Financial Engineering for Low-Income Households

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Edited by: Bindu Ananth & Amit Shah

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    List of Figures

    • 1.1 Household without any financial mechanisms 10
    • 1.2 Household with life and disability insurance 11
    • 1.3 Household with insurance and financial asset 12
    • 2.1 Probability distribution using toss of coin 28
    • 2.2 Uniform distribution using throw of a die 30
    • 2.3 Binomial distribution using throw of a die 32
    • 2.4 Poisson distribution at regular and irregular events 33
    • 2.5 Uniform distribution tending to normalcy 35
    • 3.1 Risk-averse investor's utility function 42
    • 3.2 Risk-neutral investor's utility function 43
    • 3.3 Risk-seeking investor's utility function 43
    • 4.1 Efficient frontier plotting mean and sigma at different weights of A and B 54
    • 4.2 Expected utility at different levels of lambda 58
    • 4.3 Returns using different capital market lines 60
    • 4.4 Utility at the capital market line 62
    • 5.1 L1's exposure to B1 and B2 throughout the loan tenure 72
    • 5.2 Effect of cash collateral on exposure 74
    • 6.1 Human capital across the lifetime of an individual 82
    • 6.2 Comparing value of human capital by age for a healthy person and a smoker with an optimum BMI 91
    • 6.3 Accretion in human and financial capital with positive returns to education 93
    • 6.4 Annual and cumulative investment returns to education 95
    • 8.1 Low-frequency and high-impact health expenditures for one village 116
    • 8.2 Low-frequency and high-impact health expenditures for 100 villages 117
    • 8.3 High-frequency and low-impact health expenditures for one village 118
    • 8.4 High-frequency and low-impact health expenditures for 100 villages 119
    • 8.5 Scenario where Shankar is without health insurance 120
    • 8.6 Scenario where Shankar has health insurance 122
    • 9.1 Distribution of population by age group and old-age dependency 125
    • 9.2 Break-up of financial savings in different instruments (2006–07) 127
    • 9.3 Asset allocation of a typical rural low-income household 128
    • 9.4 Retirement income needed to keep pace with inflation 130
    • 9.5 Effect of withdrawal rate on retirement portfolio 131
    • 12.1 Sales volatility versus debt servicing capacity (Scenario 1) 166
    • 12.2 Sales volatility versus debt servicing capacity (Scenario 2) 167
    • 13.1 Price movement for castor seeds across 5 years 175
    • 14.1 Year-on-year cumulative cash position 185
    • 14.2 Life wealth envelope of the household without using any financial tools 189
    • 14.3 Life wealth envelope of the household after purchasing insurance 191
    • 14.4 Existing portfolio allocation of the household 194
    • A16.1 Year-on-year cash flow plan for the household 213

    List of Tables

    • 2.1 Probability distribution using toss of coin 28
    • 2.2 Uniform distribution using throw of a die 30
    • 2.3 Binomial distribution using throw of a die 32
    • 3.1 How an investor will look at a ₹ 100 loss at different levels of wealth 44
    • 3.2 How an investor will look at losses which are proportional to her/his levels of wealth 45
    • 3.3 Types of utility functions—absolute and relative 45
    • 4.1 Illustration using mean, sigma, and correlation of two assets 52
    • 4.2 Mean and sigma at different weights of Asset A and Asset B 53
    • 4.3 Expected utility at different levels of lambda 57
    • 4.4 Returns using different capital market lines 59
    • 4.5 Utility at the capital market line 61
    • 4A.1 Relative risk and correlation of different investments and activities 65
    • 4B.1 Assumptions on real returns and standard deviations of different assets and liabilities 66
    • 4C.1 Correlation matrix of different assets and liabilities 67
    • 4C.2 Covariance matrix of different assets and liabilities 68
    • 5.1 Details of L1's loan portfolio 75
    • 5.2 Scenarios of expected loss on portfolio 76
    • 5.3 Calculating unexpected loss on a portfolio 77
    • 6.1 Estimates of life and personal accident insurance at different ages 86
    • 6.2 Minimum returns to education in India 93
    • 6.3 Investment returns to education 94
    • 6.4 Total individual insurance recommendations (assuming that at birth parent commits only to education up to 7th grade) 96
    • 6A.1 Estimated human capital at each age (real values 2010 prices) (Tabulated) 100
    • 6B.1 Annual real returns to education 104
    • 7A.1 Published mortality table—effective January 1, 2005 112
    • 8.1 Loans and savings as an option for high-frequency-low-impact health events 119
    • 9.1 Distribution of population across age groups and sectors 124
    • 9.2 Distribution of annual expenses for Padma today 129
    • 9.3 Mortality credits 132
    • 11.1 Water requirement at each stage of the crop 145
    • 11.2 Actual rainfall at each stage of the crop 145
    • 11.3 Water deficit at each stage of the crop 145
    • 11.4 Yield loss due to deficit water in each stage of the crop 146
    • 11.5 Characteristics of the insurance payout 146
    • 13.1 Illustration of price movements in castor seeds from September 2012 to February 2013 177
    • 13.2 Illustration of usage of warehouse receipt financing 178
    • 13.3 Illustration of usage of a futures contract 179
    • 14.1 Assessment of the assets and liabilities of the household 186
    • 14.2 Assessment of the various goals of the household 187
    • 14.3 Insurance requirements for the household 190
    • 14.4 Existing portfolio allocation of the household 193
    • 14.5 Recommended portfolio allocation of the household 195
    • 14.6 Comparison of various parameters for existing and recommended portfolio allocations 195
    • 14.7 Recommendation of portfolio allocation to the household 195
    • A1.1 Calculation of income from tea shop 199
    • A2.1 Calculation of income from agriculture 200
    • A3.1 Calculation of income from livestock 201
    • A4.1 Break-up of the household's routine annual expenses 201
    • A5.1 Cash flow statement for the next 10 years of the household 202
    • A6.1 Tabulation of human capital and insurance at different levels of risk aversion 204
    • A8.1 Tabulation of risk and returns of various assets and liabilities 205
    • A9.1 Gross human capital of the household 206
    • A10.1 Tabulation of liabilities towards human capital expenses and goals 206
    • A11.1 Tabulation of present value of local businesses 206
    • A12.1 Long positions in local real estate 207
    • A12.2 Short positions in local real estate 207
    • A13.1 Correlation matrix of different assets and liabilities 208
    • A13.2 Covariance matrix of different assets and liabilities 209
    • A14.1 Recommended asset allocation for different levels of risk aversion 210
    • A14.2 Recommended asset allocation for different levels of risk aversion when the household does not wish to trade in real-estate 211
    • A16.2 Assessment of assets and liabilities of the household 214
    • A16.3 Assessment of the goals of the household 214
    • A16.4 Recommended insurance amounts for the household 215
    • A16.5 Recommended asset allocation for different levels of risk aversion 215
    • A16.6 Recommended asset allocation for different levels of risk aversion when the household does not wish to trade in real estate 216

    List of Abbreviations

    ADBAsian Development Bank
    AICLAgricultural Insurance Company of India
    BMIBody Mass Index
    BQBlack Quarter
    CAPMCapital Asset Pricing Model
    CLTCentral Limit Theorem
    CMLACapital Market Line A
    CMLBCapital Market Line B
    CMRCompound Mortality Rate
    CRRAConstant Relative Risk Aversion
    CSRCompound Survival Rate
    DARADecreasing Absolute Risk Aversion
    EDFExpected Default Frequency
    FELIHFinancial Engineering for Low-income Households
    FIFinancial Institution
    FIIForeign Institutional Investor
    FMDFoot and Mouth Disease
    GDPGross Domestic Product
    GICGeneral Insurance Corporation of India
    HSHemorrhagic Septicemia
    IARAIncreasing Absolute Risk Aversion
    IFMRInstitute for Financial Management and Research
    i.i.d.Independent and Identically Distributed
    IRRAIncreasing Relative Risk Aversion
    KGFSKshetriya Gramin Financial Services
    LGDLoss-given-default
    LIWELife Wealth Envelope
    MPCEMonthly Per capita Consumption Expenditure
    NSSONational Sample Survey Organisation
    PDProbability of Default
    PTDPermanent Total Disability
    RBIReserve Bank of India
    ROCReturn on Capital
    VaRValue at Risk

    Foreword

    Having worked in corporate banking for over 25 years, I know that the clear expectation from a client is that we present to them bankers that are very well trained in finance and are able to offer customized and high-quality advice based on the particular situation of the client. And, for the most part, it has been my experience that while clients often know a great deal about the products and services that they are involved in, they are not very knowledgeable about financial instruments and financial markets, and it is the role of the banker to ensure that the products being offered to the client are indeed in the clients’ own best interest. Courts of law around the world have supported this view by allowing clients to claim compensation from their bankers if it has been found even in retrospect that an improper product or service was sold to them.

    Given this background, as an observer, it has been a great source of puzzlement for me as to how the retail finance industry has gone in a completely different direction and has transferred more and more of the burden of deciding which products or instruments best meet the individual's needs away from the bankers to the frail shoulders of the consumer.

    Finance has the power to help households manage several risks and give them the tools with which to plan their lives; maximize their growth potential; and offer them protection against large unexpected shocks as well as longer term changes in prices of their financial and physical assets. To insist on offering them “simple” products is to deny them access to this enormously powerful force which, if harnessed well, can have a transformative impact on their lives. A much more interesting direction to go, in my view, is to systematically train and certify the frontline staff of each and every provider so that they can more fully understand the economic and financial situation of the household as well as the underlying principles behind the design of financial products. It then becomes possible for them to understand the impact that the particular product or suite of products being offered by their institution can have on the customer and more accurately assess its suitability for the household. Unfortunately, materials that can support such a comprehensive training program are to be found only in advanced PhD programs and that too focused on one or more narrow domains.

    This volume, edited by Bindu Ananth and Amit Shah of Institute for Financial Management and Research (IFMR) Trust, for the first time effectively fills this gap and offers a systematic approach toward building such competencies in the frontline staff of all financial institutions. Both the authors are keen students of finance and have been closely involved in the implementation of the Kshetriya Gramin Financial Services (KGFS) model pioneered by IFMR Rural Finance—one of the subsidiaries of IFMR Trust. In this volume, they do not claim to present any original research, but rather they successfully assemble ideas from a vast variety of sources into one cogent and accessible volume. They develop the entire structure of the book from the point of view of an institution serving low-income households which seeks to offer the most comprehensive suite of financial services imaginable, with the help of a frontline staff member who has completed an education only up to the level of the high school. The result, in my view, is an outstanding book that has been written in such a way that it can be directly used to train and inform frontline staff at all types of financial institutions and its treatment of very complex concepts in finance is such that it will be of use to all levels of management within a financial institution—from the CEO to the fresh management graduate as well as to the “teller” or the “sales agent” working in domains as diverse as banking, insurance, pensions, and mutual funds.

    NachiketMor, Member, Board of Directors, ICICI Bank (2001–07); Chair, Governing Council, IFMR Trust (2008–11)

    Preface

    Financial Engineering for Low-Income Households (FELIH) is an edited compilation of technical articles aimed at practicing professionals and students of development finance. The book aims to provide an understanding of the various risk-return trade-offs facing low-income households and how principles of financial engineering can be best applied to design financial services for this segment.

    Plan of the FELIH Book

    The book is divided into four sections. The first section highlights key conceptual issues in providing universal access to finance. It gives a good background to appreciate the idea of FELIH which is building expertise for providers of financial services.

    In the second section, we cover the essentials of financial engineering so that the reader has the necessary background to appreciate the more application-oriented sections. The treatment of each of the topics is at a basic-to-intermediate level with references being provided for those who want to access more advanced treatments of the topics being discussed.

    In the third section, we go on to discuss the basic risk types that need to be understood in order to develop financial products and to provide wealth management advice to low-income individuals and households. The focus here is on understanding the basic ideas and on working through simulations and problem sets in order to develop a full understanding of the nature of the underlying risks that individuals, households, and enterprises face. The chapters in this section also explore the different types of products that may be offered to individuals and households as a part of an integrated wealth management service. The pricing of each product is covered in some detail and there is also a discussion on where and how, on a stand-alone basis the products may be offered to low-income communities.

    In the final section, there is a case study of a household along with a comprehensive financial plan. It builds on the understanding from different chapters and integrates various risk types into an individual's life and a number of different individuals and enterprises into a household.

    FELIH is a valuable tool for practitioners and students interested in understanding the design and delivery of financial services to low-income households.

  • Appendices

    Appendix A1: Income from Tea Shop

    Table A1.1: Calculation of income from tea shop

    Appendix A2: Income from Agriculture

    Table A2.1: Calculation of income from agriculture

    Appendix A3: Income from Livestock
    Table A3.1: Calculation of income from livestock
    Livestock—One Cow6—Current IncomeAmount
    Income items
    Milk 7 liters per day × ₹ 13.5 per liter × 270 days25,515
    Total income (A)25,515
    Expense items
    Cattle feed3,000
    Medical expenses100
    Imputed cost of labor (360 days)77,200
    Total expense (B)10,300
    Net income—One cow (A—B)15,215
    Source: Based on primary research done by the editors.
    Appendix A4: Household's Routine Annual Expenses
    Table A4.1: Break-up of the household's routine annual expenses
    Expense ItemAmount
    Provisions (500 per month)6,000
    Paddy from own farm88,000
    Black Gram from own farm4,800
    Water (30 per month)360
    Electricity (375 bimonthly)2,250
    Mobile (300 per month)3,600
    TV (120 per month)1,440
    Travel (200 per month)2,400
    Cash to Jaya's sister for children9 (600 per month)7,200
    Festivals500
    Other social functions1010,000
    Total household expenses48,550
    Source: Calculated on the basis of details in the case study.
    Appendix A5: Cash Flow Statement for the Next 10 Years of the Household

    Table A5.1: Cash flow statement for the next 10 years of the household11

    Appendix A6: Human Capital and Insurance at Different Levels of Risk Aversion

    Table A6.1: Tabulation of human capital and insurance at different levels of risk aversion15

    Appendix A7: Utility Function for Insurance16

    Utility function that is being maximized to arrive at the amount of Life Insurance:

    Utility function that is being maximized to arrive at the amount of Accident Insurance:

    where,

    x: Current age of the member

    Ux (): Utility of wealth of the member

    Hx : Human Capital of the member

    Wx : Financial Wealth of the member

    Kx : Human Capital of member upon being disabled

    θx : Face value of Life Insurance bought by member

    γx: Face value of Accident Insurance bought by member

    qx : Mortality rate for member

    λ : Risk Aversion Parameter

    η : Fees and expenses on the Life Insurance Policy charged by the insurer

    ₹: Fees and expenses on the Accident Insurance Policy charged by the insurer

    μ: Accident Rate

    β : Average payout rate upon being disabled owing to an accident

    D : Strength of the bequest motive17

    Appendix A8: Risk and Returns of Various Assets and Liabilities18
    Table A8.1: Tabulation of risk and returns of various assets and liabilities
    Assets/Liabilities/Short PositionsMean (%)Standard Deviation (%)
    Gross human capital010
    PV of local businesses010
    Long position in local real estate010
    Cattle-74
    Index fund930
    Gold317
    MMMF12
    Cash/investible surplus-74
    Short position on local real estate010
    Liabilities to human capital010
    Existing loans60
    Any new loan200
    Source:Table 4B.1, Chapter 4 of this book.
    Appendix A9: Gross Human Capital
    Table A9.1: Gross human capital of the household
    MemberGross Human Capital (net of insurance)
    Rajan270,000
    Jaya315,000
    Pramod730,000
    Total Gross HC1,315,000
    Source: Calculation on the basis of details in the case study.
    Appendix A10: Liabilities Towards Human Capital Expenses and Goals

    Table A10.1: Tabulation of liabilities towards human capital expenses and goals

    Appendix A11: Present Value of Local Businesses20
    Table A11.1: Tabulation of present value of local businesses
    DescriptionAmount
    Tea business
    Annual income114,300
    Fire and theft insurance1,143
    Lease/rental expense21900
    Net annual income112,257
    Discount rate2220%
    PV of tea business Agriculture activity561,285
    Annual income32,200
    Lease/rental expense10,500
    Net annual income21,700
    Discount rate2320%
    PV of agriculture activity108,500
    Livestock activity
    Annual income30,430
    Livestock insurance1,000
    Net annual income29,430
    Discount rate248%
    PV of livestock activity117,505
    Total PV of businesses (rounded off)787,000
    Source: Calculated on the basis of details in the case study.
    Appendix A12: Long and Short Positions in Local Real Estate
    Table A12.1: Long positions in local real estate
    Long PositionsValue
    Residential property2580,000
    Commercial property30,000
    Agricultural property26360,000
    Long position in real estate470,000
    Source: Calculated on the basis of details in the case study.
    Table A12.2: Short positions in local real estate
    Short PositionsValue
    Residential property27350,000
    Agriculture property28227,500
    Source: Calculated on the basis of details in the case study.
    Appendix A13: Correlation and Covariance Matrix29

    Table A13.1: Correlation matrix of different assets and liabilities

    Table A13.2: Covariance matrix of different assets and liabilities

    Appendix A14: Asset Allocation at Different Levels of Risk Aversion
    Table A14.1: Recommended asset allocation for different levels of risk aversion

    Recommended allocation when the household does not wish to trade property:

    Table A14.2: Recommended asset allocation for different levels of risk aversion when the household does not wish to trade in real-estate
    Appendix A15: Utility Function for Asset Allocation30

    The utility function used is exponential utility function:

    where C is the consumption, μ is the mean consumption level, σ is the standard deviation, and λ is a measure of the risk-aversion of the individual—the larger it is the more risk averse the individual is. In the case of an investor if it is assumed that all the returns from the investment are consumed then consumption could be replaced by investment returns and μ now is the mean return level and σ is the standard deviation of returns.

    Hence, the objective of the consumer/investor is to maximize the expression: .

    Appendix A16: Financial Well-being Report to the Household31
    Plan

    Cash flows sufficient to meet routine expenses and planned goals.

    Figure A16.1: Year-on-year cash flow plan for the household
    Grow
    Table A16.2: Assessment of assets and liabilities of the household
    Table A16.3: Assessment of the goals of the household
    • Repay all high cost debts at the earliest
    • Sell low-return assets to finance goals (more specific advice in “Diversify”)
    Protect

    Life and Accident Insurance as recommended in Table A16.4.

    Table A16.4: Recommended insurance amounts for the household
    • Health Insurance of ₹ 100,000 for each member of the family
    • No Rainfall Insurance
    • Livestock Insurance up to the market value of the cows
    • Catastrophic, Fire, and Burglary Insurance for value of house and shop
    • Liquidity in MMMF of ₹ 22,500
    Diversify
    Table A16.5: Recommended asset allocation for different levels of risk aversion

    If household does not wish to trade in property then the recommendations are as in Table A16.6.

    Table A16.6: Recommended asset allocation for different levels of risk aversion when the household does not wish to trade in real-estate
    Notes

    1. Saturdays and Sundays are holidays for the nearby school; hence calculations of sales have been taken as one-third of weekdays.

    2. Assumed 30 days per month (22 weekdays, 4 Saturdays, and 4 Sundays).

    3. April and May are summer holidays for the school and hence calculations have been taken as one-third of normal days.

    4. The household members are themselves managing the shop and there is no real cash outflow under this head right now. Hence the imputed cost of labor is being considered here and has been assumed at ₹ 100 per day throughout the year. This would represent the cost that would be incurred in case the household has to hire labor to run the shop.

    5. There are some instances where the family itself consumes a part of the produce. However, this has been considered as an income here to represent the true cost of the activity. The labor put in by family members is mostly supervisory in nature and has been considered at the rate of ₹ 30 per day or 2 hours per day during the season.

    6. The second cow owned by the household currently gives no income. However, for purposes of cash-flow projections, the income from two cows is considered from Year 2 onwards.

    7. The labor put in by family members has been considered at ₹ 20 per day or about 1 1/2 hours per day.

    8. Though there is no cash outflow here, consumption from own farm is considered as an expense here and similarly as an income in the farm activity.

    9. After the children get married, this outflow may not continue. However, health expenses could then substitute for this number and assumed to do so.

    10. Represents an average amount of money spent on social events. It is difficult to arrive at a specific number as the household often spends much more or lesser on these events year on year.

    11. The numbers here are to get a static sense of cash flows. Volatility has not been taken here as LIWE is expected help analyze.

    12. The second cow owned by the household currently gives no income. Hence the income from two cows is considered from Year 2 onwards only.

    13. The assumption made here sit that Pramod would start remitting from Year 2.

    14. Includes interest payments.

    15. See chapter on “Human Capital” for detailed explanation on the calculations. “Insurance Calculator” is available in the Enterprise Simulator Website, available on the SAGE Website.

    16. See chapter on “Human Capital” for a detailed discussion.

    17. Can be thought of in terms of how much relative satisfaction is derived from wealth in an alive-state vis-à-vis in a dead-state. For a person who derives no utility in a dead state, bequest motive is “zero” or D = 0. However, notice that it enters the equation as a multiplicative term and could be equivalently interpreted as a reduction in the probability of death.

    18. Drawn from chapter on “Asset Allocation.”

    19. The remaining years in life of the youngest member of the household taken into account.

    20. Calculations drawn from Chapter on “Asset Allocation.”

    21. Rental expense is taken at 3% on the value.

    22. Discounted to perpetuity to arrive at the present value; the discount rate used is 20% because of very high uncertainties for any business/activity to continue till perpetuity (or even 100 years).

    23. Discounted to perpetuity to arrive at the present value; the discount rate used is 20% because of very high uncertainties for any business/activity to continue till perpetuity (or even 100 years).

    24. Discount rate of 8% has been used which is the real returns expected from Equity; and discounted for a period of five years which is the expected maturity period for livestock.

    25. Household has 3,200 sq. ft of residential land with a constructed area of 400 sq. ft. The land is valued at ₹ 6.19 per sq. ft and the construction is valued at ₹ 150 per sq. ft.

    26. Household owns 1.33 acres of agricultural land. The land is valued at ₹ 270,000 per acre.

    27. It is assumed the current investment in house is just enough to meet the minimum shelter requirement for the household and therefore the short position on residential property is equal to the household's long position in residential property.

    28. Calculated on the basis of land required to suffice the household's food requirements.

    29. Calculations drawn from Table 4C.1 in chapter on “Asset Allocation.”

    30. Detailed explanation can be found in chapter on “Asset Allocation.”

    31. Contents of the report that would be handed over to the household by the KGFS wealth manager.

    About the Editors and Contributors

    Institute for Financial Management and Research (IFMR) Finance Foundation (http://foundation.ifmr.co.in) is a not-for-profit company promoted by IFMR Trust (http://www.ifmr.co.in). They are a mission-driven organization and work toward ensuring that every individual and every enterprise has complete access to financial services. The mission is motivated by a strong belief in the deeply transformative power of finance in unlocking the potential of low-income households and enterprises.

    They identify gaps in the Indian financial system that inhibit the delivery of complete financial services to low-income households and partner with several reputed institutions from around the world to understand the nature of these gaps in a systematic manner.

    They collaborate and work with key partners in addressing the gaps that have been identified by implementing projects in the broad areas of risk origination, risk transmission, and risk aggregation—the three pillars of the financial system. They provide the research framework for the trust and disseminate widely the results of the research undertaken and the projects implemented by the trust.

    Editors

    Bindu Ananth is currently the President of IFMR Trust. She worked with ICICI Bank in the microfinance practice between 2001 and 2005 and was head of the new product development group within the bank's rural finance business in 2007. She is also the founder of Centre for Micro Finance, IFMR. Bindu has an undergraduate degree in Economics from Madras University and master's degrees from Institute of Rural Management, Anand (IRMA) and Harvard University's Kennedy School. She is a Fellow at the Global Economic Society. Bindu has published in Small Enterprise Development Journal, Economic and Political Weekly, OECD working paper series, FAI working paper series, and ADB working paper series. She has also contributed to columns in Wall Street Journal, Forbes India, Mint, and Business Line.

    Amit Shah is a founding member of Wealth Management team of IFMR Rural Finance since May 2009, where he has been closely involved with the design of a new type of rural financial institution called Kshetriya Gramin Financial Services (KGFS). Prior to joining IFMR, he was with HDFC Bank, working with the Credit Policy for Credit Cards & Merchant Acquiring Business for a year. Amit has a master's degree in Rural Management from Institute of Rural Management Anand (IRMA) and is a Commerce undergraduate from PSG College of Arts & Science, Coimbatore.

    Contributors

    Shweta Aggarwal works with the Product Development team of IFMR Rural Finance. She has worked as a research assistant at the Centre for Advanced Studies in India while she was pursuing her undergraduate degree. She graduated with an M.A. in Business Economics from University College of London and has a bachelor's degree in Economics from Northwestern University, Evanston.

    Vaibhav Anand currently works in the Risk Management and Analytics team of IFMR Capital. Prior to joining IFMR, he was working as a Senior Consultant with Financial Services Risk Management division of Ernst & Young, Middle East. He completed MBA (Finance) from IIM Lucknow in 2009 and B.Tech. (Engineering, Physics) from IIT Bombay in 2005. He is a certified Financial Risk Manager (FRM) from GARP.

    Swati Grewal works with the product development team of IFMR Rural Finance and is an insurance specialist. She holds a master's degree in Mathematics from Hansraj College. Prior to joining IFMR, she worked as an Actuarial Trainee with WNS Global Services. She has a keen interest in the development sector and has been associated with various NGOs as a volunteer. She is also pursuing her studies in actuarial sciences from Faculty and Institute of Actuaries, UK.

    Arun Kumar D. works with the product development team of IFMR Rural Finance, specializing in designing asset products for low-income households and rural enterprises. He has also worked in the areas of market intelligence and training design. He had a brief stint with the rural development department of A.P. government before joining IFMR Rural Finance. Arun has completed his graduation in Sociology from PSG College of Arts & Science, Coimbatore and MBA in Rural Management from IRMA.

    Ratul Lahkar is an associate professor at IFMR, Chennai. He has done his PhD (Economics) from University of Wisconsin-Madison, M.S. (Economics) from University of Wisconsin-Madison, and M.A. (Economics) from Delhi School of Economics, University of Delhi. His areas of research interest include Microeconomic Theory, Game Theory, Evolution and Learning in Games, Mathematical Economics, and Industrial Organization. He has several research papers published under his name.

    Nachiket Mor is Chairman of the Boards of SughaVazhvu Health Care and CARE India. He is currently also an independent member of a few other boards, including CRISIL, the IKP Centre for Technologies in Public Health, and Institute for Financial Management and Research (IFMR). Dr Mor has worked with ICICI from 1987 to 2007 in a variety of jobs, including Corporate Planning, Project Finance, Rural Finance and Treasury and was a member of its Board of Directors from 2001 to 2007. From October 2007 to August 2010, he assisted ICICI in setting up a philanthropic foundation, the ICICI Foundation for Inclusive Growth, and served as its founding President. Dr Mor is a Yale World Fellow; has a PhD in Economics from the University of Pennsylvania with a specialization in Finance from the Wharton School; is an MBA from the Indian Institute of Management, Ahmedabad; and has an undergraduate degree in Physics from the University of Mumbai.

    Suyash Rai is Senior Consultant at the National Institute of Public Finance and Policy, New Delhi. Currently, he is a member of the research team for the Financial Sector Legislative Reforms Commission (FSLRC), a comprehensive legislative redrafting initiative to reform the regulation of India's financial system. Prior to this, between November 2008 and August 2011, Suyash lead a team at IFMR Finance Foundation where he was involved in research, dissemination, and advocacy efforts on financial services for rural migrants and micro-entrepreneurs. From May 2006 to October 2008, Suyash worked with ICICI Bank's Social Initiatives Group in the areas of integration of health and nutrition intermediation with micro-finance and other community development structures. Suyash is a graduate in Computer Applications and a postgraduate in Rural Management from the Institute of Rural Management Anand.

    Shilpa Sathe is a member of the Wealth Management team at IFMR Rural Finance and is a part of IFMR Trust since November 2009. She is involved in market research, design, and implementation of products in the KGFS portfolio and in the development of a wealth management framework for its clients. Shilpa has an undergraduate degree in Economics from University of Mumbai, India and is a Master of Science in Applied Economics and Financial Economics from University of Nottingham, United Kingdom.

    Anupama Pant is a veterinary graduate with postgraduation in Rural Management from IRMA. She has worked as consultant with Centre for Insurance and Risk Management (CIRM). She helped in developing risk management tools for dairy and agriculture sector. She studied livestock-related insurance products, problems, and prospects in detail. She also participated in monitoring and evaluating of livestock insurance project on the use of new technology and documenting the learnings from project sites in India. She initiated the project for designing innovative productivity cover for dairy cattle. Various models for micro-insurance delivery including community-based livestock insurance were also evaluated by her.

    Alok Shukla is an engineering graduate from Indian Institute of Technology, Kanpur and an aspiring actuary. He has been associated with weather insurance market since 2006 and has played a key role in underwriting and development of new and innovative products. He has coauthored several publications in the field of agriculture insurance. He is currently associated with Tata AIG General Insurance Company Ltd and handling pan-India business of Cattle and Weather Insurance. Before joining Tata AIG, he headed the Livelihood vertical at Centre for Insurance and Risk Management, IFMR. He started his career with Weather Risk Management Services and product development division. He has delivered many lectures on “Product designing and pricing in weather insurance” at various national conferences and workshops.


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