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Microinsurance map

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  • raRegulation
  • raRegulation
  • raRegulation
  • Is the data collection process reliable What are the Scientific mechanisms used to weed out junk data ?
  • Is the data collection process reliable What are the Scientific mechanisms used to weed out junk data ?
  • The slide should be exhaustive in terms of capturing categories of report but not in capturing all combinations

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  • 1. Microinsurance Databank : Catalyzing growth through a live market dashboard Rupalee Ruchismita Executive Director Centre for Insurance and Risk Management (CIRM) 6 th 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
    • MiM relies on Industry data reported under IRDA regulation (as under MI Act 2005 and under the Rural and Social Obligations)
    • Under the IRDA regulations, reported data includes products served to RED PLUS GREEN
    • Hence, Microinsurance Maps also presents data for RED PLUS GREEN
    • 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: C rop 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. Sample Snapshot: Public v/s Private Premium Graphical Report generated
  • 41. Sample Snapshot (contd.): Companies v/s Premium Graphical Report generated
  • 42. Sample Snapshot (contd.): Agronomy Report
  • 43. Choose desired state of India ( Tamilnadu )
  • 44. Choose desired district of Tamilnadu ( Thanjavur )
  • 45. Choose desired block in Thanjavur district ( Papanasm )
  • 46. Right click on Papanasm to open block information window
  • 47.  
  • 48. Choose type of crop category for which info is desired ( Cereals)
  • 49. Choose type of crop for which info is desired ( Paddy)
  • 50. Choose type of crop variety for which info is desired ( Kuruvai Paddy)
  • 51. Agronomy report for kuruvai paddy can be downloaded from this link
  • 52.  
  • 53. 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
  • 54.  
  • 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 November 15, 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
    Internet Market/Risk data Map data Webserver Mapping Server Database Server
  • 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.