
- Improved customer experience: A much faster, easier and less intrusive customer experience for the insured.
Asking the right questions
Non-disclosure of information required for the underwriting process has been an item of consideration with automated underwriting. Many times, a person’s favorite subject is himself. Given a chance, an applicant is very forthright with information that’s as accurate as possible when asked the questions correctly. Often times, during tele-interviews, applicants will want to provide more information than necessary to accurately complete the underwriting process.
Automated underwriting questions cannot be leading or make assumptions about the applicant. The old question ”You don’t smoke do you?“ will not provide accurate information on the person’s tobacco use history. Similarly, an applicant who has disclosed a history of high blood pressure may then be asked when she last saw her doctor. The issue is that the person may not have ever seen a doctor for this or any other condition.
The amount of time an applicant will spend on the underwriting process is limited. Since insurance can be viewed as a “nice to have” and not a “need to have,” there is a point in the process when the drop-off rate increases dramatically. So, when the kids are crying and the dog is barking, there is a good chance the applicant will stop the underwriting process after answering 45 minutes of personal medical questions. Being aware of this type of scenario is why limiting the number of questions and asking “knock-out” questions early on in the process not only increases the amount of placed business, but also offers a much better customer experience.
Traditional Latin medical terms may be accurate when diagnosing a medical condition, but they are not appropriate for automated underwriting. This can become a factor in claims review. Hard-to-pronounce diagnoses are not the way to address a condition in a good underwriting rules set. Asking if the person has high cholesterol instead of hyperlipidemia will improve the performance of the automated underwriting process.
Even when using simple English, a person may not know the answer to a specific question. For example, an applicant with coronary artery disease may not know his ejection fraction, but he should be able to identify how many heart attacks he’s had and how often he sees a doctor for this condition. Many times, a question the applicant cannot answer, even if it’s phrased properly, can prevent the applicant from being issued coverage immediately.
A vast majority of applicant’s disclosures will pertain to a limited number of underwriting conditions. Therefore emphasis should be placed on these high prevalence conditions. The fundamental basis for the philosophy relies upon the Pareto principle, otherwise known as the 80-20 rule. This principle basically states that roughly 80 percent of an effect comes from 20 percent of the cause
Focusing on the 20 percent of disclosures that are most frequently made has the greatest impact on straight through processing (STP) rates and reduction of medical costs. Utilizing existing client data to identify the most frequent and, therefore, high-priority disclosures can be reflected in the base question design and the drill-down questions that follow.
More improvements on the way
We have come a long way with automated underwriting systems in the last 20 years, starting with the original accept/reject systems asking the applicant questions through the rules engine. A pricing cushion was built in to compensate for the protective value of the underwriting requirements that were being waived.
Now, with database checks being offered in real time, we are beginning to change the underwriting requirements, making them much more customer-friendly, faster and cheaper than what has been used for years. The pricing trend is moving toward fully underwritten standard pricing, with the direct carriers benefiting from higher placement ratios due to a much faster and easier process of issuing insurance.
The future will entail even more new exciting paradigms such as predictive modelling and the use of Big Data to even further speed up the issuance of insurance with better business performance metrics for the direct carrier and a superior buying experience for the insured.