1. 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

2. Agenda
Why: Motivation for the Databank
What is Microinsurance Map (MiM)?
Putting It All Together
Analysis: The Story in the Data
Going forward
Benefits

3. Agenda
Why: Motivation for the Databank
What is Microinsurance Map (MiM)?
Putting It All Together
Analysis:The Story in the Data
Going Forward
Benefits

4. Catalyzing MI Growth
Sustainable MI growth needs
» Capital
» Distribution models
» Information

5. 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

6. 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

7. 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

8. Agenda
Why: Motivation for the Databank
What is Microinsurance Map (MiM)?
Putting It All Together
Analysis: The Story in the Data
Going Forward
Benefits

9. Microinsurance Map
A publicly available MI Data Bank comprising industry and risk data
Partners: Micro Insurance Innovation Facility, ILO

10. Agenda
Why: Motivation for the Databank
What is Microinsurance Map (MiM)?
Putting It All Together
Analysis: The Story in the Data
Going Forward
Benefits

11. 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
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

12. 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

13. 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

14. Data Collection (contd.)Industry Data

15. Data Collection (contd.)Industry Data

16. 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

17. 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

18. 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

19. 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

20. 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

21. 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

22. 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

23. Agenda
Why: Motivation for the Databank
What is Microinsurance Map (MiM)?
Putting It All Together
Analysis: The Story in the Data
Going Forward
Benefits

24. 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)

25. Growth: New Products registered
Rural, Social & Microinsurance growth: Public & Private

26. Growth: (contd.)
New Products registered
Rural, Social & Microinsurance growth: Public & Private

27. Growth: (contd.)
Premium underwritten:
Public & Private (General Insurers)

28. Growth: (contd.)
in Premium (General Insurers)
Company-wise Premium underwritten

29. Claims Performance
Microinsurance Portfolio (2007-08 & 2008-09)

30. Risk wise patterns:
Agriculture Insurance Company of India:
Premium underwritten (2005-06 to 2009-10)

31. 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)

32. Risk wise patterns (contd.)
Performance of Govt. Health Schemes: RSBY

33. Agenda
Why: Motivation for the Databank
What is Microinsurance Map ?
Putting It All Together
Analysis: The story in the data
Going Forward
Benefits

34. 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

35. 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

36. Click here to generate basic
information report
Advanced Report Selection

37. Advanced Report Query Selection Page

38. Queries Selected

39. Queries Selected
Public vs Private

40. Graphical Report generated
Sample Snapshot: Public v/s Private Premium

41. Sample Snapshot (contd.): Companies v/s Premium
Graphical Report generated

42. Sample Snapshot (contd.): Agronomy Report

43. Choose desired state of
India (Tamilnadu)
Choose desired state of
India (Tamilnadu)

44. Choose desired district of
Tamilnadu
(Thanjavur)
Choose desired district of
Tamilnadu
(Thanjavur)

45. Choose desired block in
Thanjavur district
(Papanasm)
Choose desired block in
Thanjavur district
(Papanasm)

46. Right click on
Papanasm to open
block information
window
Right click on
Papanasm to open
block information
window

48. Choose type of crop
category for which info is
desired
(Cereals)
Choose type of crop
category for which info is
desired
(Cereals)

49. Choose type of crop for
which info is desired
(Paddy)
Choose type of crop for
which info is desired
(Paddy)

50. Choose type of crop variety
for which info is desired
(Kuruvai Paddy)
Choose type of crop variety
for which info is desired
(Kuruvai Paddy)

51. Agronomy report for
kuruvai paddy can be
downloaded from this
link
Agronomy report for
kuruvai paddy can be
downloaded from this
link

53. List of rural, social & Microinsurance productsActs & 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

55. 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

56. Technology Platform
January 30, 2015
• 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

57. 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.