Microinsurance Databank: Catalyzing growth through a live market dashboard
Rupalee Ruchismita Executive Director
Centre for Insurance and Risk Management (CIRM)
6th International Microinsurance Conference Manila
9-11 November
Agenda
Why: Motivation for the Databank
What is Microinsurance Map (MiM)?
Putting It All Together
Analysis: The Story in the Data
Going forward
Benefits
Agenda
Why: Motivation for the Databank
What is Microinsurance Map (MiM)?
Putting It All Together
Analysis:The Story in the Data
Going Forward
Benefits
Catalyzing MI Growth
Sustainable MI growth needs » Capital
» Distribution models
» Information
Catalyzing MI Growth Need For Information in Microinsurance
• Absence of risk data: • Lack of actuarially sound pricing
• Regional health morbidity, livestock breed and disease data missing
• Inability to foray into new risk areas • Vicious cycle: Conservative high price - Attracting high risk clients - High claims: escalation of premium costs
– Absence of Market data: – Isolated innovations without replication – Limited efforts at recording and assessing efficacy of insurer’s MI
strategy – Parallel efforts by intermediaries to compare and choose products in
the market
Drawing a Parallel: The MiX Precedence
• 10 years ago, microfinance was in a similar state as Microinsurance is
today
• MiX Market is a global, web-based, microfinance information platform
– A dashboard of financial, operational and social performance data
– Standardises data based on international accounting standards
– A trusted, independent and accessible source
• Today 1,800 MFIs report to MiX Market. It has 200 partners
The Microfinance proof and the Microinsurance potential
Inspired us to create a National (India) Data Bank for Microinsurance
Core Objective of the Databank
Access to market level data, contributes to:
• Improved transparency leading to self regulation of market
• Sharing of best practices seamlessly
• Key Value
– Tool to spearhead innovation and greater outreach
– Better planning by regulator for catalysing Microinsurance
sector growth
Agenda
Why: Motivation for the Databank
What is Microinsurance Map (MiM)?
Putting It All Together
Analysis: The Story in the Data
Going Forward
Benefits
Microinsurance Map A publicly available MI Data Bank comprising industry and risk data
Partners: Micro Insurance Innovation Facility, ILO
Agenda
Why: Motivation for the Databank
What is Microinsurance Map (MiM)?
Putting It All Together
Analysis: The Story in the Data
Going Forward
Benefits
Target Client
Urban Rural
Non-LIG LIG* LIG Non-LIG
Prod
uct F
iling
(R
egul
ator
) Products under ‘Rural and Social
Sector’ Obligation
1 2 3 4
Products under ‘Microinsurance
Act 2005’
5 6 7 8
Defining the Space
1. MiM relies on Industry data reported under IRDA regulation (as under MI Act 2005 and under the Rural and Social Obligations)
2. Under the IRDA regulations, reported data includes products served to RED PLUS GREEN 3. Hence, Microinsurance Maps also presents data for RED PLUS GREEN 4. Ideally it should report for products offered to GREEN * LIG: Low Income Groups * IRDA: Insurance Regulatory and Development Authority
Data Collection A publicly available MI Data Bank comprising industry and risk data
Market Data • Regulator • Industry Associations • Insurers - public and private, life and general • Mutuals and intermediaries - MFIs, Cooperatives, NGOs, input and output suppliers (on going)
Sources
Risk data on regional basis
• Indian Meteorological Department,
Central Water Commission, Actuaries
Association of India, Govt. Dept. of
Agriculture, National Remote Sensing
Centre, Agriculture Universities
• Veterinary Universities
Data Collection (contd.) A publicly available MI Data Bank comprising industry and risk data
• Agri crop data: variety, cropping
season and period, acreage, primary
risk (meteorological, pest and practice
related)
• Cattle: Breed, primary risks, mortality
rates, productivity factors
• Health: To be defined in March 2011
Organizational Profile Microinsurance business
• Premia - value, volume over time and region • Claims experience - settled, repudiated, time taken over time and region • Gender break up of client over time, region and product category
Product portfolio: for every product • All of the above • Coverage - exclusions, discounts • Distribution and sales strategy
Data categories
Data Collection (contd.)Industry Data Benefits Product 1 Product 2
Life
Death
Maturity
Surrender
Hea
lth/
Pers
onal
Acc
iden
t
In-patient Hospitalization
Outpatient care
Major surgical benefit
Critical illness benefit
Maternity benefit
Domiciliary treatment
Accidental medical expenses Legal expenses
Laboratory tests
Medicines
Pre-existing diseases
Day Care
Co-Payment
No Claim Benefit
Transportation charges
Data Collection (contd.)Industry Data Benefits Product 1 Product 2
Live
stoc
k
Permanent Total Disablement
Temporary Total Disablement
Permanent Partial Disablement
Temporary Partial Disablement
Wea
ther
Area Yield
Crop loss due to High/Low Rain
Crop loss due to High/Low Tempertaure
Crop loss due to Diseases
Sourcing Data
Market information
• Secondary sources (Public
Institutions, regulator, Govt., etc)
• Primary data sources (in-depth
surveys of insurers, quantitative
and qualitative )
• Lack of willingness to share data (no
institutional incentive identified)
• Lack of granular/disaggregated data
availability
1. Identifying sources of data
Asset information
• Specialized data warehouses
(Indian Meteorological Department,
Central Water Commission,
Actuaries Association of India, etc)
Challenges
Sourcing Data (contd.)
• Standardization required to merge data from disparate sources
• Clean up to validate incomplete and erroneous data
• Acquired data to meet minimum quality levels for usability
• Most insurers and intermediaries do not have data in organized form
• Data validation by the provider rarely possible
• Data shared in bits-n-pieces and data elements not in sync in time leading to substantial delay in putting it to use
2. Data Acquisition
• Periodically updating data elements to maintain relevance of data bank
• Frequency of data updation dependant on data type
• Frequency of data limited by
available resources
3. Updates
Challenges
Challenges
Agenda
Why: Motivation for the Databank
What is Microinsurance Map (MiM)?
Putting It All Together
Analysis: Outputs from MiM
Observations – The Story in the Data
Benefits
Microinsurance Map: Trends and Maps
• Market Trends: • Outreach
• Provider Profile
• Product feature comparison
• Government sponsored insurance schemes
• Best practices
• Asset based data outputs and tools: • Agriculture: Crop variety based Premium Calculators at an agro-
meteorological unit
• Cattle: Valuation based on breed and region
Stakeholder Value: Solutions for Insurers
Use • Disaggregated region specific risk data to develop actuarially sound
product pricing • Market insight for development of outreach strategies – competitor
and profitability analysis, exposure to innovative product and processes
Benefit • Public platform to market products, find potential intermediaries, new
relations (IT providers, TPAs) • Plan market entry based on a range of factors- geographical,
distribution models, risk specific and competitor based analysis • Market assessment – Updated about ‘sector news’; Trend analyses
(over years, regions, risk type and market players) • Own portfolio monitoring, analysis and tracking
Stakeholder Value: Solutions for Intermediaries (Co-ops, NGOs, MFI)
Use • Reports to compare pricing and features of own product by various
criteria (region, risk type and insurer, premium and claims) Benefit • Use sector best practices to measure own and partner’s (insurer)
service quality • Improve own visibility to find partners • Assess insurers based on products and performance
Stakeholder Value: Solutions for Policy Makers
Use • Monitor impact of regulation on providers and products Benefit • Create industry benchmarks on product, process and service quality • Identify early trends (sectorally and also for specific providers and
risk categories) to respond accordingly • Make proactive regulation and policy for underserved regions and
track its impact on the market
Agenda
Why: Motivation for the Databank
What is Microinsurance Map (MiM)?
Putting It All Together
Analysis: The Story in the Data
Going Forward
Benefits
The Features
• Outputs- Static and dynamic market snapshots
• Examples:
• Volumes, value, risk category
(life, non-life), ownership
(public, private)
• Claim status (amount & number
settled and repudiated)
• Geographical Coverage
• Product Features
Public v/s Private cumulative premium
Companies v/s Premium Amount
Agronomy report for a region
• Map based output
• District level Premium
Calculators
• Agronomy reports
• Cattle risk reports,
• Health Morbidity
reports (in 2011)
Growth: New Products registered Rural, Social & Microinsurance growth: Public & Private
0
2
4
6
8
10
12
14
2001-02 2002-03 2003-04 2004-05 2006-07 2007-08 2008-09 2009-10
Cou
nt
Financial Year
Private
Public
Growth: (contd.) New Products registered
Rural, Social & Microinsurance growth: Public & Private
0
10
20
30
40
50
60
70
0
2
4
6
8
10
12
14
2001-02 2002-03 2003-04 2004-05 2006-07 2007-08 2008-09 2009-10
Perc
enta
ge G
row
th
Cou
nt
Financial Year
Count
%age
Growth: (contd.)
Premium underwritten: Public & Private (General Insurers)
0
2000
4000
6000
8000
10000
12000
14000
2008-09 2009-10
INR
in M
illio
ns
Financial Year
Private
Public
Growth: (contd.)
in Premium (General Insurers) Company-wise Premium underwritten
-
1.000
2.000
3.000
4.000
5.000
6.000
7.000
8.000
9.000
10.000 St
ar H
ealth
and
Alli
ed In
sura
nce
The
Orie
ntal
Insu
ranc
e
Uni
ted
Indi
a In
sura
nce
Nat
iona
l In
sura
nce
The
New
Indi
a As
sura
nce
Cho
lam
anda
lam
Ms
Gen
eral
In
sura
nce
Rel
ianc
e G
ener
al I
nsur
ance
Futu
re G
ener
alli
Indi
a
Iffco
Tok
io G
ener
al In
sura
nce
Bha
rti A
XA G
ener
al In
sura
nce
Roy
al S
unda
ram
Alli
ance
In
sura
nce
ICIC
I Lom
bard
Gen
eral
Insu
ranc
e
Apol
lo M
unic
h H
ealth
Insu
ranc
e
HD
FC E
RG
O G
ener
al In
sura
nce
Shrir
am G
ener
al In
sura
nce
Baj
aj A
llian
z G
ener
al In
sura
nce
Tata
AIG
Gen
eral
Insu
ranc
e
Rah
eja
QB
E G
ener
al I
nsur
ance
Agric
ultu
re In
sura
nce
Com
pany
Expo
rt C
redi
t Gua
rant
ee
Cor
pora
tion
of In
dia
Uni
vers
al S
ompo
INR
in M
illio
ns
General Insurers
2008-09
2009-10
Claims Performance
Microinsurance Portfolio (2007-08 & 2008-09)
0
20000
40000
60000
80000
100000
120000
140000
160000
180000
2007 2008 2007 2008
Claims Paid No. of Lives
INR
in M
illio
ns
Financial Year vs No. of Lives
Public
Private
Risk wise patterns: Agriculture Insurance Company of India:
Premium underwritten (2005-06 to 2009-10)
5.558 5.647
8.351 8.334
15.204
-
2.000
4.000
6.000
8.000
10.000
12.000
14.000
16.000
2005-06 2006-07 2007-08 2008-09 2009-10
INR
in M
illio
ns
Financial Year
Risk wise patterns (contd.) Performance of Govt. Health Schemes
Govt. Schemes Outreach (in Millions)
RSBY- National 19.69 (BPL Families)
Aarogyashri – State Specific 3.75 (BPL Families)
Kalaignar – State Specific 1.4 (BPL Families)
Risk wise patterns (contd.) Performance of Govt. Health Schemes: RSBY
60
49
39 45
60
50 48 45
18
60 56
31
57
75
53
67
32 39
64 67
15
49 56
46
-
10
20
30
40
50
60
70
80
0,00
2,00
4,00
6,00
8,00
10,00
12,00
Ass
am
Bih
ar
Cha
ndig
arh
Chh
attis
garh
D
elhi
G
oa
Guj
arat
H
arya
na
Him
acha
l Pra
desh
Jh
arkh
and
Kar
nata
ka
Ker
ala
Mah
aras
htra
M
anip
ur
Meg
hala
ya
Miz
oram
N
agal
and
Oris
sa
Pun
jab
Tam
ilnad
u Tr
ipur
a U
ttar P
rade
sh
Utta
rakh
and
Wes
t Ben
gal
Perc
enta
ge o
f Fam
ilies
Cov
ered
No.
of F
amili
es in
Mill
ions
States
RSBY Scheme : Families Covered
Total BPL Families BPL Families enrolled till Date %age Families Reached
Agenda
Why: Motivation for the Databank
What is Microinsurance Map ?
Putting It All Together
Analysis: The story in the data
Going Forward
Benefits
Going Forward…
• A site overview: www.microinsurancemap.com • Completing data collection process • Launching product comparison matrix • Creating incentives for periodic updates
• Expanding Agriculture risk maps nationally • Launching Cattle Risk maps in one state • Initiating Data collection of Health risk Maps
Thank You
Please visit us at http://www.ifmr.ac.in/cirm
Our Blog Safety Nets for all
http://www.ifmr.ac.in/cirm/blog
Click here to generate basic information report
Advanced Report Selection
Advanced Report Query Selection Page
Queries Selected
Queries Selected
Public vs Private
Graphical Report generated
Sample Snapshot: Public v/s Private Premium
Sample Snapshot (contd.): Companies v/s Premium
Graphical Report generated
Sample Snapshot (contd.): Agronomy Report
Choose desired state of India (Tamilnadu)
Choose desired district of Tamilnadu
(Thanjavur)
Choose desired block in Thanjavur district
(Papanasm)
Right click on Papanasm to open block information window
Choose type of crop category for which info is desired
(Cereals)
Choose type of crop for which info is desired
(Paddy)
Choose type of crop variety for which info is desired
(Kuruvai Paddy)
Agronomy report for kuruvai paddy can be downloaded from this link
List of rural, social & Microinsurance products Acts & Regulations in Microinsurance
Pre-defined Report Links (Market Information)
Pre-defined Report Links (Risk Information)
Click here to go to market information page
Click here to go to risk information page
Database Capabilities
• Micro Insurance Map database is scalable and reliable and can easily handle data for multiple countries.
• Database design is done in such a manner data can be managed by administrative boundaries at all levels.
• Other core capabilities of the database
– Supports transactions
– integrity checks
– less data redundancy
– fundamental organization and operations handled by the DB
– multi-user support
– security/access control
– Locking
– backups
Technology Platform
November 16, 2010
• Micro Insurance Map have been completely developed using open source tools • Language : Java/J2EE • Web Server : Apache Tomcat • Map Server : GeoServer • Database Server : PostgreSQL/PostGIS • Client Layer : Ext JS/HTML
Market/Risk data
Map data
Webserver Mapping Server
Database Server
Internet
Database : PostgreSQL/PostGIS
PostgreSQL •PostgreSQL is a Open source Relational Database Management System(RDBMS). •A standards-compliant SQL-based database server with which a wide variety of client applications can communicate PostGIS •Open source Spatial Extension for PostgreSQL developed by Refractions Research •An implementation of the OGC Simple Features for SQL Specification within PostgreSQL for the storage of geospatial data (points, lines, polygons) within an SQL based relational database management system (RDBMS). •Developed as a set of functions and data types that ‘spatially enable’ the PostgreSQL object-relational database system.