Microinsurance Databank: Catalyzing growth through a live market dashboard

Transcription

1 Microinsurance Databank: Catalyzing growth through a live market dashboard 6 th International Microinsurance Conference Manila 9-11 November Rupalee Ruchismita Executive Director Centre for Insurance and Risk Management (CIRM)

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

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

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

5 Catalyzing MI Growth Need For Information in Microinsurance 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 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

6 Drawing a Parallel: The MiX Precedence The Microfinance proof and the Microinsurance potential 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 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 Benefits Analysis: The Story in the Data Going Forward

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 Benefits Analysis: The Story in the Data Going Forward

11 Defining the Space Urban Target Client Rural Product Filing (Regulator) Products under Rural and Social Sector Obligation Products under Microinsurance Act 2005 Non-LIG LIG* LIG Non-LIG 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 Sources Regulator Market Data Industry Associations Insurers - public and private, life and general Mutuals and intermediaries - MFIs, Cooperatives, NGOs, input and output suppliers (on going) 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 Data categories 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 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

14 Life Health/Personal Accident Data Collection (contd.)industry Data Benefits Product 1 Product 2 Death Maturity Surrender 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

15 Data Collection (contd.)industry Data Benefits Product 1 Product 2 Livestock Permanent Total Disablement Temporary Total Disablement Permanent Partial Disablement Temporary Partial Disablement Weather Area Yield Crop loss due to High/Low Rain Crop loss due to High/Low Tempertaure Crop loss due to Diseases

16 Sourcing Data 1. Identifying sources of data Market information Secondary sources (Public Institutions, regulator, Govt., etc) Primary data sources (in-depth surveys of insurers, quantitative and qualitative ) Challenges Lack of willingness to share data (no institutional incentive identified) Lack of granular/disaggregated data availability Asset information Specialized data warehouses (Indian Meteorological Department, Central Water Commission, Actuaries Association of India, etc)

17 Sourcing Data (contd.) 2. Data Acquisition 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 3. Updates Challenges 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 Challenges 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

18 Agenda Why: Motivation for the Databank What is Microinsurance Map (MiM)? Putting It All Together Benefits Analysis: Outputs from MiM Observations The Story in the Data

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 agrometeorological 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 Use Stakeholder Value: Solutions for Intermediaries (Co-ops, NGOs, MFI) 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 Use Stakeholder Value: Solutions for Policy Makers 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 Benefits Analysis: The Story in the Data Going Forward

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 Map based output District level Premium Calculators Agronomy reports Cattle risk reports, Health Morbidity reports (in 2011) Product Features Public v/s Private cumulative premium Companies v/s Premium Amount Agronomy report for a region

25 14 Growth: New Products registered Rural, Social & Microinsurance growth: Public & Private Private Public Count Financial Year

26 Growth: (contd.) New Products registered Rural, Social & Microinsurance growth: Public & Private Count Count %age Percentage Growth Financial Year 0

27 Growth: (contd.) Premium underwritten: Public & Private (General Insurers) Private Public INR in Millions Financial Year

28 Growth: (contd.) in Premium (General Insurers) Company-wise Premium underwritten INR in Millions Star Health and Allied Insurance The Oriental Insurance United India Insurance National Insurance The New India Assurance Cholamandalam Ms General Insurance Reliance General Insurance Future Generalli India Iffco Tokio General Insurance Bharti AXA General Insurance Royal Sundaram Alliance Insurance ICICI Lombard General Insurance Apollo Munich Health Insurance General Insurers HDFC ERGO General Insurance Shriram General Insurance Bajaj Allianz General Insurance Tata AIG General Insurance Raheja QBE General Insurance Agriculture Insurance Company Export Credit Guarantee Corporation of India Universal Sompo

29 Claims Performance Microinsurance Portfolio ( & ) INR in Millions Claims Paid No. of Lives Financial Year vs No. of Lives Public Private

30 Risk wise patterns: Agriculture Insurance Company of India: Premium underwritten ( to ) INR in Millions Financial Year

31 Risk wise patterns (contd.) Performance of Govt. Health Schemes Govt. Schemes RSBY- National Aarogyashri State Specific Kalaignar State Specific Outreach (in Millions) (BPL Families) 3.75 (BPL Families) 1.4 (BPL Families)

32 Risk wise patterns (contd.) Performance of Govt. Health Schemes: RSBY No. of Families in Millions 12,00 10,00 8,00 6,00 4,00 2,00 0, RSBY Scheme : Families Covered Assam Bihar Chandigarh Chhattisgarh Delhi Goa Gujarat Haryana Himachal Pradesh Jharkhand Karnataka Kerala Maharashtra Manipur Meghalaya Mizoram Nagaland Orissa Punjab Tamilnadu Tripura Uttar Pradesh Uttarakhand West Bengal States Total BPL Families BPL Families enrolled till Date %age Families Reached Percentage of Families Covered

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

34 Going Forward A site overview: 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 Our Blog Safety Nets for all

36 Click here to generate basic information report Advanced Report Selection

37 Advanced Report Query Selection Page

38 Queries Selected

39 Public vs Private Queries Selected

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)

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 Acts & Regulations in Microinsurance List of rural, social & Microinsurance products 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

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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 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 Internet Map data November 16, 2010 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.