Risk Management Framework For Micro Financing

Published Date: 02 Nov 2017

The document focuses on helping senior managers and directors of MFIs design a comprehensive and systematic approach for identifying, anticipating and responding to the major risks faced by the MFIs. This document identifies that risk management is an essential element of long term success and hence for financial institutions, to effectively management risk they have to keep the following points in mind.

They have to have systematic approach to evaluate and measure risk so as to identify the risk in the early stage and hence fix it.

A good risk management framework allows management to quantify the risk and fine tune to the capital allocation and liquidity needs to match the on and off balance sheet risks faced by the institutions and to evaluate the impact of potential shocks to financial system or institution.

Having a good information on potential consequences for both positive and negative.

There has been a significant increase in the emphasis on risk management, hence the bank managers and regulators are able to better anticipate risks, than just to react to them. Therefore to foster stronger financial institutions the revised camels approach among US regulators emphasizes the quality of internal systems to identify and address potential problems quickly.

For MFIs proper internal risk management yields to practices designed to limit risk associate with individual product lines and systematic, quantitative methods to identify, monitor and control aggregate risks across financial institutions.

MFIs have been growing and serving large base of customers and also attract more mainstream investment capital and funds, hence they have to strengthen their internal capacity to identify and anticipate potential risks to avoid unexpected losses and surprises. Creating a risk management framework and culture with in an MFI in the next step after mastering the fundamental of individual risks, such as credit risk, treasury risk, and liquidity risk.

A risk management framework is a guide for MFI managers to design an integrated and comprehensive risk management system that helps them focus on most important risks in an effective and efficient manner.

Hence according to the paper risk management framework is a consciously designed system to protect the organization from undesirable surprised (downside risks) and enable it to the advantage of opportunities (upside risks).

THE MAJOR RISKS TO MICROFINANCE INSTITUTIONS ARE,

Many risks are common to all financial institutions, from banks to unregulated MFIs, these include credit risk, liquidity risk, market or pricing risk, operational risk, compliance and legal risk and strategic risk.

Hence most risks can be classified as

Financial risks

Operational risks

Strategic risks.

FINANCIAL RISKS

OPERATIONAL RISKS

STRATEGIC RISKS

Credit Risk

Transaction Risk

Portfolio Risk

Liquidity Risk

Market Risk

Interest Rate Risk

Foreign Exchange Risk

Investment Portfolio Risk

Transaction Risk

Human Resource Risk

Information And Technology Risk

Fraud Risk

Legal And Compliance

Governance Risk

Ineffective Oversight

Poor Governance Structure

Reputation Risk

External Business Risk

Event Risk

Hence considering one risk at a time for literature review, we would get a better idea on various aspects of risk management

Titles of the paper: Risk Management for Microfinance Institutions in South Africa

Name Of The Author: Fanie Jansen Van Vuuren

Objective of the study:

The main objective of this study was to combine and analyse different risks in the microfinance environment in order to create a framework which can assist in the effective management of these risks.

Find out the optimal risk balance

The effective management of risk in the microfinance environment

Prediction of the outcome of microfinance credit transactions

The average profile of a microfinance client in south Africa

Research Methodology:

The research was empirical based on primary and secondary data. The data was collected through questionnaires combined with qualitative data analysis procedures.it is a cross sectional study of a particular phenomenon at a particular time.

The study was based on small medium and large companies in the microfinance industry of south Africa. Post the implementation of national credit act in June 2007.

Classification the microfinance industry:

size

Characteristics

Small

<R5 million in turnover- between one and 10 branches

Medium

<R250 million in turnover between 10 and 100 branches

Large

>R250 million in turnover listed entities

The target population has been divided into 4 categories

The first category is unlisted entities with less than 10 branches.

The second category is unlisted entities with more than 10 branches

The third entity is with banking license

The fourth category includes the microfinance division of some of the traditional banks.

According to the category the questionnaires were designed.

Data analysis was done through pie charts and bar charts and then analysed. The following were the findings of the author.

Five risk tools where to be analyzed and the respondents gave "credit granting policy and customer affordability calculations" the highest priority followed by "internal controls", "debt controls", "debt collecting", "staff training creating loyalty and integrity", "credit scoring models."

The risks that can be involved in non-bank microfinance institutions in south Africa where analyzed and the respondents answered "internal and external fraud", "bad debts", customer migration to competitors or the commercial banks" "regulation of the industry" and "lack of affordable funding."

How well the risk tools used in banks can be applied to the micro financing industry.

Most effective way to lower the overall microfinance risk in south Africa. And the respondents answered "conservative credit granting policy", "improved internal controls", "better loan management system", "better educated staff" , "better collecting on arrears clients."

The biggest predictors of non-payment of new client in microfinance institution in south Africa are " disposable income" "number of loans" " judgments" "employment industry" credit enquiries" "gender", "age", "race".

The biggest contributor to minimize credit risk in a microfinance institution in south Africa is accurate affordability calculation, shorter term loans instead of longer ones , the use of a credit score model, small loan amounts, the analysis of credit bureau information.

The most efficient way to optimize client service in a microfinance institution in south Africa,and the most efficient way to reduce risk in microfinance institutions in south Africa are "real time loan management system"," decentralized credit decisions","cash disbursements to clients", " a call center function", centralized credit decision."

The items on which MFI would spend the most in a financial year could be " staff training, internal audit, independent review on the loan management system", "rewards for fraud tip offs"

The biggest misperception in south Africa regarding microfinance institutions. Are MFI were no affected negatively by the national credit act, MFIs don’t relieve poverty in SA, MFI in SA don’t realy compete with the 4 major banks, MFI in SA is an extremely high risk industry.

The most efficient options to pro- actively manage risk in a microfinance institution in SA are a credit scoring model, build customer relationship with shorter products, extensive training for new staff, to only disburse 30 day loans.

The best predictors of on time payment of clients are correct affordability calculations , a shorter term loan, work reference, a credit score model, a proper and signed credit agreement.

The findings from client information of 3000 microfinance clients in south Africa:

A good client means not in arrears for more than 2 installments

And a bad client means some on who is in arrears for more than 2 installments.

The following table was constructed for 2009 and 2010 year

Type of clients

Number of clients

% male clients

% female clients

% clients with registered addresses

Average loan amount per client

Outstanding balance per client

Average term per client in months

Average installment amount per client

Average number of judgment per client

% of clients with 0 judgments

% of clients with 1 judgments

% clients with 2 or more judgments

Average number of enquiries per client

Average number of loans per client over the period

Average number of open loans per client

Average amount of loan exposure per client

In the paper the author identifies through literature review, identifies various ways to identify the risks related to MFI, ie. The debt equity ratio( gearing risks), interest cover, liquidity risk, market risk(beta) company specific risk, growth, management team, industry comparative performance, theft and fraud and the non-performance of loans.

Then he identifies the relation between the business and credit risk. According to the author, to lower the risk of loans not performing the emphasis should be on quality loans and a risk portfolio not exceeding 5%. The quality of a loan is determined by the probability that the credit decision is right. Hence usually the following are the ways for a proper credit decision.

Rationing credit

Requiring collateral

Screening applicants

Monitoring borrowers

Credit scoring

In this paper he takes up screening of applicants and monitoring borrowers.

Conclusion:

By effectively managing the risk in the industry, south Africa has a good market where in business models can be sustainable. By being able to service the poor through credit lending it is creating opportunities to help build the economy.

A combination of risk tools need to be applied effectively in order to reduce material risks, predict good customer and also real time loan management system with integrated credit scoring models, accurate affordability calculation combined with well trained staff forms the basis of risk management

Research Gap: even though there was a thorough examination of the MFI industry, the author did not look into each risk and tools that need to be used to mitigate the risk.

CREDIT RISK:

1.1.1) Title of the paper: credit risk assessment in the microfinance industry: an application to a selected group of Vietnamese microfinance institutions and an extension to east Asian pacific microfinance institutions.

Name of the author: Ayi Gavriel Ayayi, associate professor of financial economics

Objective of the study:

Is to access credit risk in order to determine internal global scale rating for Vietnamese MFI.

Particular attention is paid to conventional and special credit evaluation metrics due to the unique institutional arrangement of MFIs and the socioeconomic environment in which they operate.

Also this research is to provide an analysis to the Vietnamese MFI so that the donors and investors try making decisions with respect to providing .

The other important aspect of this paper is to help the MFI management teams to evaluate their institution’s performance and hence identify and correct the weakness.

Research methodology:

To achieve the objective, the author has used to Morgan Stanley approach to assessing credit risk in the microfinance industry. The approach was supplemented with his numerical grading system, and hence converted the quantitative and qualitative risk factors on the same schedule hence providing a comparative analysis of the MFIs understudy.

He used Morgan Stanley approach since, it was tailor made for

To institutions that are providing microfinance products

Whose business model mainly revolved around providing micro-loans as financing or micro-entrepreneurs,

It addressed the challenges faced by microfinance industry such as country risk, data availability and minimal default history among FI.

It draws up a methodology of rating the major pioneers in micro financing industry

CREDIT RISK ANALYSIS:

Morgan Stanley credit analysis indicators are tabulated as below

RATING FACTOR

INDICATOR DEFINITIONS

GRADES

Loan portfolio

A1: portfolio at risk=( outstanding loans with arrears over 30 days+ rescheduled or restructured loans)/ total gross loan portfolio

<3;<6;<9;<12;<15; above 15

A2: write offs=total write offs over the last 12 months/average gross lolan portfolio

<2;<3.5;<5;<7;<10; above 10

A3: size of portfolio=gross loan portfolio

>300M;>350M;>100M;>50M;>10>;<10M

A4: loan loss reserves= loan reserves/PAR30

>85;>75;>65;>60;>55; below 55

Profitability, sustainability, operating efficiency

B1:Sustainability= operating income/(financial expenses+loan loss provisions+write offs+operating expenses)

>120;>115;>110;>100;>90;below 90

B2: ROAA=net income/average assets

>3;>2;>1;>0;>-2;below -2

B3: operating efficiency= total operating expenses/average gross loan portfolio

<20;<25;<30;<40;<50; above 50

B4: productivity= number of borrowers/total head count

>200;>190;>170;>145;>130 below 130

Asset and Liability management

C1: leverage= total liabilities/(networth+subordinate debt)

<5x;<6x;<7x;<8x;<9x; above 9x

C2: exposure to foreign currency=(financial debt in non-hedged foreign currency)/total financial debt

<15;<20;<35;<50;<65; above 65

C3: liquidity= (cash+short term inverment)/(gross loan portfolio)

>15;>12;>9;>6;>3 below 3

Management and strategy

D1: quality of senior management and board

D2: strategy and business plan

( including competitive landscape)

D3: quality and support from shareholders and network

D4: HR management

Systems and reporting

E1: quality of management information systems

E2:quality and speed of data feed

E3: quality of reports and distribution/analysis of reports

Internal and operational controls

F1: operational procedures

F2: internal controls

Growth potential

G1: regulatory environment and government involvement

G2: Number and density of micro-entrepreneurs

G3: behavior of micro-entrepreneurs towards microloans

Loan portfolio:

Portfolio at risk: PAR30 value below 3% is ranked best by Morgan Stanley. Low PAR30 value may indicate that the MFI have decided that they don’t want the bad loans in their books, hence they must have written-off any loans that are not being paid for more than 30 days.

Write-offs: the low values of write offs remove the doubt about the good portfolios that have been concluded in the PAR30.lower the write offs, better it is for the ratio according to morgan Stanley rankings. Because write offs of a loan affects the gross loan portfolio and loan loss reserves.

Size of portfolio: the overall growth of the loan portfolio is MFI is a due to the increasing rate of expansion of their number of active borrowers.

Loan loss reserves: the evaluation of MFI’s loan loss reserve levels and policies allows a credit analyst to determine how well an MFI can cope with estimated loan loss and hence gives one an understanding an MFi’s level of financial responsibility. An MFI’s loan loss reserves should ideally cover any anticipated losses. Also an MFI has to satisfy the regulatory standards applied to provisioning as dictated by its legal status.

Profitability, sustainability and operational efficiency: this parameter gives the idea of the financial viability of the MFI. One has to set minimum expected levels of profitability and cash flow sustainability, while taking into account the MFI’s ability to leverage its operational platform and flexibility In the event of deteriorating margins.

Sustainability: this measures the free cash flows, there by reflecting the extent of an MFI’s financial cushion against margin or top line shocks.

ROAA: takes into account taxes and other sources of revenues, including income earned on cash in the bank there by providing a more measure for profitability.

Operational efficiency: this indicated the MFI’s ability to operate efficiently and leverage its infrastructure.

Econometric analysis: for the econometric analysis the MFI for east asia and pacific were analyzed and correlation matrix for 118 different MFI with 14 variable was made and conclusions were drawn.

Conclusions:

Econometric analysis showed that there was no statistical difference in terms of risk management among different types of MFI.

Research GAP: there was no significant conclusion made even after the econometric testing, morgan Stanley approach to credit assessment was used to understand the credit risk of the MFI, the research gap is even though the econometric analysis was done, It was compared with few MFI in limited to East Asia and Pacific rather than comparing with the global players in MFI. It indirectly means the researcher narrowed down his interests to one particular region.

1.1.2) Title of the paper: Determinants of Credit Ratings of Microfinance Institutions in the Former Soviet Union.

Name of the author: PHILLIP MAX GUTHRIE

Objective of the study:

This study primarily seeks to explore two questions.

First, whether ratings respond to individual indicators as the existing literature on both the traditional financial sector and the microfinance sector predict. This is important to determine perception of credit risk of microfinance benchmarking it with other financial institutions.

It tries to determine the optimal model for predicting the credit rating of a MFI given number of independent variable

This tries to use the traditional rating agencies and financial institutions to MFI and specialized rating agencies.

Also it expands little work that has been done on determining contributors to a strong credit rating of MFI and fills a gap in the knowledge regarding the optimal model for predicting an institution’s credit rating

Research methodology:

This research is based on the work from Gutierrez and Serrano.

The work from Gutierrez and Serrano finds 5 key components to credit rating.

Size was found to positively impact the credit rating and is consistent with the research on contributors to ratings of Russian financial institutions

Profitability and efficiency also were identified as positive contributors to credit ratings

Increased risk and lower portfolio quality harmed a firm’s rating.

The work for Gutierrez and Serrano showed that metrics or social performance have no bearings on ratings of MFI.

The rating agencies are primarily concerned with identifying probability of default, not a firm’s impact on poverty alleviation or economic development.

This analysis has replicated the model proposed by Gutierrez and Serrano , to establish the validity of the results for MFI.

But the paper also expands to identify the specific model that best predicts the rating of an MFI.

The paper surveys the rating agencies of the MFIs and identifies the following

Ratings of microfinance institutions

Ratings

ECA

LA

MENA

SA

SSAf

% total

Apoyo and associados internacionales S.A.C

1

0

1

0

0

0

0.19

Class and asociados S.A.

3

0

3

0

0

0

0.57

CRISIL

24

0

1

0

21

0

4.56

Ecuability

2

0

2

0

0

0

.38

Equilibrium

8

0

8

0

0

0

1.52

Feller Rate

1

0

1

0

0

0

0.19

Fitch Ratings

10

0

10

0

0

0

1.9

JCR-VIS credit rating company LTD

1

0

0

0

1

0

.19

M-CRIL

46

6

0

0

21

0

8.75

Microfinanza rating Sri

134

61

52

3

1

14

25.9

MicroRate

131

0

93

2

0

36

24.9

Planet rating SAS

163

23

56

19

1

57

30.99

S&P’s

2

0

2

0

0

0

0.38

total

526

90

229

24

45

107

Percent total

100

17

44

5

9

20

LA: latin America

MENA

SSA: sub-saharan Africa

ECA: Europe and central asia

SSAf:

Planet rating was created in 1999 as a specialized MFI rating agency. It operates in over sixty countries and is headquarters in Paris, France. Planet rating offer pre-rating assesments, credit ratings, social ratings and consulting services to help MFIs improve their performance and management

Planet Ratings uses a

Proprietary GIRAFFE methodology that assessed

Governance

Information

Risk management

Activities and Services

Financing and Liquidity and

efficiency and profitability

Represents a modification of the typical CAMELS system for evaluating banks that measures Capital Adequacy, Asset Management, Management quality, earnings Liquidity and Sensitivity to market risk.

The paper also discusses the ordered probit model methodology used for credit rating:

Using a standard ordinary least square regression was rejected as this method includes inappropriate assumptions about the underlying parameters.

It assumes that that intervals between possible ratings captures differences that are of the same absolute magnitude.

This is equivalent to saying that the risk differential btween a AA- rated agency and a AAA- rated agency is the same as that between a BB and BBB- rated agency

Rating agencies frequently define levels abover which a rating indicates investment quality and below which an institution or security is non-investment grade

The difference between these categories, therefore, cannot be considered discrete, equally spaced intervals.

Credit ratings are ordinal. Hence the appropriate credit rating analysis tool would be multiple discriminant analysis.

This is an improvement on the ordinary least square method. As it takes into point the ordinal nature of the credit rating and treats each rating as a separate category and requires more significant assumptions about the distribution of the independent variables.

The coefficients on the parameters will differ in interpretation from thos associated with the standard ordinary least square method

The positive sign indicates a positive impact on the dependent variable.

The magnitude of impact is not a direct linear relationship.

P(yt = 1) = F(c1 – xt*β),

P(yt = 2) = F(c2 – xt*β) - F(c1 – xt*β)

. . .

P(yt = k - 1) = F(ck-1 – xt’*β) - F(ck-2 – xt*β)

P(yt = k) = 1 - F(c k-1 – xt*β)

The function F is cumulative distribution on function of a standard normal random variable

Parameters are the vector of slop coefficients β and the threshold values c

Conclusion:

This study has contributed to the literature on microfinance in a number of ways.

Donors and lenders can also use the results to target specific areas

Research gap:

He attempted to apply the existing research to some other area, which he was focusing on former soviet union ,using the research from latin America.

Title of the paper: what explains the low profitability of Microfinance Institutions In Africa?

Name of the Author: MURIU, Peter W.

Objective of the study:

To find out why MFIs of other regions have positive profits and those operating in sub-sahara Africa(SSA) economies continue to post negative profits.

Also finds out the determinants of MFI profitability

Find the relation between credit risk, managerial efficiency, capitalization with profitability

Corruption effect on the profitability

There are few observations in the paper that the author has made

Even though there is a high loan repayment rates, only few of the MFIs are profitable.

The MFIs in Africa have on an average consistently posted negative profits compared to other regions.

Hence the two goals of the paper are

Identify on the basis of empirical evidence and in a single static framework, significant determinants of MFI’s profitability.

Investigate if the MFIs can maximize profits or whether they are pursuing additional objective as well

Research methodology:

The research was based on determinants of profitability in MFI sector hence the author has built a model based on the same

MFI industry is characterized by a different function to that of retail banks of any other profit seeking corporate entity. Hence multivariate regression model was used to for the same. The linear regression model that was predicted was based on the literature reviews.

Hence the determinants are

Size: this variable was used to capture the economies of scale or diseconomies of scale in the market.

Age: age is introduced in model to capture the learning effects. From the literature review of the author, older firms have more amount of experience in the same industry hence enjoy higher profits

Capital assets ratio (CAP): high CAP ratio signifies that the MFI is operating over cautiously and ignoring profitable investment opportunities. On the contrary the cost of insurance against bankruptcy can be high for MI with low CAP ratio. The gearing ratio defines the source of business finance to boost financial performance.

Credit risk: this is another determinant in MFI industry. Poor quality of credit reducs the profitability of the MFI. Hence the negative relationship between credit risk and the profitability. This is calculated by taking sum of the level of loans past due 30 days or more and still accruing interest hence portfolio at risk( PAR30) . write off ratio which is the value of loans written off during the year as uncollectible as a percentage of average gross portfolio over the year. Other measure for credit risk is risk coverage(RC) ratio which is measure as the adjusted impaired loss allowance/PAR30. Loan loss reserve ratio this is measured by ratio of loan loss reserves to gross loans.

Efficiency: is expenses management should ensure a more effective use of MFI’s loanable resources. Higher ratios of operating expenses to gross loan portfolio imply a less efficient management. From the literature review we can say that microfinance is a costly business since it has high transaction cost and information cost. This is measured by operating expense/average gross loan portfolio and in robustness tests, cost per borrower can be used

The other two proxies

Macroeconomic environment, inflation and real GNI per capita growth.

Dependent variable is

ROA or ROE

Conclusions:

Efficiency in delivering microfinance is an important determinant of profitability

A major drawback of the negative profitability in SA could be due to the fact that the managerial practices have come down due to the increase in technological innovations.

Higher spending could be due to the same reasons

Research gap:

the main research gap is the analysis was based on literature review rather than actually coming up with original work.

title of the paper: BASEL II- integrated risk management solution

Author of the paper: white paper by BIM

Objective of the paper:

To measure each kind of risk in the Basel II norm through a comprehensive IT solution.

Risk identification

Quantitative risk measurement

Risk mitigation

Minimum capital allocation

Theory in the paper:

The 3 pillars of Basel II are

Pillar I: minimum capital requirement

Pillar II: supervisory review process

Pillar III: market discipline requirements

Types of risk

Credit risk; default by the borrower to repay the borrowings

Market risk: volatility of the bank’s portfolio due to change in market factors

Operational risk: risk arising out of banks inefficient internal processes, systems, people or external events like natural disasters, robbery,etc

Minimum capital allocation for credit risk:

Standardized approach: external credit rating agencies , capital allocation and credit rating are inversely proportional

Internal rating:

Foundation IR approach

Advanced IR approach

In both the methods capital allocated is based on the following 3 factors

EAD exposure at default: amount of facility that is likely to be drawn in default

LGD loss given at default: measure the proportion of lost exposure n default

Probability of default(PD) chances of default in terms of percentage (default- fails to repay borrowings)

Minimum capital allocation for market risk: VAR is used to measure market risk. VAR measures the likely loss in value of a portfolio over a iven time period with specified probability.

Minimum capital allocation for operational risk:

These three methods are used to measure and allocate operational risk.

Basic indicator approach: capital charge should be 15% banks average annual positive gross income over previous years.

Standardized indicator approach: in this approach the bank activities are classified into 8 business line. Each business line is having an exposure indicator which is multiplied by the factor( beta) will give the capital charge for operational risk

Advanced measurement approach: loss distribution approach is of the advanced versions in this approach, in which the impact of significant operation events on various business lines of banks and frequency of occurrences of these events are captured in the form of normal distribution.

Title of the paper: performance of microfinance providers in karnataka

Name Of The Author: BUVAN I.B

Objective of the study:

To study the growth and pattern of microfinance in Karnataka

To evaluate the business performance of the Microfinance providers

To study the impact of micro financial institutions on member enterprises

To identify the constraints faced by the microfinance providers.

Research methodology:

The data for the research was collected from the primary source with respect to amount lent, portfolio lending by microfinance providers, cost and returns involved in each activities, recovery performance under micro financial activities in selected districts was collected with the help of a questionnaire.

Analytical techniques:

Triennium averages: the 1st three years average and the last three years averages was calculated because of plausibility of large number of continuous time series data . the annual average growth in percentages calculated by dividing the changes during the period by number of years in the study period.this is done to study the performance of microfinance activities undertaken by non government microfinance providers

Compounding growth rate analysis: the growth in the number of SHGs credit link, banks loan and refinance of microfinance providers can be assessed by taking for 14 year period

And the compound growth were computed by using exponential function of the form

Yt=ABtUt

where

Yt is SHG credit linked/bank loans/refinance/ number of family assistd/recovery/over dues

A is the time period

Ut= error term

B= 1+G where g is the growth rate

By taking logarithm

We see that log(Yt)=log A+t log B+log Ut

Which is of the form

Qt=a+bt+Ut

Hence g=antilog(b)-1*100

Paired t test: to find out the impact of NGOs on the SHGs the paired t test was done. Which is statistical test for finding the differences in performance of SHGs before and after joining the NGOs who are involved in microfinance.

Impact index: the impact of the NGO on the SHGs was also assessed using the scoring pattern

Impact index=(average scored obtained)/(average maximum scored to be obtained)

Conclusions:

The pattern of growth of SHGs in the state 1992-1993 to 2005-2006 and that the importance of SHGs has increased in the lives of the poor people and that the microfinance may also be possible because of refinance support provided by the apex level institutions involved in microfinance.

The total amount of loans as expanded considerably through NABARD especially from selected villages.

Title of the paper: the ACCION CAMEL Model

Name of the Author: Sonia B Saltzman, Darcy Salinger

Objective of the paper:

The objective of the paper is to design and test the CAMEL’s model for Micro financing Institutions

Research methodology:

Based on a questionnaire , adjusted financial statements and interviews with the MFI’s management and staff, a rating of one to five s assigned to each of the CAMEL’s 21 indicators and weighted accordingly.

The following are the definition of each area

Capital Adequacy. The objective of the capital adequacy analysis is to measure the financial solvency of an MFI by determining whether the risks it has incurred are adequately offset with capital and reserves to absorb potential losses.

There are three indicators:

First one is leverage, explains the relationship between the risk-weighted assets of the MFI and its equity.

Second one is ability to raise equity, a qualitative assessment of an MFI’s ability to respond to a need to replenish or increase equity at any given time.

the third, is adequacy of reserves, is a quantitative measure of the MFI’s loan loss reserve and the degree to which the institution can absorb potential loan losses.

Asset Quality.

The analysis of asset quality is divided into three components

PORTFOLIO QUALITY: Portfolio quality includes two quantitative indicators: portfolio at risk, which measures the portfolio past due over 30 days; and write-offs/write-off policy, which measures the MFI’s adjusted write-offs based on CAMEL criteria

PORTFOLIO CLASSIFICATION SYSTEM: entails reviewing the portfolio’s aging schedules and assessing the institution’s policies associated with assessing portfolio risk.

FIXED ASSETS: fixed assets, one indicator is the productivity of long-term assets, which evaluates the MFI’s policies for investing in fixed assets.

MANAGEMENT:

Five qualitative indicators make up this area of analysis:

Governance

human resources

processes, controls, and audit

information technology system

strategic planning and budgeting

EARNINGS:

Three quantitative and one qualitative indicator to measure the profitability of MFIs:

Adjusted Return On Equity: measures the ability of the institution to maintain and increase its net worth through earnings from operations

Operational Efficiency: measures the efficiency of the institution and monitors its progress toward achieving a cost structure that is closer to the level achieved by formal financial institutions.

Adjusted Return On Assets: measures how well the MFI’s assets are utilized, or the institution’s ability to generate earnings with a given asset base.

Interest Rate Policy: to assess the degree to which management analyzes and adjusts the institution’s interest rates on microenterprise loans (and deposits if applicable), based on the cost of funds, profitability targets, and macroeconomic environment.

Liquidity Management:evaluates the MFI’s ability to accommodate decreases in funding sources and increases in assets and to pay expenses at a reasonable cost. Indicators in this area are liability structure, availability of funds to meet credit demand, cash flow projections, and productivity of other current assets. Under liability structure, CAMEL analysts review the composition of the institution’s liabilities, including their tenor, interest rate, payment terms, and sensitivity to changes in the macroeconomic environment.

The paper also drafted the CAMEL’s indicators with weightings

Quantitative Indicators

Qualitative Indicators

Capital Adequacy (15%

Leverage (5%)

Adequacy Of Reserves(5%)

Weightings (%)

Ability To Raise Equity(5%)

Asset Quality (21%)

Portfolio At Risk(8%)

Write Offs/Write Off Policy(7%)

Portfolio Classification System (3%)

Productivity Of Long Term Assets(1.5%)

Infrastructure(1.5%)

Management(23%)

Governance/Management (6%)

Human Resources (4%)

Processes, Controls, And Audit (4%)

Information Technology System (5%)

Strategic Planning And Budgeting( 4%)

Earnings (24%)

Return On Equity (5%)

Operational Efficiency( 8%)

Return On Assets (7%)

Interest Rate Policy (4%)

Liquidity Management (17%)

Productivity Of Other Current Assets (2%)

Liability Structure( 8%)

Availability Of Funds To Meet Credit Demand (4%)

Cash Flow Projections( 3%)

Total(100) 47%

53%

TITLE OF THE PAPER: Role Of Microfinance Interventions In Financial Inclusion: A Comparative Study Of Microfinance Models

NAME OF THE AUTHOR: Deepak Barman, Himendu P. Mathur and Vinita Kalra

OBJECTIVE OF THE PAPER:

To study the relationship between the level of indebtedness to moneylenders and the type of microfinance model through a case study in Varanasi, U.P.

Comparing two microfinance models prevalent in the research area

Research methodology:

This survey was conducted among 59 households of twelve villages covering four blocks of the selected district. Primary data on different socio-economic aspects of the households and details of micro-financial services availed by them were collected directly from the clients through the structured questionnaire and personal interview. Qualitative information was collected through Focus Group Discussions (FGDs) and semi-structured interviews of the bankers, NGOs and MFIs operating in the area to understand the supply-and demand sides of the problem of microcredit in the selected research area. The collected data are subjected with the chi-square statistical test in order to determine if there is significant variation in the tendency to borrow from the moneylenders among clients of SHG and MFI model of microfinance. The test is applied when one has two categorical variables from a single population. It is used to determine whether there is a significant association between the two variables i.e. indebtedness to moneylender and being client of particular type of microfinance model.

Conclusions:

The authors conclude that the level of indebtedness to moneylenders is higher in the case of clients of Microfinance Institutions (MFI) model and without complete information on the credit-worthiness of borrowers, MFIs may contribute to the over-indebtedness of their clients as well as damage in their performance.

Research gap: there could be more number of variables which could affect the indebtedness to money lenders.

Title of the paper: cost control in microfinance: Lessons from ASA

Name of the author: Saleh Khan , Ashta, Arvind

Objective of the paper:

The main aim of this paper is to provide with a literature review on previous work n transaction costs including operating costs, in microfinance.

The second part of the paper describes the research modalities followed by a section which provides the findings based on empirical evidenvr.

The depth into one case study of lean cost management

Provides managerial recommendations.

Research methodology :

The data was collected from Microfinance information exchange(MIX).the parameters considered were

Average loan balance outstanding per borrower in USD

Gross loan portfolio in USD

Number of depositors

Cost per borrower in USD

Operating expenses as a percent of the gross loan portfolio

Nominal yield on gross loan portfolio

And based on these data longitudinal analysis was conducted from the data from MIX and analysis of top 10 MFIs, which accounted for about 92% of the clients over the past 10 years.

Time series data for outreach was presented and the top 3 mFIs are in the league of their own and are about equal in size of growth rates.

Conclusion:

There are number of factors that attribute to an MFI having lean operation and being cost effective.

The operating costs differ significantly for different institutions and can be attributed to achieving economics of scale in operations

They saw that it is possible to adopt cost effective operating structure while operating in same service space as other less efficient MFIs

Research gap: they used the existing literature to find out the costs that the MFis incur rather than using primary data to find out about the different types of costs.

Title of the paper: Credit Elasticities in Less-Developed Economies:Implications for Microfinance

Name of the author: Dean S. Karlan and Jonathan Zinman

Objective of the paper:

Test the assumption of price inelastic demand using randomized trials conducted by a consumer lender in South Africa.

Research methodology:

identify demand curves for consumer credit by randomizing both the interest rate offered to each of more than 50,000 past clients on a direct mail solicitation, and the maturity of an example loan

The sample frame consisted of all individuals from 86 predominantly urban branches who had borrowed from the Lender within the past 24 months, were in good standing, and did not currently have a loan from the Lender as of 30 days prior to the mailer.

pilot-tested in three branches during July 2003 (wave 1), and then expanded the experiment to the remaining 83 branches in two additional waves that started with mailers sent in September 2003 (wave 2) and October 2003 (wave 3)

conclusion:

the randomized field experiment to estimate price and maturity elasticities of demand for consumer credit. The sample includes former borrowers from a major, for-profit, South African consumer microlender to the working poor.

In the Lender’s case, the cost of reducing interest rates (lost gross interest revenue on inframarginal loans) slightly exceeded the benefits (increased gross revenue from marginal borrowing, increased net revenue from higher repayment rates)

title of the paper:help, risk and deceit: microentrepreneurs talk about microfinance.

Name of the author: Robyn Eversole

Objective of the study

To find the relation between the ostensibly commercial transactions which converted into complex assumptions about the social development, external assistance and power

To illustrate the divide between developed and developed in their shared quest to help business grow and concludes that building strong lending institutions does not automatically translate into broad based benefits for micro entrepreneurs of their businesses

Conclusion:

While international agencies prioritise the developemt of sustainable microfinance organization to provide loans to the micro and small businessness, the business people themselves may see their own interests as quite different for those of the organisations meant to serve them.

The reasons for this were many such as loan products that were suited to only certain kinds of businesses, businesses which were ill equipped to take out loans. Expectations that help equated to short term assistance and flexible repayment schedules and assumptions that corruption was likely to be rampant whenever development money arrived

Title of the paper: Exploring Household Microfinance Decisions: An Econometric Assessment For The Case Of Ghana

Author of the paper: Lindsey R. Barone

Objectives of the paper:

To analyze the relationship between household financial instruments by determining the link between insurance coverage and household savings.

Research methodology:

The data set used for the purposes of this paper uses data from 351 households captured at one period in time. Because the data is not dynamic, a two-step approach is used to analyze the relationship between insurance coverage and savings at the household level.

Variables :

Insurance purchase:

Health Insurance

Life Insurance

Old age Insurance

Other Insurance

Savings:

Total HH savings

Shocks to house holds

Weather shock

Crime shock

Business shock

Loss of job

Death of worker

Illness of worker

Family shock

Severity of shock

Risk perception

Share of ill

Share of injured

Additional risk measures:

Share of employed

Share of dependents

Avg HH age

Life expectancy

Risk aversion measure

Risk aversion measure

Income

Controls:

Female head

Age (in years)

Education (in years)

HH earnings (occupational)

HH additional earnings

Distance to health provider (in km)

Vaccinations

Private Hospital

Health center1

Chemist/Pharmacist

Government Hospital

Mission Hospital

The sample mean , std dev of each of the variables was taken and analysed based on the data.

Regression model of the nature

P( Y=1, Health insurance) = α+β1 savings+β2 life insurance + β3 old age insurance +µ

Was constructed and regression analysis was done

Conclusion :

There are a variety of reasons to support this claim. Financial tools, when used in unison, provide households with options for managing assets

Prior to a shock, households can allocate income between savings and insurance products to help protect against potential risks.

The findings of this paper suggest expanding access to products increases use through simple exposure.

households use saving mechanisms and insurance products, they appear to increase their use of both products

title of the paper: foreign exchange risk management practices of microfinance institutions.

Author of the paper: Peter R Crabb

Objective of the paper:

to review the current practices in the management of forex risk for and by MFIs.

The advantages and disadvantages of these practices

Research methodology:

Current practices:

The standard framework of the Forex risk measurements are

MeasuringVAR to exchange rate fluctuations

Purchasing derivatives of adjusting portfolios to offset this risk

Continuously monitor the risk position

Alternative practices:

Diversify both the source of debt capital and the use of debt capital

Insuring the risk of devaluation in the network

Using currency swaps

Conclusions:

Three general conclusons can be drawn from this study of Forex exchange ris and MFIs

First need addistional funding to meet demands and debt capital is most likely source for funding

Second Forex exchange rate risk is significant and though it is only one factor in a decision to lend to a MFI , it is a strong deterrent

The risk devaluation against most major currencies such as the US dollar nd the Euro is high and it is in these currencies that any new debt capital is likely to be denominated

The exisiting Forex practices are prohibitively expensive, either to the client or the institution

Research gap: the potential intermediaries or counter parties to any potential currency swap agreements were not discussed in the paper

Title of the paper: impact analysis of microfinance in Nigeria

Name of the author: Babajide Abiola

Objective of the paper:

To apply the financing constraints approach to study whether microfinance institutions improve access to credit for microenterprise in Nigeria or not

Research methodology:

This paper is based on generating financial constraint theory model thing or an event.

Pri = (1+ exp(-λi))-1, where λ is linearly dependent on the variables hypothesized to affect the probability: λi = α + βXi.

The probability thus varies from 0 to 1 (λ = ±∞), and the model is simplified by rearranging it into a log of the odds,

ln(Pi /(1 - Pi)) = α + βXi.

which, for examples consists of individual outcomes, and can be estimated with maximum

likelihood. Interpretation of the coefficients can also be done by reverting back to the probabilities.

Thus,

Pr(IFA = 1) = f(α + β1IF + β2IO + y/Z)

where IFA is the decision to invest in fixed assets, IF is the variable for internal funds capital;

IO is the investment opportunity variable, and Z is a vector of variables that capture various characteristics of the enterprise and the states in which it operates.

Firms without investment opportunities would not invest even if they had capital. Thus, control for investment opportunity (IO) and separated it from the effect of internal funds (IF).

Conclusion :

The paper uses the financing constraints approach to study the impact of microfinance on access to credit for microenterprises in nigeria

The model contained ten independent variables (average profit, market & skill, hired employee, asset loan, enterprise age, internally generated revenue, business location, entrepreneur gender and availability of investment opportunity).

They show that MFBs improved access to credit in locations where more MFBs offered financial products because investment in local microenterprises was less sensitive to availability of internal funds in unconstrained location, than investment in microenterprises in locations where microfinance activities were limited or non-existent and where micro entrepreneurs had to rely more on internal funds for investment.

Popularity of microfinance forces MFBs to be more transparent and thereby decreases the cost of assembling a database with MFBs branch distribution, therefore making the financing constraints approach more attractive for use in the future.

Risk category

Subcategories

Specific risks

Financial risk

Credit

Loan portfolio(internal)

Interest rate (internal/external)

Loan enforcement practices(internal)

Loan rescheduling and refinancing practices

Market

Prices(external)

Markets(external)

Exchange rate(currency)(external)

Value chain(external)

Liquidity

Cash flow management issues(internal)

Operational Risk

Transaction( internal)

Fraud and integrity(internal)

Branch level authority limits on lending

Technological (internal)

Information technology

Human resource(internal)

Staff training, operational manuals

Legal and compliance(internal)

Operational audits, financial audits

Environment (external)

Specific environmental impacts

Strategic risks

Performance(internal)

Generating profits and returns on assets and on equity to attract investors

External business(external)

New financial sector laws

Reputational(external)

Competitive pressures(existing, new actors)

Governance (internal)

Changes in regulatory practices(licensing and reporting requirements)(external)

Lack of board consistency and direction(internal)

Country (external)

Relationships with donors and government programs(eternal)

Producer risks

Experience

Technology

Management ability

Transactional risk: transactional risk is the risk with individual loans. MFI mitigated transaction risk through borrower screening techniques, underwriting criteria and quality procedures for loan disbursement, monitoring and collection

Title of the paper: The Development Perspective of Finance and Microfinance Sector in China: How Far Is Microfinance Regulations?

Name of the author: M. Wakilur Rahman

Objective of the paper:

The paper reviews the development process of bank and microfinance sector in China and presents their regulatory status.

Research methodology: since this paper is a review of existing literature there is so quantitative research methodology.

Microfinance structure and their services Since the first microfinance seed was planted in China, a vast number of different types of microfinance operators have appeared within the Chinese market.

Generally, there are three broad categories of microfinance service providers. These include-

Micro-credit by financial institutes This category mostly includes state own formal microfinance service providers i.e. ABC, ADBC, RCCs, Rural

Commercial Bank, Rural Cooperative Bank, Postal Savings, China Development Bank (CDB), MCC, VTB, LC, andRMCCs. The microfinance market share is dominated by these providers.

Micro-credit by NGOs & international organizationsThe service providers are- NGOs, international organizations and social organizations. The internationalorganizations have been providing financial services as project based with the collaboration of government agencies.They also incorporate different services beside micro-credit i.e savings, training in project sites. NGO lending services have covered countrywide and large volume of business.

Micro-credit by Government agencies This category provides micro-credit focusing on the government poverty reduction program. For instance, Urban Credit Bank (UCB) was established to support laid-off workers which ultimately expanded micro-credit services to urban areas.

Only NGO-MFIs and MCCs are non-financial institutions and consequently not allowed to work with savings or receive funding from commercial banks –thus, preventing them from enjoying economies of scale Even the lending companies are also not allowed to work with savings. In addition, the three newly created rural financial institutions (VTBs, LCs, and RMCCs) as well as MCCs are subjected to geographical restriction. The traditional collateral system for micro-financing still exists particularly for micro-lending companies, lending companies, postal saving banks, MCCs, and VTBs. Even RCCs and UCCs have followed a special kind of collateral to credit disbursement. RCCs required collateral for large loan amounts and UCCs required companies guarantee. On the other hand, the donor funded projects (UNDP, UNFPA, UNICEF, Heifer Project, World Vision, Oxfam Hong Kong and CIDA) are allowed to providing micro-credit services by collaboration with government departments or agencies having certain conditions.

Conclusions :

that the banking and microfinance services have expanded and improved gradually. Hence, the banking sector is close to the maturity stage while the microfinance sector is still at learning stage.

CBRC is the sole institute to deal with policy regulations for banks and microfinance service providers which may contradict to handle different goal oriented institutes (Banks and MFIs run their business in different perspectives).Author recommended to the concerned authorities to have a balanced policy regulation for the microfinance

Title of the paper: Sustainable Microfinance: The Impact Of Pay For Performance On Key Performance Indicators

Name of the author: Jay Jiwani

Objective of the study:

This study investigated the relationships between pay-for-performance incentive programs and loan officer productivity in microfinance institutions (MFIs).

Loan officers’ performance is measured by five key performance indicators:

new borrowers,

portfolio value,

average loan size,

arrear rate,

default rate.

Research methodology :

The independent variable is the loan officer’s financial incentive (the percentage of salary that is based on performance). Five dependent measures (performance outcomes) have been examined:

number of new borrowers,

value of portfolio,

average loan size of the borrowers,

number of borrowers in arrears (loans overdue > 30 days),

number of borrowers in default (loan overdue >90 days).

Hypothesis:

H1a: Loan officers with higher incentives will have more new borrowers.

H1b: Loan officers with higher incentives will have a higher portfolio value.

H1c: Loan officers with higher incentives will have a larger average loan size.

H1d: Loan officers with higher incentives will have lower arrear rates.

H1e: Loan officers with higher incentives will have lower default rates.

The second research question uses survey questions from supervisors of loan officers, and loan officers to assess the impact of the productivity level of MFIs with financial incentives and MFIs without financial incentives: Is there a difference between the productivity level of loan officers at MFIs with financial incentives and MFIs without financial incentives

H2a: Loan officers with incentives will have more new borrowers.

H2b: Loan officers with incentives will have a higher portfolio value.

H2c: Loan officers with incentives will have a larger average loan size.

H2d: Loan officers with incentives will have lower arrear rates.

H2e: Loan officers with incentives will have lower default rates.

Conclusion:

All five hypotheses suggested that there would be an increase in productivity with higher incentives.

Results indicated that the number of new borrowers was related to the size of the incentive program. The negative correlation between the number of new borrowers and the size of the incentive program indicated that MFIs with larger incentive programs had loan officers with a smaller number of new borrowers in each month, and overall. There were no relationships between the size of the incentive program and any of the other performance measures

Title of the paper: Savings, Lending Rate and Skill Improvement in Microfinance Operating Through Public-Private Cooperation

Name of the author: Amit Kundu

Objective of the paper:

microfinance program through joint liability credit contract is explained with the help of a two-stage game when the program is operated by a non-motivated NGO with the help of a commercial bank and government.

Research methodology

Initially, the author assume that two homogeneous members belong to the same village form SHG on the basis of joint liability only for two periods.

The group is formed by the initiative of an NGO whose basic activities are:

Motivating local housewives to form SHG;

Collecting savings (contribution) from them in installment and giving them technical knowledge for skill improvement of the participants at the initial stage;

Bridging the gap between the group and the bank as well as the government;

Maintaining the group corpus;

Collecting subsidy and cash credit from the DRDA and bank respectively;

Disbursing credit simultaneously to both the members and recovering credit from the members

Generating profit after performing all these activities at the end of the second period.

Government Subsidized Microfinance Program in the Total Absence of Social Sanction:

Suppose each member of the group is willing to contribute (save) x amount in each installment and each member has to contribute 2t times in each year. The amount saved by each group member in each installment is deposited in the office of the NGO and the NGO deposits the amount in the linked commercial bank.

assume that before getting first credit from her group, each member has to save t times regularly. During this period, she is also getting skill-training from the NGO without spending any amount. Total amount accumulated in the group after contributing for ‘t’ times by each member is:

2tx(1 + i) = 2X(1 + i), where 2tx = X.

The NGO withdraws 2X amount from bank and distributes that equally among the group members as credit against a rate of interest rˆ.

The income earned by each member after utilizing the microcredit as the working capital can be expressed as:

Ym = ƟX, where mϵ {1, 2} ...(1)

Here ÆŸ is the degree of technical knowledge gained by each group member after group formation from the NGO and ÆŸ > 1. It is also assumed that the husbands of both the members are earning members and ready to contribute their entire income for their family.

The annual earning of the husband of each group member is W and 2x < W. At the end of the first stage, we have four possible levels of consumption of both the member households. If the group member is well-behaved and is ready to repay her own loan with interest at the end of the year, then the consumption of the non-defaulter member household will be:

CmGR = W+ƟX- 2X+ X(1+ rˆ)

where m ϵ{1, 2}

Conclusions:

It reestablishes the fact that even in the presence of government subsidy in microcredit program under joint liability through formation of SHG, social sanction or depriving the members from enjoying further benefits from the government still plays an important role of security at the time of repayment of loan

It is also proved that if the group members are not equally powerful in the society, then in the second stage of the game, the powerful member applying her social influence and taking advantage of joint liability may force the less powerful member to repay her loan with interest and enjoy a free ride.

So positive assortative matching, both from the economic as well as social point of view, is necessary at the time of group formation and that should be maintained in both the periods to keep repayment rate 100%.

Title of the paper: Microfinance and development: risk and return for a policy outcome perspective

Name of the author: Gail Arch

Objective of the study:

This paper address microfinance- financial services products including credit loans and insurance which encourage productive and entrepreneurial activity for the marginalized often unbanked also known as the poverty market

This paper provides the overview of the microfinance market space, its industry players and it addresses current issues in development policy

Research methodology:

This is a descriptive paper hence the author has considered various scenarios and analyzed the microfinance market

Conclusion:

The problem with the financial system of Kenya is that it was built as if the structure of the economy was that o England or the US

In reality all most all the people are small farmers, vendors and informal sector industr