Agile and Efficient Business Outcomes with Artificial Intelligence

wipro.com

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Adoption of AI in insurance for enhanced efficiencies and agile decision making

Challenges faced by insurance industry and howAI can help?

For decades, the insurance

industry has worked with

descriptive analysis and risk

assessment. However, with the

availability of big data from

historical processes, IoT and social

media, insurance companies have

the opportunity to take real time

actions based on machine learning

and prescriptive analytics.

Advances in artificial intelligence

(AI) are helping insurers enhance

efficiencies by improving cost

structures and leveraging

automation. The technology has

moved from being a simple rules

based process automating tool to

enabling advanced AI driven

decision making through

underwriting and thinking systems.

Today’s hyper connected

customers expect insurance

services that are at par with those

offered by retail and banking

industries. Changes in digital

technologies and evolving market

dynamics add to the heightened

level of disruption. In addition, as

part of a highly regulated industry,

insurers are required to maintain

humongous amounts of data on

their siloed legacy systems. All of

these factors are compelling

insurers to look for innovative

options in order to deliver high

service levels.

The good news is insurance

companies can leverage AI

solutions and platforms to

address these challenges and

transform into highly efficient

customer centric organizations

(see Figure 1).

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Figure 1: How AI Helps Tackle Industry Challenges

• Virtual assistant uses 3600 customer view, natural language processing and prescriptive analytics to provide personalized customer service

• Increase efficiencies and accuracy through usage of robotics and automation in business processes

• Robots with advance learning capabilities can present a single desktop experience to customers and CSRs

• Machine vision, deep learning and autonomics tech can be combined for scenario analysis and decisioning

• Knowledge virtualization from multiple data sources and IOT data used to provide targeted risk analysis and personalized coverage

AI SolutionsChallenges

Customer’s high benchmarks

of service:

Increasing regulation

& compliance:

Technology advancement

in insurance:

Enterprise architecture

constrained by legacy systems

Complex business processes &

decision making

AI systems are making a perceptible

difference across the insurance

functions. AI can deliver benefits

including:

10-15% improvements in

underwriting

30-35% efficiency in new

business processing and policy

servicing

Claims FNOL process

improvement by approximately

20-25%

Claims assessment

improvement of 10-15%

Approximately 2-4%

improvement in claims payout

with fraud prediction

Wipro HOLMES™ platform based

on cognitive intelligence can

analyze and use the available

humongous data to help insurers

take the customer servicing,

underwriting decision, scenario

analysis, and claims assessment to

the next level.

The Wipro HOLMES™ (Heuristic

and Ontology based Learning

Machine and Experiential System)

platform is a cognitive computing

software. It brings together

comprehensive sets of capabilities

such as language understanding,

vision, learning, prediction,

reasoning, and inferences to

enable businesses to build and

deploy cognitive solutions in the

digital age.

Develop five kinds of AI

applications with Wipro

HOLMESTM:

Digital virtual agents (ngGenie)

Self-learning and predictive

systems

Digital virtual agents (ngGenie)

Visual computing applications

and

Knowledge virtualization and

diagnostics

Some of the key features of

HOLMES™ include:

Enables processing of large

volumes of structured and

unstructured data in different

formats, and analyzes and

understands the content after

they are processed.

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Wipro HOLMES™: A game changing platform for AI driven transformation

Through its smart AI

capabilities, Wipro HOLMES™

can save 25 to 40% of costs

for Fortune 1,000 companies.

Interacts with users and asks

questions through natural

language processing (NLP).

NLP and machine learning are

used as part of chat service to

automate the call center service

operations by answering users’

questions. The output is

machine learning-based and it

continues to learn and

improve the answers over a

period of time by updating

its knowledge

Helps companies

hyper-automate processes,

redefine operations, and

re-imagine customer

journeys. Through its platform

HOLMES Mimictron, the

solution enables complex and

cognitive process automation

that cannot be achieved

through a traditional RPA tool.

Facilitates deployment on

private as well as public

Cloud platforms, addressing

individual business needs for

data confidentiality and

security.

Adapts rapidly to

technological changes due

to its open-source based

design.

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Naturally

Interactive

Knowledge

Representation

Algorithmic

IntelligenceReasoningLearning

Natural Language

to application

services mapping

Knowledge

extraction from

unstructured

Information

Dialogue based

interactions

Semantic mapping

& automated

ontology

construction

Stochastic

computations –

probability,

randomness, fuzzy

logic

Automated

hypothesis

generation and

validation

Applied machine

learning, data and

features based

Common sense

reasoning –

Wordnet, OpenCyc,

Yago

Interactive machine

learning via

observation and

monitoring

Knowledge graph

traversal & deep

inference -

knowledge mining

Natural Language

Generation

Blended Reality

Automated

knowledge model

construction

Knowledge

enhancement

through

annotations

Knowledge

enhancement

through

annotations

Continuous and

adaptive learning

Ontology based

learning

Some of the key attributes of HOLMES™ Artificial Intelligence platform are showcased in Figure 2. A number of function BOTs work in tandem with the virtual assistant (ngGenie) to perform human equivalent actions for the business.

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BOTS are software programs deployed as a service for IT and business processes

Functional BOTS

Building new BOTS

• Classifier BOT

• Summarization BOT

• Do it yourself BOT

• Task Assignment BOT

• Resolver BOT

• Service Ticket BOT

• Curator BOT

• Duplicate Detection BOT

• Diagnosis BOTS

• Text Analytics BOT

• Data Extraction BOT

• Image Processing BOT

• Investigation BOT

• Outlier BOT

• Concept Extractor BOT

• Research BOT

Data Curation

Assemble BOTS

Train & Integrate Algorithms

Deploy BOTS

Verify BOTS

Monitor

Wipro HOLMES™ platform, based

on cognitive intelligence, can

analyze humongous data

volumes to help insurers take

customer servicing, underwriting

decisioning, scenario analysis,

and claims assessment to the next

level. The platform enhances

customer engagement with its

ability to learn from the information

present in policy documents, blogs,

call center logs, underwriter or claim

examiners’ comments, and interact

with the customers using NLP

capabilities. It can provide

personalized customer servicing at

different touch points (chats, calls,

CSR, emails) while helping customers

plan for their future by

recommending the right products,

features, coverage limit, etc. Figure 3

depicts the benefits provided by

HOLMES™ across the insurance life

cycle and Figure 4 provides an

illustration of how HOLMES™ delivers

enhanced customer experience,

underwriter effectiveness and

improved process efficiencies in

the insurance sales process.

How Wipro HOLMES™ helpsthe insurance industry

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Wipro Holmes eKYC (Cross sell & Upsell using Single Customer View)

Figure 3: Advantages of using HOLMES™ across the insurance life cycle

Wipro Holmes eKYC (identify fraudulent customers, content search using ontology)

Wipro Holmes - Robo advice (Product recommendation & UW with social media data

Wipro Holmes (Call center-Service desk automation)

ngGenie (Voice enabled virtual assistant - (Natural Language Assistance, Contextual and Personalized Recommendation)

Wipro Holmes eKYC (Knowledge extraction & fraud identification)

Wipro Holmes (Predictive Analysis & Fraud)

Wipro Sight™ (Drone)

Property / Crop damage assessment and Risk engineering report

Sales

&

Distribution

New Business

&

Underwriting

Policy

Servicing

Claims

&

Payout

BI

&

Reporting

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Figure 4: Illustration of how HOLMESTM can help improve processes

Customer goes to insurer’s website(POS) or calls the call center

Voice enabled virtual assistant

(ngGenie) responds

automatically to call center

calls, or provides the NLP

based chat assistance on the

website using Wipro Holmes.

It asks a few basic questions on customer’s needs and suggests the

right product, policy limits etc. using Knowledge Extractor Bots It

helps customer with the goal based insurance planning

The customer wants to generate quotation

from the insurer website, ngGenie helps

the customer with any questions related

to quotation screens/ fields

During the quotation/policy application stage,

if the policy gets referred to the U/W, it helps the

U/W with eKYC using Knowledge Extractor Bot,

Duplicate Detection Bot & Investigation Bot

Once the policy is issued, the bot generates the covering letter,

policy documents by extracting the right information from required

applications. It sends the document to the dispatch center.

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04

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Policy SalesPoint of Sales Enquiry

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Wipro partners with global

insurance companies to transform

their entire insurance value chain

using the Wipro HOLMES™

platform.

Business challenge:A leading life Insurance company’s

policy validation process was

manually driven by a team of 15 people. This team cross checked

the details provided in the contract

proposal forms and the supporting

documents available in the

documents repository portal

against the information in the

mainframe based policy application

system. Pass, error and detailed

error reports were created

manually. The team received over

4,000 documents each day, which

were manually validated within

three days (on average). The

manual process was prone to a high

degree of inaccuracy, compelling

the client to conduct a separate

audit check on approximately 20% of policies.

Solution:The client leveraged cognitive

intelligence through Wipro’s AI

platform HOLMES™. BOTS

extracted data from the contract

proposal forms and supportive

documents, and verified it against

the system generated details. They

also generated pass, error and

detailed error reports which were

sent to the agents for further

processing. HOLMES™ combined

OCR, image processing, machine

learning and computer vision

technologies to completely

automate this process.

Business benefit: Automating the customer data

validation process with the help of

HOLMES™ led to 80-85% accuracy and improved turn-around time.

Currently, over 4,000 documents

are processed with in a matter of six hours (representing an

efficiency gain of 75%), with just

one or two people assigned to the

task of exception handling.

Wipro HOLMES™: Success stories

Application - proposal forms and supportive documents

are uploaded

Main frame database for policies

Data Extraction-

Bot will extract the data from proposal form.

Data Verification-

Verify extracted data against spool files generated

from system

Agent will confirm for false positive or false negative and

false negative cases will be send to bank for reprocessing

EQC automation for a leading life insurer

Data in the Home Office

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02

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Bot will generate reports –

Pass Report will be transferred to vendor for policy printing

Error report will be given to agent for further processing

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07VENDOR

Figure 5: AI Credential - 75% efficiency gain achieved in EQC process for a leading life insurer

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