streamlining individual lending evaluations at … standardized margins and household expenses for...

Swadhaar Finserve Pvt. Ltd.

Evaluations at SwadhaarAppendix 2 to

Streamlining Individual LendingEvaluations Project Report

Streamlining Individual Lending

2

• The Need for an Individual Microenterprise Loan Product

• Swadhaar’s Individual Lending Process

• Swadhaar – Unitus Project Objectives

• Analysis of Key Tools / Processes

o Tailoring Products to suit Business Needs

o Developing a Preliminary Client Scoring Model

o Standardization of key metrics in capacity evaluation

o Client’s business growth indicators

Contents

3

The microenterprise segment is not being served effectively by current banking OR group lending products – thus, there exists a large gap for flexible individual business loan products

* For further information, please refer to APPENDIX 1 - Background Note on Individual Lending

Micro entrepreneurs need… Commercial Banks offer… Microfinance - Group Loans offer…

Flexible loan amounts between

Rs 25,000 – Rs 2,00,000

Loan amounts typically starting at > Rs 5,00,000

Rigid loans based on cycle, between Rs 5,000 – Rs 30,000

Shorter loan tenure for working capital requirement

Loan terms typically 12 months or greater

Loan terms typically 12-24 months

Option to foreclose loans based on business seasonality and cash flows

Available, generally for a penalty/fee

Renewal loans only when the whole group closes, and not as per individual requirement

Fewer documentation requirements Require several documents such as IT Returns, and often collateral

Low documentation requirement

Flexibility in payment mode – Doorstep cash collection/ PDC/ ECS

Require Post Dated Cheques or bank transfers

Need to participate in time-consuming group meetings

The Need for an Individual Microenterprise Loan Product – Serving the Missing Middle*

4

Initiate Renewal

Loan

Evaluation

Loan

Approval

Loan

Disbursement

Loan

Repayment

Willingness to Pay

Capacity to Pay

Customer Relationship Officer (CRO)

CRO & Branch Manager

(BM)

Branch Mgr/ Area Mgr

Admin Assistant

CRO

20-30 mins 2 – 2.5 hours 15-20 mins 20-30 mins 5-10 mins per

collection

Loan evaluation is the most critical and difficult part of the lending process to

cover individual risk – it is important to explore tools to optimize this process

Promotion

Swadhaar’s Individual Lending Process

5

Objectives of the Swadhaar-Unitus Project

• The primary objective of the Swadhaar -Unitus project was to analyze a selection of available data from Swadhaar’s existing client base (across 4 years of operations) and develop tools to simplify and standardize the individual lending evaluation process with an aim to increase efficiencies and enhance risk mitigation.

• The key tools/processes that were explored in detail as part of this project were:

1. Tailoring products to suit the needs of specific business sectors

2. Identifying a suitable methodology to implement a preliminary credit scoring model for better client selection

3. Using standardized margins and household expenses for client’s capacity evaluation

4. Using key business indicators to track client’s business growth across cycles

• Each of these processes is discussed in greater detail in the following sections


2. Identifying a suitable methodology to design a preliminary credit scoring model for better client selection


4. Using key business indicators to track client’s growth across cycles

Analysis of Key Tools / Processes

7

Benefits of tailored products

There are several benefits of tailoring products to the needs of specific business sectors:

• Effective Marketing

• Field officers can readily identify the target segment for the product and can deliver a more focused/relevant sales speech

• Reduced evaluation time

• As critical aspects of the business are already considered in the product features, evaluation processes can be shorter

• Increased client satisfaction

• Products are more customized to client’s business needs, thus leading to increased satisfaction levels

• Clients are more likely to avail repeat loans, thus improving customer retention

• Minimized Risk

• Specific business risks are addressed through product eligibility criteria and other loan features

8

Findings: Business Categories by sector and activity

Based on similarities found, businesses were categorized across six major business types.

Sector Business Type Example of Businesses

Trader and Service

1. Semi mobile businesses

- Selling vegetables, fish, flowers, toys, plastic - Selling ice cream, candies, juices - Food stalls (chat, samosas, Chinese, vada pav, tea etc)

Trader 2. Small businesses but at fixed location:

- Selling: grocery items, footwear, masala, meats (chicken, mutton, eggs, etc), cutlery items, sari

Service 3. Small businesses but at fixed location: Services related

- Services: beauty parlor, barber shops, service stations, repair shops (watches, electronics etc.), tailor, photography

Service 4. Small businesses but at fixed location: Food related

- Fixed food outlets: restaurants, tea shops, sweets

Trader 5. Wholesalers/large retailers

- Selling: clothes (cut pieces, materials, readymade garments, lingerie, socks, etc.), Kirana shops, footwear

Manufacturer 6. Home based businesses/small factory

- Manufacture of shoes, bangles, imitation jewelry, piece-rate tailors

Trading

9

Findings: Business Characteristics

Business Type Monthly Sales

(in INR)

Monthly Cash Flows:

Inventory rotation

Business Assets #of employees

on Cash on Credit Inventory Furniture/Tools Others


30,000 - 60,000

100% 0% 3 days - 1 week

80%

10% 10% None (mostly family members)

2. Small businesses but at fixed

50,000 - 1,00,000

~80%

<20% 1 week - 3 weeks

70% 20% 10% One to two employee + family members

3. Small businesses but at fixed location: Services related

30,000 - 50,000

~90% <10% Own Inventory: negligible

10% 80% 10% None

4. Small businesses but at fixed location: Food related

50,000 - 1,00,000

80% <20% 1 week - 3 weeks

60% 30% 10% None

5. Wholesalers /large retailers

1,00,000 - 3,00,000

~60% <40% 4 weeks - 6 weeks

90% 10% NA One to three employees

6. Home based businesses/small factory

50,000 - 3,00,000

<10% ~90% 4 weeks - 6 weeks

80% 10% 10% Up to 10-20 workers paid on per piece basis

location: Trading

10

Recommendations: Product Features

Business Type Loan Requirem

ents

Cycle Loan Amount (in INR)

Loan Term (months)

Seasonality/Moratorium

Repayment Frequency & Method

Document Proof

Collateral


Working capital loans and business asset loan

First 10,000 to 15,000

6-9

None Daily or Weekly, repayment via cash

ID proof Residence proof

Co-signor required

Second 15,000 to 20,000

9-12

Third 15,000 to 20,000

9-12

2. Small businesses but at fixed location:

Working capital loans and business asset loan

First 15,000 6-9

None Weekly or Fortnightly, repayment via cash

ID proof and any address proof (residence/business)

Co-signor required

Second 20,000 to 25,000

9-12

Third 25,000 9-12

Based on a detailed analysis of business cash flows, and using Swadhaar’s current experience in individual lending, standardized product features were developed for each category:

Trading

11



ents


Loan Term

(months)



Document Proof

Collateral

3. Small businesses but at fixed location: Services related

Working capital loans

First 15,000 6-9



Co-signor required

Second 20,000 to 25,000

9-12

Third 25,000 9-12

Building business assets

First None NA

Second 20,000 to 30,000

9-15

Third 30,000 9-18

4. Small businesses but at fixed

related


First 15,000 6-9



Co-signor required

Second 20,000 to 25,000

9-12

Third 25,000 9-12


First None NA

Second 20,000 to 30,000

9-15

Third 30,000 9-18

location: Food

12



ents


Loan Term

(months)



Document Proof

Collateral

5. Wholesale/ Working capital loans

First 30,000 to 50,000

6 None Monthly, repayment via cash/cheque/ECS. From second cycle onwards via cheque/ECS)

ID proof and any address proof (residence or business)

10% upfront margin

Second Upto 65,000 6-9

Third Upto 80,000 6-12

Fourth Up to 1 lakh 6-12


None (No significant demand for an asset loan)

6. Manufacturing: Home based

factory


First 30,000 to 50,000

6 During lean period or at beginning of loan term: only interest has to be paid, principal to be adjusted in remaining months. Moratorium maximum of 3 months.

Monthly repayment via cash/cheque/ECS. From second cycle onwards via cheque/ECS)

ID proof and any address proof (residence or business)

10% upfront margin

Second Upto 65,000 6-9

Third Upto 80,000 6-12

Fourth Up to 1 lakh 6-12


First and Second

None NA

Third 50,000 to 1 lakh

6-12

Fourth 50,000 to 1 lakh

9-18

businesses/ Small

Large retailers

14

Overview of Credit Scoring

• Why Scoring

• Swadhaar is looking for ways to further streamline its credit process from the application stage to the disbursement stage to make its products/processes customer friendly and efficient, and to mitigate risk in client selection

• Where does Scoring fit in the Credit Process

• Scoring of clients would enable Swadhaar to prioritize client visits for renewals and collections and to offer products based on their risk categories. Scoring can also be used to select clients at time of application

• Swadhaar’s experience with scoring • Swadhaar has implemented a Renewal Score as part of the process to select clients

for renewals. However, it hasn’t been able to implement a score for client selection as existing clients haven't completed sufficient number of cycles with Swadhaar to build a large enough database

15

Benefits of Credit Scoring

A credit score would allow Swadhaar to categorize its customers as high, medium or low risk. This information could then be used to:

•Determine what products to offer

• Loan amount, term, interest rate, etc. when an applicant applies for a loan

•Prioritize visits to be made

• At the time of renewals, our credit score informs us which clients are our ‘best’ clients and hence can be renewed earlier

•Improve loan officer productivity and efficiency

• An MIS segregating our clients allows for closer monitoring of renewals and provide better service to more deserving clients

16

Methodology to develop a Credit Scorecard

Credit Scoring – Three types of methods may be used

1. Expert Methodology

Built using the knowledge of an ‘expert’ or a group of ‘experts’. Based on their past experience/learning, experts identify variables and assign weights to these variables

2. Combination of Expert selection and Data analysis/validation

Expert selection card is used to identify variables and data analysis to check, correct/adjust and validate the score

3. Statistical Methodology Using a regression model to examine how a given variable is affected by another

variable(s)

17

Development of selection scorecard using the expert methodology

Steps followed in this process are as follows

1. Identification of variables: A group of experts is asked to identify variables to be

considered when evaluating a client’s willingness to pay

2. Assigning weights to variables:

a. Each variable is given a score from 1-7, (1=insignificant, 4=neutral, 7=critical) by

each expert; the weighted score from all experts gives the significance of the

variable.

b. Variables are selected and weighted based on the weighted expert scores.

c. The attributes (“values”) of each variable are then scored by the experts to

identify how they affect the client score (e.g. if education is the variable, then its

attributes would be illiterate, public school, private school or college); each

different attribute would get a score such as -10, 0, 5, 10.

3. Calculating client score: Expert scores are constructed viz:

a. For a client, the scores from all variables are added to get the final score.

b. The higher the client’s final score, the lower the risk category s/he represents

18

Development of the selection scorecard (1/2)

1. Identification of variables: 29 variables were proposed, e.g. Demographics (e.g. age, civil status, education, gender), Geo-demographic stability (e.g. business & home

2. Assigning weights to variables: Given below is an example how the final score is calculated for each variable and feature/attribute:

a. All variables received a score from the experts; e.g. the age variable received the average score 4.8 by the experts (4 being neutral, meaning that age is significant)

b. 11 variables were selected for the final score, e.g. the age variable was selected for the score based on the score given; variables selected included

• Age and gender

• Civil Status

• Home ownership

• Number of dependents

• Etc.

c. Attributes and scores were assigned for each variable;

e.g. age attributes/scores:

Age attribute range

Score

18 – 30 yrs 10

31 – 50 yrs 50

> 50 yrs 10

ownership), Family stability (e.g. household size, children’s education), etc.

19

Development of the selection scorecard (2/2)

3. Calculating client score:

a. Final client score is obtained by adding scores from all variables:

b. Segmentation of clients into categories based on the score:

Client score range (example) Category

>= 350 AA-Low Risk or Best Clients

150 to 349 A- Low to Medium Risk Clients

0 to 149 B- Medium Risk Clients

-500 to -1 C- High Risk Clients

<-500 D- Unable to score

Variable Attribute Score

Age 35 50

Civil Status Single -40

Gender Male 0

Home ownership Own house 70

… … …

Total 105

20

Methodology to develop a Renewal Scorecard

When developing the renewal score at Swadhaar a combination of the expert methodology and data analysis was used to check and validate the expert score

Steps followed in this process were as follows

1. Identify variables: A number of repayment performance related variables were identified during the analysis.

• Scores are assigned for each attribute (e.g. value) of a variable based on past experience and expert opinion.

• Based on aggregate weighted scores across all the variables, the score range for segmentation of clients into categories is defined.

3. Back-testing: Historic client data is then used to score a sample of existing clients. This helps:

• To validate the performance of clients post renewal (to see if client behaved the way we thought s/he would)

• To check that the bands and variables are stable

4. Adjustment: Adjustment of the variables and scores assigned to them is done at this stage based on the results of the back-testing

5. Validation: Once the final adjusted score is arrived at, it is validated against another sample of clients from the database to ensure that the results are the stable

2. Analysis:

1 Ratio Days Late is defined as the ratio of the maximum days late during the month in the term of the loan and the term of the loan given 2 A higher score means a better / lower risk client

21

Methodology used to develop a Renewal Scorecard (1/2)

1. Identify variables: Some of the repayment performance related variables identified were:

• Average days past due during loan term,

• Ratio of maximum days late to loan term1,

• Vintage of the client with the institution,

• Resting time between loans,

• Etc.

2. Data analysis (1):

An example of a score band for the variable “Ratio of maximum days late1“ to loan term:

Score band for Value of Variable “Ratio Maximum Days Late1”

Score2

Equal to zero 100

Greater than 0 and less than equal to 0.6 50

Greater than 0.6 and less than equal to 1 0

Greater than 1 and less than 6 -50

Greater than 6 -100

22

Methodology used to develop a Renewal Scorecard (2/2)

2. Data Analysis (2): Based on aggregate weighted client score ranges (e.g. from ≤ -500

to ≥ +500), clients are segmented into categories with a recommendation for the type of renewal evaluation and eligibility for loan amount increases in the next cycle:

Client score range (example)

Category Type of evaluation for renewal loan

Recommended increase in loan amount

>= 350 AA-Low Risk or Best Clients No evaluation required Upto 50%

150 to 349 A- Low to Medium Risk Clients

Simplified Evaluation Upto 25%

0 to 149 B- Medium Risk Clients Full Evaluation Same as previous loan

-500 to -1 C- High Risk Clients Reject NA

<= -500 D- Unable to score on account of insufficient information

Full evaluation Same as previous loan

24

Standardization of key metrics in Swadhaar's

Client Capacity Evaluation

A. Issues in Current Process and Benefits of Standardization

B. Standardization Methodology

C. Swadhaar Findings

D. Standardization Review

25

Issues affecting loan officer productivity • Individual Loan officers handle multiple

responsibilities – marketing/promotions, client evaluations, and installment collections

• A major part of the loan officer’s time is spent in client’s financial capacity evaluation as he/she collects detailed data on client’s business and household income and expenditure items

• Limitations

• Growth to client base is limited due to excessive time spent on evaluation instead of promotions

• Lack of experience/skill level of loan officer resulting in underestimation/ overestimation of client capacity

• Deliberate manipulation of client evaluation to fulfill loan requirement

• Clients are uncomfortable with detailed questioning on their income and expenses

The Loan officer markets the individual loan product, conducts client

evaluations and collections – hence optimizing his/her time and resources

directly enhances profitability

26

Benefits of moving to a more Standardized Process

To overcome these limitations, we decided to use our existing knowledge base and experience to identify commonalities for business and household segments to create benchmarks of key metrics. This helped us in the following ways:

• Increased efficiency and consistency of evaluations, leading to reduced time (~30% lower) in client evaluation

• Ability to scale and replicate the individual lending model to different geographic regions and/or business types due to reduced training time

• Enhanced understanding of market segments and business types, leading to more tailored product offering increasing client satisfaction

• Minimize variability in loan evaluation across loan officers; from a risk perspective, this allows us to manage our portfolio risk across geographies more consistently

• Effectively evaluate client’s financial capacity, thus offering optimum loan terms to the client and improving portfolio quality

• Simplify loan evaluation process could potentially result in 2-3 additional disbursements per month; this would result in an increase in portfolio by Rs 3.0 lakh per loan officer

Caution: Expected benefits from standardization depend on the organization’s strategic focus and operating policies/processes – it is important to assess benefits from the

organization’s viewpoint before undertaking the standardization exercise.

27

Sales

Cost of Goods Sold

Gross Profit

Operational Expenses

Net Business Income

Other Household Income

Total Household Income

Detailed Financial Evaluation Process

- =

- =

+ =

Education

Household Surplus

-

-

- -

=

At Swadhaar, several business and household (HH) metrics are used to determine the HH surplus, which then determines clients’ loan amount and monthly installment eligibility.

However, calculating each metric individually takes a large amount of the loan officers time, which adversely affects our customer acquisition rate, and our ability to monitor the accuracy of each income and expense item.

Other Expenses

Rent

Food

28

a. Decided the metrics to be standardized

b. Decided the sample size and sampling method for data collection

c. Collected data for our samples from various geographies

d. Checked the quality of the data

e. Performed analysis on the collected data

f. Reported the findings

Each of these steps is discussed in detail in the Appendix - Standardization Methodology

The sales margins and HH expenses at Swadhaar were standardized in the following manner..

29

Household (HH) Expenses • The following HH expenses are more uniform and can be standardized – food, clothing,

transportation, health, utilities, education, rent

• HH Expenses was directly proportionate to the number of HH members

• Values varied based on geographic region (e.g. – Mumbai’s rental expenses were ~ 50% higher than Pune, Nasik, and Gujarat)

• We found that HH Expenses varied with the following factors –

Swadhaar’s Findings – Household Expenses

Expense Category Range of Values (INR)

Food, clothing, utilities, health, transportation – 1st HH member 4,000 – 8,000

Food, clothing, utilities, health, transportation – Additional HH member

500 – 1,000 / per member

Rent 1,500 – 4,000

Education -Private School 500 – 1,000 / per student

Education - College 500 – 1,000 / per student

Education - Government School 300 – 600 / per student

Savings, debt payments, insurance payments Vary significantly, capture on actual basis as they cannot be standardized

30

Swadhaar’s Findings – Gross Margins

*The variations in margin are caused due to shop location (home

based/residential area/market area) OR product range offered

and similar factors

Different businesses within the sample group were analyzed to arrive at the

following margins -

Business Type Gross Margin*

General Store 15-30%

Kirana Store 12-20%

Cloth Merchant/Garmet Seller/Sari Seller 20-40%

Footware Store 30-40%

Electric/Hardware Store 35-55%

Imitation Jewelry/Cosmetic Items Store 40-50%

Vegetable Vendor 20-35%

Mess/Tiffin Service/Food Stall 45-60%

Restaurant 30-50%

Garage/Automobile Repair 60-80%

Saloon/Beauty Parlour 70-90%

Tailoring 55-80%

Laundry 45-65%

Fabrication 30-60%

Handwork 45-60%

31

Swadhaar’s Observations on Gross Margins

Several other salient characteristics of gross margins were found, as listed below -

• The standardized gross margins include the cost of goods sold, but exclude indirect costs such as rent, salaries, utility payments, etc.

• Margins were found to be uniform in the range of business sizes within the sample for businesses of the same type – margins may differ for businesses which are larger or smaller than those considered in the sample

• Margins in the service sector are typically much higher than in trading/manufacturing

• Margins can be standardized across regions, as they do not seem to vary significantly across geographies

• Diversified product offering in the same type of business does not make a major difference in sales margin (For example – cloth sellers, garment sellers, sari sellers had similar margins)

• For business types where sufficient sample size was not available, margins were not standardized – these businesses will have to be relooked at a later stage when more data samples are available

• Caution: If a business location houses two different types of standardized businesses (e.g. xerox and general store), then it is recommended to calculate the business margin rather than using the standardized methodology

32

Review of Standardized Values

A process for validation and regular review of the standardized values needs to be in place (review at least once a year)

A review of the standardized values is further needed when:

• Your operations expand to different areas

• Your target client segment changes (E.g. different income group)

• There are changes in the macroeconomic environment (Inflation, regulations, culture, etc.)

• There are changes in the local environment (Free education declared in certain pockets, product demand fluctuates, natural calamities, etc.)

• CAUTION: An incorrect assessment of the current environment and its impact on standardized margins can have adverse consequences on portfolio quality

You can ensure accuracy of your standardized metrics by:

• Consistently using on-the-ground knowledge and assessments of field staff to tweak standardized metrics

• Periodically deploying an independent market research and assessment team to survey various business types and market environments

Your organization can maximize automation and standardization of loan approval process

• By extending standardization of margins and metrics to more business types, segments within business types, etc

34

Tracking client evaluations across cycles is important for …

• Designing product features tailored to client business needs across cycles

• Ensuring that the loan increment policy is based on typical sales/inventory growth across cycles

• Potentially catering to additional loan requirements in renewal cycles (E.g. Asset loans in addition to working capital loans)

• Improved client segmentation

• Client’s ability to translate our loan into visible business growth, may be used as one of the parameters to determine exposure to various business segments for the institution

• Assessing social impact

• Ensuring that a loan in increases client’s business income and also the client’s disposable income

• Assessing increased personal savings/investments

• Understanding impact of loan on household spending

35

Swadhaar Individual Client History

• Swadhaar launched its Individual Lending (IL) product in 2007 and has disbursed over 17,000 loans worth INR 35 crore (~ $ 7 million to date)

• IL Product was launched in Mumbai in 2007, where we have upto 6-7 cycles of client history

• IL Product was launched in Gujarat in 2009, where we have upto 3-4 cycles of client history

• IL Product was launched in Pune & Nasik in 2010, where we do not have a significant renewal history of clients

• Snapshot of client historical information with Swadhaar (only records where sufficient information is available on the system are considered)

# of Loan Cycles with Swadhaar # of Clients

1 5468

2 854

3 375

4 135

5 30

6 9

7 1

Total 6872

36

Possible Business Growth Indicators

There are several parameters that can be used to assess the impact of individual loans on clients businesses such as:

• Business Indicators

• Monthly Sales

• Net Business Income

• Monthly Household Surplus (Disposable Income)

• Working Capital

• Current Assets

• Inventory

• Each of the above indicators must ideally reflect some growth over cycles

• Non – Business Indicators

• Investment in fixed assets (Household goods, vehicle, real estate)

• Increase in household expenses (Indicating increased purchasing power)

• Increase in savings

• Increased spend on education/health

37

Swadhaar observed that Sales and Net Business Income were good indicators for client’s business growth

• The sales and net business income show significant growth from cycle to cycle

• Inventory and current assets remain approximately constant over the first few cycles

* Compared to first cycle

Cycle Average % increase in

Sales *

Average % increase in Net

business income*

Average % increase in Inventory*

Average % increase in

Current Assets*

1 - - - -

2 0% 0% 0% -1%

3 13% 9% -2% -1%

4 25% 14% -2% -1%

5 24% 18% 4% 3%

6 36% 24% Insufficient Data

Insufficient Data

38

Findings – Business Growth Indicators

• Growth in the sales/income of the client is observed from the 3rd cycle

• In the initial stages of growth the client may require to make operational adjustments (Eg: Additional salaries, increased transportation, increased overheads) which limits the client’s observed business growth

• It is important to fund the client’s business across multiple cycles for significant business growth

• The net business income increases around 1.5 times slower than the sales

• Some portion of the sales growth is due to inflation in prices, which also affects business costs – hence increases in the net business income is relatively lower

• The increase in the net business income is a better indicator to the business growth rather than sales as it nets out the effect of inflation

• Trading businesses showed a steady growth in sales/income compared to manufacturing businesses (Refer to Business Growth Indicators – Appendix for details)

• As several manufacturing businesses have seasonal orders, the financial figures would depend upon the timing of the evaluation

• In order to evaluate the growth in manufacturing businesses, it is advisable to observe the client’s business at the same time over consecutive years (Eg: Marriage season, etc)

• Inventory and current assets do not vary significantly until the 5th cycle

• Clients may utilize the business loan to clear payables OR purchase goods on cash at discounted rates - This increases the business profitability but does not reflect in the client’s current assets

• Client can support a limited increase in sales with the same level of inventory and current assets

• An increase in inventory and current assets may be observed in higher cycles

39

Appendices

40

• In order to make the evaluation process more standard and less time consuming, Swadhaar decided to standardize two key metrics in the financial evaluation process to avoid extensive item-by-item data gathering

• Sales Margin (Gross Margin)

• Calculated as (Gross profit/Sales), gives us the gross margin on the business. It includes the cost of goods sold but excludes indirect costs such as rent, salaries, utility payments, etc

• Swadhaar found that while sales vary vastly based on the scale of the business, sales margins themselves can be standardized based on business types

• Manual calculation of sales margin is very time consuming and error prone as it involves collecting information on all the different products sold by the client – quantities sold, cost price, sales price, wastage.

• Clients are not comfortable with sharing such detailed business information

• Household Expenses

• Total of the expenses on food, clothing, rent, utilities, transport, health and education

• Swadhaar found that clients in similar income range largely follow a uniform spending pattern, thus a large part of the household expenses can be standardized

• Clients often underestimate their household expenses, as they typically do not have full information about the household spend; clients are also not comfortable sharing their personal expenses for a business loan

• Standardizing household expenses would give a more correct estimate of household expenses

Swadhaar’s Standardization Methodology a. Decide the Metrics for Standardization

41

Caution!

•Organizations need to balance scientific accuracy with resources available while deciding on sample size & methodology (For other methods see Data Sampling Techniques)

•Ensure that sample bias based on geography, business type/scale, community, etc is avoided with an appropriate sampling method and size.

Swadhaar Standardization Methodology

b. Determine appropriate sample size

Note: There is a tradeoff between practicality and scientific accuracy of the results. Each MFI should determine how to allocate resources accordingly.

• Swadhaar’s Sampling Process

• ~5000 Households (HH) to analyze trends in general HH expenses, education expenses and rent expenses.

• At least 20 samples from each business type to standardize sales margins.

• Used random sampling of clients across Mumbai, Pune, Nasik and Baroda.

General Procedure

•Your organization needs to determine the optimum sample size.

•Then, you need to determine the methodology for sample selection (e.g. Random Sampling)

42

Caution!

•Organizations need to balance resources/time to make the data collection process as efficient as possible.

•It is best to give each staff member a list of all business type interviews required, so he/she does not spend too much time in searching for a particular business type


c. Collect data to fulfill sample size

Swadhaar Procedure

•Used existing client files to aggregate data.

•Whenever data was not sufficient, additional client interviews were conducted.

•In cases where data showed divergent trends, expert interviews were conducted.

General procedure

•Data for desired sample size may be collected through:

• Personal interviews

• Focus group discussions

• Expert interviews (E.g. to standardize health expenses, collect data through doctor interviews) – see Quantitative Collection Techniques

43

Caution!

•Do not remove statistically significant data; take extra caution in defining what constitutes an outlier.

•If it doesn’t fit a dataset, it may be another subset altogether.

Swadhaar’s Procedure

•Used the quartile method to determine upper and lower bound to eliminate outliers (See details of Quartile Method)

General procedure

•Remove outliers: if a data set has values that vary widely from the central value then:

• Remove the data, OR

• Determine the need to create a separate subset for standardization (see Appendix for Errors)


d. Conduct data quality check

44

Swadhaar’s Procedure

•Swadhaar used the median value to standardize household expenses and mean values to standardize sales margins

•Wherever similar business types yielded similar margins, they were grouped under a single head – Eg: All types of food stalls, mess and tiffin services.

Caution!

•Ensure that the statistical method used suits the size and quality of data available – not all methods may yield correct results on a small data sample.

•Look for commonalities among data sets to treat different sub-groups as the same group (E. g: During analysis, it was found traders selling cloth, dress material, saris, ready made garments, handkerchiefs, etc showed similar margins, hence were clubbed together under a single head

• Validate findings with a sample of evaluation forms for any deviations

General procedure

•Use appropriate method to standardize (Calculate average, inter-quartile method, etc)

•Make sure to use an adequate sample size for accuracy


e. Conduct the data analysis

45

Appendix: Data Sampling Techniques

• Simple Random Sampling

o This is the easiest and best way to select a data sample

o In this technique, select a group of homogenous subjects (a sample) for study from a larger group (a population)

o Each individual is chosen entirely by chance (E.g. Surveying the first 20 clients that walk into a chosen shop)

o Every possible subject of a given population has the same chance of selection

• Other sampling methodologies may be more appropriate if

o Additional information is available on clients

o Detailed analysis of the sample is expected

o There are stringent accuracy requirements and/or cost/operational concerns (E.g. If only limited staff members are available)

• Systematic Sampling

o A statistical method involving the selection of elements from an ordered sampling frame. The most common form is an equal-probability method, in which every nth element in the frame is selected

o Simple random sampling does not use a systematic method of choosing clients, whereas this method does. E. g. : Choosing every 5th house on a particular street

o Important: This method, along with simple random sampling, should be done in homogenous populations with little variation to ensure the best results

46

Appendix : Data Sampling Techniques (contd.)

• Stratified Sampling

– This method is useful when the population varies greatly

– This process involves splitting the data into non-overlapping (Mutually exclusive) sub groups or strata which are homogenous in themselves

– The strata must be collectively exhaustive i.e. No population element can be excluded

– A random or systematic sample is then selected from each stratum

– The sample size of each stratum may be proportionate to the population size of the stratum (Proportionate stratification) or may vary (Disproportionate stratification) based on the variances or costs in different strata

– Eg: To standardize sales margins, its important to get a good sample from the following strata – market shops/residential shops, different business scales, etc

– A stratified sample can provide greater precision than a simple random sample with a smaller sample size. However, the administrative costs are typically higher

• Judgment Sampling

– In this method, sample is obtained based on the judgment of an expert who is familiar with the characteristics of the population

– Eg: A particular locality may be chosen to be a representative of the entire city

– When using this method, the researcher must be confident that the chosen sample is truly representative of the entire population

47

Appendix: Quantitative Data Collection Techniques

• Quantitative data collection involves the use of numeric data which can be analysed using statistical techniques. Swadhaar has primarily used the following methods to collect quantitative data from the sample population:

o Anonymous Questionnaires/Surveys

– Can be administered to a large number of people at minimal cost

– People may be more truthful while responding to the questionnaires regarding controversial issues especially if their responses are anonymous

– Drawbacks are that many of the people who get questionnaires often don't return them and those who do might not be representative of the originally selected sample

– Different sources for surveys include: Internet, mail, street, and telephone

o Existing Data

– Swadhaar used its internal client database for an initial sample

– If such information is collected by other MFIs or institutions and is accessible, it may be a viable alternative

– Drawbacks: Data from may not be adequate for your organization’s needs, and may contain potential biases or errors

48

Qualitative data collection methods can be used to improve the quality of survey-based quantitative evaluations by helping to strengthen the design of survey questionnaires and expanding or clarifying quantitative evaluation findings. These include:

o Open-ended and less structured protocols (i.e., researchers may change the data collection strategy by adding, refining, or dropping techniques or informants)

o Rely more heavily on interactive interviews; including focus groups, panels, and in-depth individual interviews; respondents may be interviewed several times to follow up on a particular issue, clarify concepts or check the reliability of data

o Use triangulation to increase the credibility of their findings (i.e., researchers rely on multiple data collection methods to check the authenticity of their results)

o Findings cannot be generalized to any specific population. However, each case study produces a single piece of evidence that can be used to seek general patterns among different studies of the same issue

o Qualitative techniques takes a great deal of time, and the researcher needs to record any potentially useful data thoroughly, accurately, and systematically, using field notes, sketches, audiotapes, photographs, and other suitable means.

Appendix: Qualitative Data Collection Techniques

49

Appendix: Quartile Method

1. Calculate the median of the data group

1. Calculate the 1st and 3rd quartile of the data group

• The number used for the 1st quartile number used should have 25% of the data below it

• Similarly, the 3rd quartile number used should have 75% of the data below it

2. Subtract the 1st quartile from the 3rd quartile to get the inter-quartile spread

1. To remove outliers, you need to calculate the Upper and Lower Bound (UB & LB)

• UB is calculated by taking the median + 1.5 times the inter-quartile spread

• LB is calculated by taking the median – 1.5 times the inter-quartile spread

2. Treat the UB and LB as the range in which the data set needs to be in. Anything beyond the range is characterized as an outlier

50

Appendix: How to Avoid Data Collection Errors

Aside from the sampling error of selection bias, MFIs must be cautious of non-sampling errors, which are caused by other problems in data collection and processing. They include:

• Over-coverage: Inclusion of data from outside of the population

• Under-coverage: Sampling frame does not include elements in the population

• Measurement error: E.g. when respondents misunderstand a question, or find it difficult to answer

• Processing error: Mistakes in data coding

• Non-response: Failure to obtain complete data from all selected individuals

51

A steady increase in sales is observed between cycles in almost all businesses

• Trading businesses

typically show a steady

increase in sales.

• Manufacturing

businesses display an

erratic sales growth

through cycles,

primarily due to

seasonal orders

• Sufficient data is not

available in higher

cycles

• Some variation in the

values across cycles may

also be due to change in

the field officer which may

result in a slightly different

estimation

Business Cycle 2 Cycle 3 Cycle 4

General Store 6% 12% 16%

Kirana Store 5% 10% 12%

Cloth Merchant/Garmet Seller/Sari Seller 11% 14% 18%

Electric/Hardware Store 20% -2% -14%

Imitation Jewelry/Cosmetic Items Store 4% 9% 4%

Vegetable Vendor 1% 5% 9%

Mess/Tiffin Service/Food Stall 4% 9% 7%

Restaurant 6% -8% 44%

Garage/Automobile Repair 2% 5% 10%

Saloon/Beauty Parlour 6% 10% 10%

Tailoring 7% 13% 25%

Laundry 7% 9% 16%

Fabrication 5% 6% 20%

Footwear Manufacture 7% -8% 88%

Handwork 6% 44% 50% *Entries in red indicate less than 5 data points

52

Growth in net business income is more erratic than sales growth in the first 3 cycles

• While sales shows a relatively

steady growing trend, the

growth trend in the business

income is not very strong in

the initial cycles

• This trend may be due to the

adjustments the micro

entrepreneur needs to make

to support the growing sales

– additional transportation

costs, additional employees,

etc. It may take some time for

the business income to

stabilize

• Inflation affects the sales as

well as cost figures, due to

which the growth in business

income is much lesser than

sales growth

Business Cycle 2 Cycle 3 Cycle 4

General Store 2% 9% 13%

Kirana Store 1% 3% -18%

Cloth Merchant/Garmet Seller/Sari Seller 3% 3% 35%

Electric/Hardware Store -4% -4% -8%

Imitation Jewelry/Cosmetic Items Store -4% 13% 14%

Vegetable Vendor 3% -3% 7%

Mess/Tiffin Service/Food Stall 4% 16% 4%

Restaurant 5% -15%

Garage/Automobile Repair 8% -2% -18%

Saloon/Beauty Parlour -2% 11% 13%

Tailoring 1% 6% 13%

Laundry 5% 5% -

Fabrication -3% - -

Footwear Manufacture 10% 4% 27%

Handwork 1% 13% -14% *Entries in red indicate less than 5 data points

streamlining individual lending evaluations at … standardized margins and household expenses for...

Documents