For over 30 years, AXA’s culture of innovation has propelled them to the forefront of technological development in the life insurance industry. Now, their goal is to optimize the way they process enrollment forms and ensure that the onboarding process is a seamless experience for financial advisors and customers alike.
“The aim of any insurer’s new business department is to make the best, most accurate decisions at the point of sale,” explains Louis DiModugno, former Chief Data and Analytics Officer for AXA US. That directive fuels the company’s search for new and novel paths to continuous improvement in the department, as well as throughout the organization.
One of AXA’s group annuity products was heavily dependent on paper-based forms. Enrollment for the product was seasonal, with incoming application numbers doubling during enrollment season.
AXA’s paper applications were entered manually into systems of record, which required their data entry team to accommodate volume peaks. AXA found that hiring temporary workers to enter application data was expensive and time-consuming, and sought a more efficient process.
Manual data entry creates a long-standing problem for operations that use paper-based forms: poor-quality data. That poor quality data is classed as “not in good order” — and according to industry benchmarks, 70 percent of paper applications are considered “NIGOs” with one or more errors that must be corrected in order to issue a product. Correcting mistakes in the data requires costly and time-consuming rework, and is an irritant to both advisors and customers who expect smooth and painless interactions.
According to research conducted by Celent, staffing costs constitute the highest percentage of new business budget expenses. To manage these costs, AXA chose to streamline their seasonal volume processing routines as a way to reduce cycle times, which, also according to Celent, is the metric generating the most attention for new business departments.
Improving the number of group annuity applications that were eligible for “straight-through” processing was another key consideration for AXA, who sought significant process improvements to increase efficiency and decrease cycle times for their customers.
AXA and Captricity joined forces to create a process to measure, analyze, and optimize the way customer enrollment forms are digitized and processed. “We put our heads together and asked, ‘how do we find the 20 percent of issues that contribute to 80 percent of the problems in a given process?’” says DiModugno.
Tracking down those high-value problems meant getting to the root causes of NIGO data — before it entered downstream processes or led to costly rework. As DiModugno puts it, “we asked, ‘how do we make sure that we’re only processing accurate and correct information from our customers at the point of enrollment?’”
Focusing on a line of business with a handwritten enrollment application that resulted in thousands of NIGOs annually, Captricity examined the specific fields and root causes of the NIGO data. Working with a sample set of forms, Captricity measured the data quality for each data field on a paper form to determine common sources of NIGO data.
Knowing that this kind of detailed NIGO analysis is not common in new business departments yet, AXA saw Captricity as offering a competitive advantage. “Most insurers can tell you the percentage rate of NIGOs they have in a given workflow,” DiModugno said, “but they can’t tell you why they occur, or pinpoint which data fields may be causing NIGOs.”
After analyzing the fields most likely to yield NIGOs, Captricity took a deeper look at AXA’s form design. The simplest way to get higher quality data from customers and prevent NIGO data is through data-driven form design. AXA’s enrollment forms were analyzed to determine where a customer may fill in incorrect information because of issues such as confusing instructions or insufficient space to write a full answer. Once areas of the form that were leading to poor quality data were identified, Captricity recommended customer-focused design changes.
The next step: refine the application process to give customers a seamless, frictionless experience.
AXA desired a way to find data errors quickly, get better quality data, and create better enrollment forms that would contribute to a great customer experience.
To meet that challenge, Captricity identified third-party data sources that can automatically correct data that’s inaccurate, saving the time it would take for an AXA representative to reach back out to an advisor or customer. For example, the first field analyzed was the phone number field. All digitized phone numbers were run through the Twilio phone recognition API to validate whether the information provided was correct. 67 percent of home phone numbers, as well as 51 percent of mobile numbers, were blank — and only 25 percent of numbers listed as “home” were landlines.
Next, addresses were analyzed. When addresses were run through an address validation and correction API, 41 percent of the addresses could be improved, while 25 percent had fields missing data completely.
Without an automatic validation process, data quality problems require rework that can dramatically lower customer and advisor satisfaction. Validating contact and annuitant information before transmitting data to other systems and workflows ensures that AXA’s data is high-quality and reliable, and can be trusted by other departments and analysts.
Simplify the Enrollment Process with Captricity
Using Captricity’s intelligent automation technology, handwritten applications can be digitized quickly and accurately, regardless of volume. Say goodbye to hiring temps and seasonal backlogs. For more information, visit our resources page and check out Captricity’s resources on Intelligent Automation: http://captricity.com/resources/.