Human Input to Digital Data: Crossing the Divide
October 30, 2017 by Jeanette Sherman
Earlier this year, Celent analyst Colleen Monks examined the role of technology in helping insurers drive new business. In Clearing the Bar: Digitizing New Business with Technology and Tools, Monks notes: “Although a variety of systems exist to automate the new business and underwriting process, the majority of insurers are not using them; paper applications and manual underwriting still reign supreme.”
The study showed that at least half of the insurers in the study use digital tools in their new business process, including electronic applications, e-signatures, imaging, workflow systems and others. Celent also found that companies using electronic applications deal with significantly less not-in-good-order (NIGO) information than those using paper applications.
NIGO rates for electronic applications were reported at five percent. The average NIGO rates for paper applications? A staggering 69 percent.
If we know that digital data tools can deliver higher accuracy, why do many insurers still use paper processes that require lots of human time and effort and generate a ton of mistakes and rework?
The answer’s easy: paper is still used because it offers versatility and human-level convenience. Paper has been very handy for collecting complex policyholder data and explaining complex policy information. Paper is central to the claims adjudication process, too. Adjusters often rely on data from old policy forms and certificates generated before the digital era, especially when it comes to serving beneficiaries’ needs.
In a highly regulated industry built on the reduction of risk, it makes sense that incumbent insurers are naturally cautious about everything: reserve is the foundation on which their businesses were built.
Paper processes don’t have to mean relying on error-prone, time-consuming workflows like manual data entry. When applications are sent back for corrections and remediation, agents and policy applicants often feel frustrated. Many — even most — applicants will drop out of the application process if they are approached to review incorrect information.
(According to an Ernst & Young survey, 40 percent of customers left an insurer in the past 18 months. Sixty percent of North American responders said that “ease of doing business with an insurer” was more important to them than getting “value for money.”)
The time it takes to collect, structure and analyze data from core systems, multiple streams and input sources can diminish its value and slow critical processes. And paying highly-skilled full-time employees to perform low-skill manual data entry is an expensive waste of talent.
Insurers that have a “wait and see” approach to embracing new technologies have seen plenty of expensive data mining initiatives fail; they have seen the cost and middling success rates of costly rip and replace approaches to getting data from core systems.
What they need to see is the bridge between human systems and digitization. The right bridge eliminates wasteful and repetitive data processing, and unites the strengths of people and paper without disrupting how work is done. The right bridge is scalable, withstands cyclical fluctuations in volume, and is a robust, agile platform built to evolve throughout the digital age.
Captricity has built the right bridge for many of America’s biggest insurers.
The core of Captricity’s data platform, crowd-guided machine learning, combines the power of advanced machine learning and crowdsourcing to replace manual data entry with a single and reliable cloud-based solution. This unique pairing of people and machines delivers an unprecedented accuracy rate of 99%+, even for unconstrained handwriting.
Ready to cross the divide? Learn how Captricity can make it possible at www.captricity.com.