There is a potted plant somewhere in your office, or maybe in the lobby of your building. It's a healthy plant. Perhaps it's one of those office fig trees. It looks healthy, but from a life-cycle perspective, it's in trouble. The roots are cramming themselves in every nook and crevice of the pot because they can't escape. At some point, it will suffer because it needs room to expand. It needs someone to get it out of the pot and into the ground.
This is where the existing new business and underwriting process is today within many insurance carriers. It's keeping insurance companies in the pot. That's why so many organizations are looking at their new business and underwriting process for improvements. With a redesigned underwriting process, your company can seek new markets, get business on the books faster and improve decision consistency that will ultimately save it millions of dollars with improved mortality.
But for all of its promise, new business and underwriting automation needs to be done properly to be effective in your operations and to your bottom line. Giving your roots room to grow requires a good look at your goals.
Speed
One aspect of moving to automated underwriting is the improvement insurers find in their App-to-Decision cycle. Long and inefficient cycles often have root causes in manual processes or existing point-to-point solutions that evolved at different times, were provided by different vendors and cobbled together over time. When there is a spike in new business, existing inefficiencies require firms to hire additional underwriters, or they risk losing new business. However, the acquisition and training of underwriting resources is a time-consuming and expensive process that may not reflect immediate improvement in those app-to-decision cycles. Moving to more automated underwriting can cut days or weeks off of the App-to-Decision cycle time, freeing marketing to reach into new markets and open up the pipeline without overwhelming underwriters.
Rules Engine
Use of any Rules Engine can help you automate decisions. The more rules you have, the better the rules engine is might be your company's common thinking, but in reality, an unwieldy rules set may not always be helpful. However, the caliber of a good Underwriting Rules Engine is having a well-honed set of relevant rules with the ability to manage, update and audit the rules efficiently. This consequently provides insight into how good or effective a rule is and allows you to change it rapidly while engaging those who understand the decision directly.
Additionally, the core of any good automated underwriting system is a robust Rules Engine built specifically with the complexity of underwriting mind. The Rules Engine is the consolidator, the traffic director and the decision maker rolled up into one. They have to know what to do with MIB, MVR, APS and other data, make the correct decision recommendations and properly route application information, complementing your organization's traditional approach to underwriting and providing expansion opportunity.
Structured Data and Analytics
The underwriting process generates a tremendous amount of data. But even in the best automated solutions, standardized data and a good Rules Engine have limited effectiveness if you cannot model patterns and gain insight into your new business issuances. However, predictive analytics can drive better insights, informing and helping you to tailor your Rules and processes. Getting to the best predictive analytics requires the capture of every data element and decision detail, then storing it in a structured format. The more data you can capture — every bit of the requirements data, every answer to every question, all of the records you can get into the system — the healthier your analysis will become. It's like giving your office plant the best food, the best water, the spot with the most sunlight and an atrium bed instead of its pot. Your system will thrive on good data and so will your results.
The key is to get the same quality data from all of your applicants, or to normalize it in your repository, so that your sampling base is as large as possible. The science behind predictive analytics continues to fuel dramatic improvements in decision-making throughout hundreds of industries. In life insurance, predictive analytics will allow you to price effectively and create leaner products that require less padding and fewer reserves. Marketing and your actuarial team will love getting their green thumbs on the business intelligence tools and data you can provide them with.
Mortality Accuracy
All of your work getting the right decisions culminates in one very important goal, too often lost in the discussions regarding underwriting — improving mortality. Mortality inaccuracies are the highest cost of Underwriting inconsistencies and improving accuracy is the best way to ensure the long-term financial health of your life insurance book of business. Improving your risk assessment process through the automation and the capture of standardized data provides you insight, not only into your rules, but also into your underwriters' decisions. Studies have shown that very slight fluctuations in mortality management (as little as half of one percent) can have a dramatic positive impact on an insurer's bottom line, and with proof of decision consistency, your organization can reduce capital and reserve costs, increasing profits.
Underwriting and Technical Expertise
The last piece of the puzzle falls outside of an automated underwriting system. It involves a partnership and is equally important to developing a process that works. When bringing together your underwriting experts, your in-house technical expertise and outside underwriting technology consultants, you have a team that will make the most of automated underwriting. Given the strategic significance of this functional core process, it only makes sense to pair up your resources with an experienced firm that has strategies and software that will transform your new business and underwriting process. A trusted partner will help you accomplish change quickly with as little disruption as possible. They'll bring the experience of many implementations with them, understanding the hurdles and knowing what it takes to get a job done right the first time.
(Erik Stockwell is senior vice president for MajescoMastek.)
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