At a time when technology
innovations are giving a total makeover to the insurance industry, the digital underwriting automation processes
have seen slower growth than other operational areas. This, despite the fact
that it is the one that customers always perceive as a differentiator. In fact,
a survey by EY suggests that a massive 87% of all policyholders consider it a
core reason for changing their insurer. Having said so, the industry has been
spending considerable time and money on the InsurTech module which empowers
adjusters and agents to automate manual tasks, sift through massive data sets
and provide a satisfying customer experience.
Faster claims processing with
limited human intervention coupled with an ability to evaluate and make
data-driven decisions is what could customers with an insurer. Existing
technology innovations use workflows, rule-driven automation, interfaces and
data enrichment to automate processes and provide the transparency that
customers are always looking for in claim settlements. From an insurer's point
of view, these innovations also assist in fraud detection besides assisting the
third-party administrators with auto-adjudication options using artificial
intelligence.
In fact, artificial intelligence
also plays a part in enhancing service quality and delivery of communication to
the customer. Since more and more data is getting added to the insurance
database, the machine learning modules help the system better understand the
various claim scenarios. They not only guard against customers being
overcharged, but also provide them with timely updates during the entire claim
process. These data points are shared via automated calls, text messages,
Whatsapp and through customized mobile applications built by the insurers.
The automation of the entire digital claims has been an ongoing process and is slowly
getting extended to new claim types. The automation process faithfully follows
decades-old templates that track a claim from the moment a policyholder alerts
the insurer to claims investigations, policy checks, payment calculations and
actual payout. What's changed is that the third-party administrators, who
relied on manual intervention to process claims, have upgraded. They are now
using artificial intelligence and machine learning created as homegrown
solutions to automate the process based on the industry that it maps to.
For example, in the healthcare
business, InsurTech has based the transformation protocol around the
digitization of tariff, historical medical data, hospitalization bills and
discharge summaries. TPAs work out a standard operating cost with their
hospital networks that consumers have access to and saves them from surprise
expenses. Similarly, claims evaluated and settled at hospitals also are made
available, helping the customers determine actual costs. The AI-ML integration
with the digital forms ensures that the bills and charges summaries are far
more accurate, a factor that helps TPAs automatically arrive at the validity of claims under
policy conditions.
As discussed earlier, the claims
process is what makes or breaks a customer relationship and each time there is
a dip in the satisfaction index, the insurer costs tend to go up. This is where
the richer, data-driven and analytics-enabled customer experience comes into
play. Take the case of property and casualty insurers using historical repair
data to decrease estimating time for cars or houses or how advanced telematics
data could instantly capture details of an automobile accident and actually be
used to trigger a first notification of loss.
The advent of robotic process
automation (RPA) marked the first step towards automation where programmed bots
acted as digital workers and took over the mundane and repetitive tasks.
Process claims were automated using RPA, making it much faster and more
efficient. Some of the functions that got automated included copying and
entering data across systems, reconciling and verifying claims data, gathering
information from emails and automating the workflow with a set of rules. The
introduction of AI further enhanced the overall bot capabilities, while
cognitive automation helped analyze images, audio and natural language texts
wherever they figured in the claims process.
Having traversed the journey to this
point, where does claims automation go from here? At the base level,
third-party data could get integrated with existing records that could
potentially enhance automated notifications and chat bots. Deployment of drones
as adjusters could be another change that we could witness sooner than later as
insurers seek to expand automated claims handling to new claim types. The next
step could be the use of visualization and modeling to access claims risk while
implementing machine learning to detect fraudulent claims.
Given the importance of customer
experience has shifted from the service and marketing functions to a more
public domain due to the proliferation of digital channels, insurers would have
to go that extra mile to ensure a hassle-free claims experience. This
"moment of truth" for the industry is an ideal opportunity to
strengthen customer loyalty and enhance retention by using the best of
technology innovations to build and manage trust.
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