ARTIFICIAL INTELLIGENCE

IN
INSURANCE
Team Members
Sharmistha Halder PGP/22/281
Ashwini Kumar PGP/22/269
Dibyanshu Kumar PGP/22/348
Agnik Dutta PGP/22/003
Rajvi Desai PGP/22/
Najla Ajmal PGP/22/
Industry Overview Business Model Impact Specific Instances Financial Viability

Digital Mode
Summary

• India trends to have a double digit growth of 13% and the current situation,
only 13.1 % of the market is tapped
• Insurance industry tends to run via partnership mode which includes Agents,
Banks collaboration, Cooperative Society, Digital Mode
• Preferably buying channel is also through digital mode but there huge
influence of Agents
• Consumers prefer to buy insurance to get tax rebate
• Recently microinsurance is trendy and has huge potential to untap
• Most of valuable source of information for the consumers is the Digital Mode
which includes online aggregator, company website, financial blogging, etc.

Preferable Buying Channel

 Industry Overview Business Model Impact Specific Instances Financial Viability

Stage Challenges Useful Techniques Required Capability

Content
H Traditionalists
Customer Target Difficulty in comprehension of Management;
Preference
Simplified video and documents in regional language
Presales products, benefits and features Multilingual app and
for human
contact Transitionlists website
Lack of trust and misfitment issues Persona Building Analytics
Native Digitals
L Lengthy Process for complaints and
Use of Chatbots
querry handling
L H
Adoption of digital technologies Service Period AI for personalised
Timely Renewal of Process Payment through UPI invite
communication
Irrelevant Communication Persona Building Analytics
Integrated data
Long waiting period Dedicated customer relationship manager system eliminating
duplication of efforts
Insurance Claim Workflow based
Paper Based Service Digitisation
online self service
Customer Account
Transparency Dedicated customer relationship manager
Management
Analytics
Difficulty in prediction Better Alumni Plans and Offers
Customer Churn Data Warehousing
 Industry Overview Business Model Impact Specific Instances Financial Viability

Challenges Technologies: Benefits, Ecosystem, Challenges

Legacy Ecosystem Technology Benefits
• Lack of Electronic Health Record makes across
Country
Technology/Parameters Company Customer
• Collection of data only through medical test or Cost Saving
self-disclosure by customer
RPA Error reduction Convinience and speed
Disruption of Existing Business Model
Cloud Integration of Data Seamless Experience
• Technology should be benefitting for customers
but it might get worse when this tries to Analytics Prediction Accuracy Relevant product offering
penalise the customer
IoT Integration of behaviourial attributes Ecosystem of services
Return on Investment
AI Risk analysis, Pricing, Data integration Relevant product offering
• Apart from setup-cost & operational expenses,
cost like specialized equipment, data digitization Social Media Ease in customer engagement Ease in information availability
& cleansing, subject matter experts, analytics/AI
software, skilled manpower for running
Block Chain Ease in Data storage Data Privacy
operations and security compliances
Technology/Platform E commerce Health Tech InsurTech FinTech
Consumer Adoption
Digital Payment
• High cost of health/fitness monitoring devices,
home monitoring devices, telematics, etc. Sales Platform
• Building consumer trust in IoT will take time Persona
Interoperability Analytics
• Data Standardization is a major challenge RPA
among all technology & regulatory departments IoT
• Hardware standards, security standards,
installation practices, power management & Cloud
protection standards, etc. is also required Blockchain
 Industry Overview Business Model Impact Specific Instances Financial Viability

Customer Service Delivery Channels

• App Designed for marketplace get
Website/Portal Mobile Apps E mail/SMS Social Media Aggregators price quote
• AI Bots enhance the customer
experience more interactive
Impact of Digitalization

Operational Services • Big Data Analytics, RPA, etc. to

improve efficiency & reduce time
New Business and Claim
Administration Rating Reinsurance • Use of RPA for rating & provide
Underwriting Management price estimate

Support Service • AI would help in billing & payments

• Estimate risk using AI tools, API is
Risk HR Financial Billing and Content required to connect with different
Management Management Management Payments Management govt portals to access data &
provide personalized product
offering, detecting fraud, etc.
Data Data Supply Chain Value added • Big Data & data processing through
Reporting
Management Analytics Management service blockchain will provide structure
data for reporting & Data Analytics
Service orchestration and integration
Payment gateway integration /
Business Process Enterprise IOT/M2M platform
aggregator/social media API
• Integration of Enterprise Bus Service
Management Service Bus integration & Payment Gateway to ease
integration
redundancy & improve efficiency
• OTP/ Biometric Authentication to
Service orchestration and integration provide secure systems
• Blockchain can be used to save
Security System and database Network DC and DR Cloud hosting information which is easy to access
management management Management infrastructure (PaaS , SaaS) & stored in ledger format
 Industry Overview Business Model Impact Specific Instances Financial Viability

Way to Transform Insurance Experience

•Deploy huge workforce & time

Customer Sales &
•Data such as customer-specific
spent to segregate valid &
fraud claims
Servicing habits, spending trends, family Marketing • Personalized plans
background, etc. is acquired
•Claims data analyzed further from online & traditional •Collaborate with market to target customer
to ensure process efficiency & •Available digitized data should be using data provided
distribution channels agency, sales agency,
build inbuilt system checks to leveraged by the organization to to cater specific
•Data defines customer advertising agency, etc. by
accurately identify valid claims service customers better & needs
acquisition strategy considering budget
provide a smooth user experience,
spending
thus improving customer
Claim retention & new customer Distribution •Use available data to target
relevant customer
Product &
acquisition
Processing Channel Pricing
 Industry Overview Business Model Impact Specific Instances Financial Viability

Application by partnering with E-Commerce

Bought Laptop Bag

Buys 1 double
bedsheet & single
Total Purchase of 50k in
bedsheet Preliminary Persona
last 12 months

Couples with kids

• Spending 50k over 12 months
• Probably 1 primary earner
Buys school Buys Ladies, Gents &
stationary
Behaviour
Girl’s clothes
• Family centred
• Can analyse dietary habits

Collectively using such data points, can help us to generate unique insights & Journey
provide individual personas which are more accurate and can be used for • May provide life & disability cover
precision marketing
 Industry Overview Business Model Impact Specific Instances Financial Viability

Behavioral Pricing & Fraud Management System

Traditional Method
IDENTIFY
Suspicious claims are identified through referrals,
rules, classification & descriptive analysis Data is combined
in logical manner
for easy analysis As per
ANALYSE Structured Data is taken scores
Analyse the suspicious claims through deep from the data repository decisions
includes internal data are being
diving, statics, processes, etc.
taken.
High risk
MODEL cases are
Developed a heuristic model for fraudulent rejected
scenario for future cases or send to
Analytic
engine will through
Method Using AI use AI further
investigat
techniques
•Identify patterns between Actors & Behaviour to analyse ion as per
•Leverage Machine Learning Techniques the data scores
Identify

•Leverage business knowledge, industry trends & advanced ML

techniques
Analyse •Analyse patterns which looks anomalies
Case Management
System uses different
•Prioritise & investigate events case & algorithm,
Investigate •Seeks additional information & Resolve alerts
which then takes wise
Alternate Data is processed decision. Scores are
Alternate Data from
& structured using ML provided in each
•Develop, Push scores & Alerts into Case Management Systems external sources taken &
parameter w.r.t to
•Optimized alerts based on economics value & business send through Big Data
Alert constraints, etc.
requirement
 Industry Overview Business Model Impact Specific Instances Financial Viability

Financial Modelling
Expenditure One-time 2021 2022 2023
App Development & Maintanance 2,65,00,000.00 53,00,000.00 58,30,000.00 64,13,000.00
Data Analytics 15,00,000.00 8,00,000.00 8,80,000.00 9,68,000.00
Protal Video 2,00,000.00
Total Expenditure (INR) 2,82,00,000.00 61,00,000.00 67,10,000.00 73,81,000.00

Total Expenditure(5 Years) 4,83,91,000.00 Cost Line Cost

Instruction Video 2,00,000

Cost Line Cost

Total Cost 2,00,000
App Development & Maintenance 50,00,000
Platform-wise Cost 2,10,00,000
Quality Control 5,00,000
Total Cost 2,65,00,000

Yearly Maintenance Cost 53,00,000

Yearly Growth Rate 10%
Microsoft Excel
Year One-time 2021 2022 2023 Worksheet
Costs 2,65,00,000 53,00,000 58,30,000 64,13,000

Total Cost (INR) 4,40,43,000

Thank You