Improving the
insurance experience
Why AI
in Insurance
Claims and
Underwriting?
Introduction
With today’s rapidly maturing technologies and
the ability to tap into ever-increasing data, AI has
emerged as the transformative technology and
critical dierentiator in the insurance industry,
especially when applied in tandem with humans.
To further identify opportunities around AI for
insurers, Accenture conducted research to better
understand both how insurance customers and
employees can benefit from the maturity of AI in
Claims and Underwriting.
Why AI in Insurance Claims and Underwriting?2
Survey methodology
We conducted surveys to gain 3 perspectives on
insurance industry pain points and opportunities
to improve through use of AI:
6,784
home and auto insurance customers,
across 25 countries, who have
made a claim in the past 2 years.
128
insurance claims executives
in 13 countries.
434
US-based underwriters from entry-level
to executive/senior management, including
members of The Institutes supplemented with
a sample list from Risk & Insurance Group.
Unless otherwise cited, all data are from
primary research conducted by Accenture.
ese surveys, in conjunction with market
trends, point to three areas carriers should
consider as they take their next steps in the
AI journey.
AI is transformative in the enablement of improved
customer interactions, increased eiciency/automation,
and decision eectiveness.
AI must be applied responsibly and in tandem with
humans to meet ethical guidelines, airm regulatory
decisions, and enable the insurance workforce of
the future.
As the economics around AI improve, the value delivered
through AI solutions indicate that now is the time to invest
in AI-led transformation.
In this report, we explore these considerations in detail and
reveal why AI is the transformative technology in insurance
claims and underwriting.
01
02
03
Why AI in Insurance Claims and Underwriting?3
As AI matures, insurers can leverage the
technology to improve customer relationships
through enhanced interactions, while
realizing gains in both process eciency
and decision eectiveness.
Enhanced customer interactions
Coverage, price, and service experience are the main
factors consumers say they consider when choosing or
remaining with an insurance company. Yet in today’s highly
commoditized market, many customers who choose an
insurer or policy primarily on price may not understand
what is covered or what to expect in the claims process.
This often results in a dissatisfied claimant.
Our research found that a third of all claimants say they
were not fully satisfied with their most recent claims
experience. While it may seem a small percentage of the
total insurance customer base, these claimants represent
up to $170 billion in renewal premium over the next
five years.
A clear pain point is speed of settlement. It is the factor that
causes the most discontent among dissatisfied claimants.
AI solutions can improve settlement time by enabling
digital and self-service claims processing that dramatically
enhance customer experience and accelerate processing.
In fact, many leading insurers have invested heavily into this
aspect, creating omni-channel environments that leverage
the use of chat bots, rich text messaging, guided scripting
for agents, among other AI driven methods, to address
these gaps in customer interactions today.
4
AI is transformative for
insurance customers
and carriers
Why AI in Insurance Claims and Underwriting?
Case study
Compensa Poland, part of the Vienna Insurance
Group (VIG), has enhanced its customer experience
with a self-service claims-handling solution. It uses
advanced data analytics to automatically process
claims
from first notice of loss (FNOL) through to
smart claims segmentation, routing, assessment,
settlement and adjusting the claims reserve, which
results in more accurate payouts and high customer
satisfaction. The AI-based system led to as much
as a 73% increase in claims process cost eiciency,
and 50% of customers who used the self-liquidation
application said they would recommend it to a
friend or family member.
1
1
Automatic payment in a digital claims process
Q. How satised were you with how the
insurance company/agent handled the claim?
% of policyholders not fully satisfied by speed of settlement
<48 hours
48 hours - 1 week
1 - 4 weeks
1-2 months
3-6 months
>6 months
17%
25%
31%
37%
39%
39%
Not satisfied A little satisfied Somewhat satisfied
5 Why AI in Insurance Claims and Underwriting?
More eective decision-making
Underwriters acknowledge that AI-driven risk appetite and
risk scoring have helped improve performance in terms of
risk selection and pricing accuracy.
In claims, AI can provide insights that help insurance
companies prevent leakage. For example, in the case of
Compensa Poland, while the goal was to improve customer
satisfaction, the implementation of the AI-based system
also led to a 10% improvement in claims accuracy.
2
6
Daido Life Insurance in Japan is a formidable
underwriting use case for AI. The company has built
a powerful AI prediction model that visualizes the
decision-making process and enables underwriters
to perform assessments while checking the AI’s
prediction results and cautionary points. This model
improves back-oice eiciency, while solving the AI
black box problem through human verification of
AI predictions. Daido Life will continue to refine the
model by accumulating underwriting results from AI
predictions and human judgment.
3
3
An artificial intelligence (AI)-based medical underwriting solution
Increased automation and eciency
Our underwriting employee survey found that up to 40% of
underwriters’ time is spent on non-core and administrative
activities. We estimate that this represents an industry-wide
eiciency loss of up to $160 billion over the next five years.
Incorporating AI and automation into the underwriting
workflow is a prime opportunity to reduce time spent on
administrative tasks, manual processes, and redundant data
inputs. An intelligent UW solution (submission ingestion, data
enrichment, triage, appetite fit & propensity to bind scoring)
allows underwriters to focus their time on risk evaluations of
submissions most likely to drive (profitable) bound premium.
In Claims, typically approximately 40% of inbound call volume
are comprised of basic claims status checks. An AI-driven,
outbound status message delivers improved experience and
eiciency gains of reduced inbound calls.
Case study
2
Automatic payment in a digital claims process
Why AI in Insurance Claims and Underwriting?
Case study
Leading insurance companies will develop
AI strategies with careful aention to ethics,
regulation and responsible business. In
the face of workforce challenges across the
insurance industry, AI will also be essential
to the insurance workforce of the future.
Ethical and regulatory implications
Carriers need to be aware of the ethical and regulatory
implications of using AI solutions. Humans must test AI
solutions to avoid coded biases that can unintentionally
produce decision results that propagate historic racial,
gender, and other socioeconomic disparities. An insurer’s
data scientists must take care when selecting taxonomies
and training the AI on how to use data.
Loop, a US-based insurtech, strives to provide
more equitable auto insurance options by basing
its rates on what it considers to be more relevant
metrics than those used by incumbent insurers.
Rather than customer attribute data like credit
score and marital status, Loop relies more on
driver behavior and location data, utilizing AI to
set personalized insurance pricing.
4
4
Austin insurance tech startup Loop raises funding, gets set to launch
Why AI in insurance Claims and Underwriting?7
AI must be applied
responsibly and in
tandem with humans
7 Why AI in Insurance Claims and Underwriting?
Explainabili
With a rules-based system, insurers can explain the
logic of a decision. However, with AI, there must be
humans who work in conjunction with AI solutions
and who are empowered to modify an AI-generated
decision as needed.
Future workforce enablement
With the aging insurance workforce, especially in Life
Insurance and Property underwriting, the workforce
will see dramatic change in the next 5 to 10 years.
The US Bureau of Labor Statistics estimates 50% of
the insurance workforce will be retired in 15 years,
leaving more than 400,000 open positions.
5
Replacing
them person-for-person isn’t viable. AI solutions must
supplement the workforce and help transform the
insurance operating model.
5
US Bureau of Labor Statistics Occupational Outlook Handbook
In an industry where feedback from employees often reflects a desire to work on things they
care about, AI frees up humans to do exactly that. Insurers can put AI solutions to work on tasks
that are tedious to humans, or which machines can do faster and more accurately, while skilling
humans for work that requires emotional intelligence and personal judgement.
8
Edelweiss Tokio Life has partnered with Element
AI to drive an AI program that balances creating
value today with building capabilities for tomorrow.
Empowering employees to work smarter with AI
by building an organization’s literacy and trust to
work with AI is at the center of the initiative. It
is also establishing a framework for trustworthy,
explainable and responsible AI for now and
the future.
6
6
Edelweiss Tokio Life partners with Element AI for AI transformation journey
Case study
Why AI in Insurance Claims and Underwriting?
Why AI in insurance claims and underwriting?9
As the economics around AI improve,
the value delivered through AI solutions
indicate that now is the time to invest in
AI-led insurance transformation.
Aordabili and value of AI
The costs of implementing AI are falling dramatically,
making it more viable to adopt it at scale. Consider, for
example, that the cost to train an image classifier like
ResNet-50 on a public cloud platform dropped from
approximately $1,000 to $10 between 2017 and 2019.
7
AI investments can also be leveraged across insurance
functions, creating gains across the value chain
(e.g., Claims, policy service, and contact centers).
7
ARK Invest: The Cost of AI Training is Improving at 50x the Speed of Moore’s Law:
Why It’s Still Early Days for AI
Investment in AI is accretive to market
and investor condence
Investors have recognized the industry-changing potential
of AI. Insurtechs that leverage AI, machine learning,
machine vision, natural language processing and virtual
assistants/bots as their primary technology solution
raised 20% more investment each year (CAGR) from 2015
to 2020. In 2021, there were at least five instances of VC
funding each worth more than $100 million into AI-led
insurtechs. This indicates the potential for insurers to
boost market and investor confidence through strategic
investment in AI.
Now is the time to
adopt AI at scale
9 Why AI in Insurance Claims and Underwriting?
10
80%
say these
technologies
can bring
more value
65%
say they plan to
invest more than
$10 million into AI
Investment in AI-led insurance
transformation is ramping up
Across all industries, including insurance, AI
ranked consistently as the top game-changing
technology in Gartner’s CIO surveys over the
last three years (2019 to 2021). Insurers are
starting to see the value of AI and adoption is
set to accelerate. While less than half of claims
executives (44%) say their organizations are
advanced in use of automation, AI and machine
learning-based data analytics, 80% say these
technologies can bring more value, and 65% say
they plan to invest more than $10 million into AI
in the next three years.
Why AI in Insurance Claims and Underwriting?
AI is no longer a technology of the future, but an established
presence in our everyday lives. Many insurance innovators
are already putting it to work to deliver better customer
experiences and empower their workforces in parts of their
business. As humans and AI collaborate ever more closely
in insurance, companies will be able to reshape how they
operate, becoming more eicient, fluid and adaptive. It is
those that are already moving to leverage AI to create gains
across their functions and value chains that will be able to
create sustained competitive advantage in the future.
Conclusion
11 Why AI in Insurance Claims and Underwriting?
About Accenture Research
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Authors
Andrea Lorenzoni
Managing Director, Insurance
Michael Reilly
Management Consulting Senior Principal
Contributors
André Schlieker - Global Insurance Research Lead
Juan Demarchi - Insurance Research Manager
www.accenture.com/insurance