Life Insurance industry has been witnessing low persistency (a policy's ability to be active and sustained premium payment)rate hence the proactive need for customer retention and maximizing renewal premium collection and need for monitoring the performance of intermediaries and agents could gain immense value from deriving highly usable recommendations. The need for such inferences, importantly in a timely basis can't be more important than now as the rightful and the revised guidelines by the regulator ensures the need to minimize wrong selling, increased persistency and performance of all the stakeholders in Life Insurance to make business a flourishing one. How did the evolving need of the industry coupled with constant change in market and competitive landscape was married and focused approaches were espoused through with tangible benefits on Customer Value Retention and Maximization & agent's performance improvement were met. What are the recommendations from Sameer to individuals & enterprises who intend to devise their Analytical Vision for their respective organization, what are the areas to be considered before embarking such a journey .

1. make connections • share ideas • be inspired
India’s Largest Analytics Forum
Customer Management
Sameer Seksaria
Senior Vice President – Business Retention and Sales Support
Reliance Life Insurance Co. Ltd
Copyright © 2011, SAS Institute Inc. All rights reserved.

2. Content…
Industry Summary
- An Outline
- The Journey
- The Developments
- The Future Changes Expected
- The Opportunity
Reliance Life Insurance – An Organization Profile
Challenges in Life Insurance
Role of Data Analytics
Customer Management in Insurance and our Approach
Persistency – Our Approach and the Results
Copyright © 2011, SAS Institute Inc. All rights reserved.

3. Industry Summary – An Outline
Representing Life Insurance Industry
• Life Insurance Industry regulated by the Insurance Regulatory and
Development Authority (IRDA)
• Life Insurance Industry opened up for Private players in the year 2000
• 26% FDI allowed in Life Insurance Companies
• Currently 24 Life Insurance companies operating in India (including LIC)
• Total Premium Collected by all life insurance companies during Apr11-
Dec11 stands at about 72,000 Cr by issuing 2.7 Cr policies
• Private Insurers market share in terms of premium stands at 28%
• Penetration of the insurance industry, premium as percentage of the
country's GDP, has improved from 2.3 per cent in 2001 to 5.2 per cent in
2011.
Copyright © 2011, SAS Institute Inc. All rights reserved.

4. Industry Summary – The Journey…
India life sector performance review
Nascent Stage: High Growth Stage: Growth Rationalization Stage:
Stable Growth
Build-out Phase Focus on market share Focus on breakeven Stage
10-20% p.a.
PVT LIC
394
384
premiums ( bn)
New business
338
342
195
864
709
103 559 592
56 530
3 10 24
196 207 256
160 170
2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011
– 102% -18% 6% 22% 24% 118% 6% -11% 34% 22%
LIC
– 4277% 257% 155% 128% 84% 90% 74% 1% 12% 3%
Private
– 105% -15% 15% 35% 37% 110% 23% -6% 25% 15%
Sector
4
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5. Industry Summary – The Developments
Recent changes Impact in 2011 Impact in 2012 onwards
ULIPs now more customer friendly
Charges on ULIPs down
Drop in distributor commission More balanced mix
Cap on surrender charges
Short-term impact on top line Improving persistency levels
Products Longer lock-in period
Expense Management critical Time-to-market critical
Short-term and long-term impact
Higher life cover amounts per policy
Pension product effectively Operating efficiency is key
withdrawn(1)
Lower upfront commissions & Dominance of variable / low
Revamp of selling practices
Incentives cost channels
Distribution Commissions to be disclosed
Re-design of Agency model Agency productivity a
Stringent guidelines on Referral
differentiator
Slowdown in last 2 years as against
More focus on Traditional
Structure / initial years of high growth Near-term lag
(Protection) products
Growth LIC likely to grow higher than LIC gained market share
Distributor force to shrink
private players in the interim
Note: (1) Recent changes introduced guarantees on pension policies
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5

6. Industry Summary – Future Changes Expected
Likely timing of
Regulation Beneficial changes effected
Maximum 26% currently
Foreign Direct
Likely to move from 26% to 49% Medium
Investment
Requires parliamentary approval
No listed companies currently
IPO norms Short
IPO norms already approved
Single tie regime currently
Bancassurance Medium
Multi tie regime proposed
Life insurance products currently enjoy EEE status(1)
Tax benefits status Proposal to move to EET(2) status by introducing taxation at maturity (for Short
endowments and ULIPs)
Current tax rate of 12.5%
Tax(3) Medium
Potential increase in tax rate to 30% proposed
Beneficial Short - < 6mths Medium - 6mths to 2 yrs
(1) EEE = Exempt Exempt Exempt status. Amount invested or contributed would be 'Exempt', the returns or the interest generated would be 'Exempt' and lastly the final maturity amount would
also be 'Exempt' from tax
(2) EET = Exempt Exempt Tax status - Amount invested or contributed would be 'Exempt', the returns or interest would be 'Exempt', but the final maturity amount would be 'Taxed‘
(3) Potential implementation of DTC legislation
Source: News articles, expert discussions
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6

7. Industry Summary – The Opportunity
Opportunity
Structural positives
India growth story
Favourable demographics
Rising income levels
High savings rate
Under penetration
Insurance penetration in India is still very low(1)
Protection levels are low compared to developed markets
Distribution
Introduction of multi tie-up for banks
Improve agency professionalism and productivity
With increasing internet penetration, Online channels will grow
Product
Push for higher protection element in products
ULIPs becomes more customer friendly
Untapped profitable market segments
Huge potential – rural and health insurance
Micro-insurance through MFIs, regional rural banks and co-operative banks
Note: (1) On a per capita basis
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7

8. Reliance Life Insurance – An Organization Profile
Representing Reliance Life Insurance Co Ltd (RLIC)
• RLIC is an associate company of Reliance Capital Ltd., a part of Reliance
Group.
• Reliance Capital is one of India’s leading private sector financial services
companies, and ranks among the top 3 private sector financial services and
banking companies, in terms of net worth.
• RLIC partnered with Nippon Life Insurance, also called Nissay. Nissay is
Japan's largest private life insurer with revenues of about Rs 350,000 Cr
(US$ 70 Billion) and profits of over Rs 12,000 Cr (US$ 2.5 billion).
• Nissay is largest private life insurer in Asia and It is ranked 81st in Global
Fortune 500 firms in 2011
• RLIC has large branch network with 1200+ branches across India with 1.9
Lakhs of Individual Agents working with us
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9. Continued Strong Growth of RLIC
Initial Entry(1) Present
Key Performance Indicators
FY 2005-06 FY 2010-11
Customer Base
( Issued Policies) 0.1 m 7.5 m
Market Position in
No of Policies (Pvt) 12 1
New Business Premium
(Rs bn) 2 30
Market Position in New
Business Premium (Pvt) 11 5
Total Premium ( Rs bn) 2 66
Assets under Management
( Rs bn) 4 179
No. of Branches 153 1,247
Note: (1) Acquired AMP Sanmar in Oct 2005. Name changed to Reliance Life in Jan 2006
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9

10. Challenges in the Insurance Sector
Challenges
Sector & Company profitability Product & Customer Segmentation Analysis
Near-term dip in business profitability
Attrition/Retention Prediction
Improving product mix, expense and persistency
Gap Analysis in Product Mix
management to offset profitability pressures
Customer Service & Persistency
Low persistency at private players
Attrition/Retention Prediction & Win-back Strategies
Effective communication
Customer expectation for differential treatment Incentive & Commission Analysis
Limited Service differentiation exist in Insurance industry Customer Satisfaction Analysis
for customers and distributors
Large number of “Orphaned policies” with little service
support
Distribution Agent & Sales Force recruitment
Improving profitability and productivity of channels Agent Productivity Analysis
Distributor attrition leads to Cross-sell and Customer Satisfaction Analysis
Low customer satisfaction Customer Agent Association Analysis
Low Cross-sell / Up-sell
Sales Force Attrition Analysis
Low persistency
Difficulty in attracting talent for distribution
Competition
Competitor New Product Launch Impact Analysis
Increasing intensity of competition for new business and
Bench-Marking & Business Performance Analysis
distribution channel acquisition
Marketing Mix Analytics
Potential new entrants
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10

11. Role of Data Analytics in Insurance Industry
• Customer Acquisition
• Customer Management •Segmented sales approach
•Attrition/Retention Prediction • Campaign Management
•Lifetime Value Analytics •Marketing Analysis
•Customer Segmentation Analysis
•Customer Satisfaction Analysis • Channel Management
•Win-back Strategies • Agent & Sales Force recruitment
•Cross-sell / Up-sell •Productivity & Success Factors
• Product Mix Gaps • Agent / SM Attrition
•Product Identification Customer Customer •Incentive / Commission Analysis
•Channel Profitability
Management Acquisition
Policy Underwriting • Risk Management
• Claims Management
• Fraud Identification Models
Servicing & & Risk • Same Client Multiple policies
• Claims Estimation Analysis Claims Management analysis
• Portfolio risk management
• Servicing Channel • Risk Assessment and pricing
• Automation Opportunity Assessment • Selective Health Underwriting
• Performance Analysis
• Business Performance Analysis
• Premium Trend Analysis
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12. Customer Management in Insurance
• The business of insurance is to bring together persons with common insurance
interests (a) sharing the same risks (b) collect the share or contribution (called
premium) from all of them, and (c) pay out compensations (called claims) to those
who suffer from the risks. Hence, It is important that
•Insurer chooses right customers, Agents and other sales forces
• Insurer launches right product mix
• Also, Life Insurance is a long term contract, hence servicing the customer and
managing the data for a longer period is very important
Life cycle of a life insurance policy
Policy Servicing period
Pre - Sales Customer
Maturity
Acquisition
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13. Changing Customer Expectations:
Life Insurance Examples
Pre- Privatization (1 State Company) Post Privatization (24 Companies)
Banks, Brokers, Internet, Telemarketing, phone etc
Purchase option only through Advisor
and far wider range of products
Basic Medical examinations
Efforts on to make Medicals a good experience:
mobile labs, home visits
Generally no correspondence from either company
or agent except for premium reminder
Mailers from companies on products &
services, greeting cards on birthdays, new year
Payment in the Company Branch or to Advisor
etc, reminders on premium, Phone calls from call
centers, SMS, Emails, Welcome Calls
Not much expectation except that Policy Document
is received
Payment at bank branches, SI on Credit
Cards, Direct Debits, ECS, Drop
Boxes, Internet, Kiosks, Pick Up Runners etc
Policy Document to be received within 7 – 15
days, Premium Notice received, Lapse warning in
advance, quick Claim payment, more awareness on
Free Look cancellation, Surrender/ withdrawals
Copyright © 2011, SAS Institute Inc. All rights reserved.

14. Our Approach to Customer Management
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15. Persistency Management – Our Approach
Persistency drivers Actions Taken
Customer education campaigns
Market related
Re-instatement campaigns & Interest waivers
Renewal alerts sent on SMS, email, mail, IVR and available on portal
ECS mandatory for monthly and quarterly modes effective October 2008
Process related Information to the customer on login/issuance on policy term and premium mode via
SMS/welcome call
Multiple renewal collection mechanisms – internet banking, online payment gateways,
kiosk, mobile, branch, collection service, etc
Awareness building through retention team meetings with sales and operations teams in
the offices to drive focus. Also building awareness campaign thru e-mailers
Field Force drivers Target setting for renewal collections for TMs and RMs
Retention as one of key KPIs of the branch operations teams
Contest for Ops, Sales, Distributors
Source: Reliance Life
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15

16. Persistency Modeling: Approach
Predictive modeling: Predictive Modeling can be defined as an analysis of
large data sets to make inferences or identify meaningful relationships, and the
use of these relationships to better predict future events. It uses statistical tools
to separate systematic patterns from random noise and turns this information
into business rules, which should lead to better decision making
The prerequisites for a effective model are:
A clearly defined target variable, i.e. what the model is trying to predict
The availability of suitably rich data set, in which at least some predictive
variables correlated with the target can be identified
A large number of observations upon which to build the model, allowing the
abiding relationships to surface and be separated from random noise
An application by which model results are translated into business actions
Copyright © 2011, SAS Institute Inc. All rights reserved.

17. Persistency Modeling – Our Approach & the Results
Model Performance : 84%
Persistency Improvement : 10%
Model Performance : 79%
Persistency Improvement : 5%
Customer Segment
Model Performance : 67% +
Product Variables
Customer Segment +
+ Customer Vintage
Model Performance : 57%
+
Product Variables
+ Agent Demographics
Customer Segment +
Customer Vintage
+ Orphaned Policies Customer
Model Performance : 54% +
Product Variables Service Experience
Agent Demographics
+ +
+
Customer Segment
Customer Vintage
Orphaned Policies Customer Market Performance
+
+
Service Experience
Product Variables
Economic Indicators
Customer Segment
Source: Reliance Life
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17

18. Scoring & Segment based Campaign Design
Segment 1 – Urban A Contract Segment Probability of Lapse
Common Contact Processes Premium Notice, SMS & Email
Customer Classification for Campaign Management
High Net Individuals Persistency Experience Non High Net Individuals Persistency Experience
Early Warning Early Warning
High Moderate Low High Moderate Low
Signals Signals
Tele-Calling
Tele-Calling IVR Calling
IVR Calling IVR Calling
IVR Calling IVR Calling IVR Calling IVR Calling IVR Calling IVR Calling
Tele-Calling
Tele-Calling Tele-Calling
Tele-Calling Tele-Calling Tele-Calling Tele-Calling
Runner Pick-up
Runner Pick-up Runner Pick-up Runner Pick-up
SM / Advisor SM / Advisor
Follow-up Follow-up
Source: Reliance Life
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18

19. Credits
RLIC Analytics Competency Center Partners
Business Retention
Analytics & Program Management SAS India
Chander Mahalingam
Amul Desai
Raghavendran Kandaswami Senior Manager, Business Retention,
Principal Consultant, SAS India
Senior Program Manager, RLIC Business RLIC
Technology
RainMan Consulting
Kaizad Gazdar
Kiran Kamat Chief Manager, Business
Chief Manager, RLIC IT Program Krishna Kumar CS, Chief Analytics Officer
Retention, RLIC
Management Office Satish BK, Project Manager & Analyst
Source: Reliance Life
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20. make connections • share ideas • be inspired
India’s Largest Analytics Forum
Thank You
Sameer Seksaria
Senior Vice President – Reliance Life Insurance Company
Mobile : + 91 9324899240
Email : sameer.seksaria@relianceada.com
Copyright © 2010, SAS Institute Inc. All rights reserved.