Technical writers:Shubhranka Mondal and John Victor Arun Kumar

CREDIT AS A HOOK: BUILDING DIGITAL FOOTPRINTS FOR CREDIT ACCESS

TECHNICAL REPORT

This publication is made possible by the generous support of the American people through the United States Agency for International Development (USAID). The contents are the responsibility of CATALYST and do not necessarily reflect the views of USAID or the United States Government.

About CATALYSTCATALYST is a user-centric ‘digital financial inclusion innovation platform’ for the underserved last mile. The initiative is funded by the United States Agency for International Development (USAID) under the mSTAR Program, through funding provided to FHI 360. Housed within the Institute for Financial Management and Research, Leveraging Evidence for Access and Development (IFMR LEAD), the initiative aims to expand digital payments and financial inclusion in India.

CATALYST identifies, develops and validates solution frameworks and business models in collaboration with facilitating government agencies and participating industry solution providers to responsibly transition small business ecosystems (i.e., merchants, consumers, suppliers) from an inefficient cash economy to digital payment platforms, and further onto broader digital finance solutions. CATALYST has also launched a new business incubator, ‘Fintech for the Last Mile,’ to promote entrepreneurs focused on developing innovative digital finance solutions for traditionally underserved segments.

AcknowledgementsThe authors would like to thank and acknowledge the support of Jayshree Venkatesh for her expert advice to conceptualize and review the report and Aditya Deshpande for partnership mangement. The implementation would not have been possible without our payment solution partners Nupay and Mswipe and NBFC partners Arthimpact and Capital First. Special thanks also to the very hardworking CATALYST feet-on-street (FoS) team, led by Manish Sharma, who carried out the handholding exercise and data collection.

Thanks to Josh Woodard, Jaheed Parvez and Harsh Pandey (FHI 360) for editorial reviews and feedback, and to Sharon Buteau and Badal Malik for their consistent support and encouragement. Thanks to Ananda Swaroop for content editing and Allan Macdonald for the design of the report.

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SummaryAccess to formal sources of credit remains a challenge for the unorganized Micro, Small and Medium Enterprises (MSME) sector in India. The credit gap for informal enterprises within the MSME sector in India was estimated to be at US$418 billion in 2012-13.1 Lack of business transaction data and credit history acts as a barrier to establish credit-worthiness required to access credit from formal sources. As a consequence, these enterprise owners often end up accessing loans from informal lenders at exorbitant interest rates.

In an attempt to break this vicious cycle and help small merchants get loans from formal sources, CATALYST carried out multiple experiments. These were aimed at testing if access to credit through a starter builder model2 would encourage merchants to transact digitally and build a digital footprint. CATALYST designed a bundled product comprising a mobile Point of Sale (mPoS) machine plus a small business loan. The aim of the intervention was to discover whether access to credit would incentivize merchants to initiate and increase digital transactions and whether, this in turn, would help them access higher ticket size loans in the longer run.

Our initial hypothesis that credit would act as a hook to incentivize digital payments was proved wrong due to a number of reasons we discovered through our field insights. Firstly, compared to formal loans, informal loans are available at short notice and with limited or no documentation. Second, suppliers offer trade credit at competitive terms to merchants and are an important relationship-building mechanism. Third, our assumption that small businesses are merely price sensitive and therefore would be more open to formal credit was proved wrong. We discovered that the drivers for adoption are not price, but easy and timely access to loans, easier onboarding and product features that match the current benefits of informal loans.

However, there still exist a credit gap and an opportunity for formal lending. Based on our insights, we recommend that formal lenders seeking to operate in this segment establish a strong on-ground local presence through people who are trusted such as local nonprofit partners, influencers in the supply chain, and others.3 Merchants do need handholding and support on call, which must be available when required. While this can be considered as a capacity-building exercise to provide access, it can also, in commercial terms, create demand. We also recommend better use of training and awareness campaigns to increase digital literacy of small merchants.

1IFC. 2017. MSME Finance Gap, Assessment of the shortfalls and opportunities in financing micro, small and medium enterprises in emerging markets.2A mechanism to provide incremental loan to a customer based on his/her digital repayment and digital transaction history.3Refer to the Customer Centricity playbook published by Cashless CATALYST for a chapter on how these partnerships can be structured effectively.

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Table of contents

1 Background and context 61.1 Overview 7

1.2 Diagnosis 8

1.3 Stakeholder analysis 10

2 Pilot design and implementation 122.1 Theory of change 13

2.2 Scope 13

2.2.1 Target segment 13

2.3 First pilot: Mswipe and Arthimpact 13

2.3.1 Product design (data filtration funnel) 13

2.3.2 Outcomes 14

2.4 Second pilot: Capital First and Nupay 14

2.4.1 Implementation challenges 14

2.4.2 Product design 14

3 Observations and insights 163.1 Metrics 17

3.1.1 Conversion funnel 17

3.1.2 Challenges and barriers to conversion 17

3.2 Key learnings 19

3.3 Cost-benefit analysis 19

3.4 SWOT analysis 20

4 Recommendations 21

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BACKGROUND AND CONTEXT

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1.1 OverviewNinety-three percent of India’s US$670 billion retail market continues to be unorganized, operating through mom-and-pop stores, kirana stores or standalone stores.4 According to a recent Boston Consulting Group-Confederation of Indian Industry (BCG-CII) report, this sector is projected to double from a US$1.1-1.2 trillion market by 2020, driven by a 70 percent rise in income levels and a 100 million addition in the number of youth entering the labor force.5 Growth projections notwithstanding, there are several factors that hinder the growth of these informal enterprises which provide livelihood options to nearly 111 million workers,6 thus forming an important engine for India’s economic growth.

The lack of proper infrastructure and technical skills notwithstanding, a pressing factor hindering attainment of scale by informal enterprises is the lack of credit at affordable rates of interest. According to an International Finance Corporation (IFC) report, the credit gap for informal enterprises within the MSME sector in India was estimated at US$418 billion in 2012-13.7 Underlying the gap in accessing formal credit is the story of absent applicant credit histories or other parameters of credit-worthiness used in traditional appraisal processes by lenders.8 Under such circumstances, most enterprises resort to informal lenders, despite the high interest rates charged. Reluctance to adopt digital payments further exacerbates this situation, since it is near impossible to convince lenders of credit-worthiness in the face of missing information on credit and other transactional histories. Lack of awareness, low capability and unwillingness to try new technologies for fear of failure are some reasons that contribute to this wariness and create a vicious cycle that has been hard to break.

CATALYST, in its drive to explore the digital readiness of this segment, hypothesized that providing access to a small amount of credit at lower rates could act as a hook for digital payment adoption and usage, which, in turn, could act as a positive spiral to access higher amounts of credit. Credit as a hook is a pilot experiment to test this hypothesis and an opportunity to learn and iterate from the findings of on-ground implementation.

4Tandon, S. India’s $670 billion retail market is heading for a dream run. Quartz, April 16, 2018.5BCG-CII National Retail Summit, 2016, Retail Transformation: Changing Your Performance Trajectory.6Rodrigues, J. Found: 111 million MSME workers in India as data rules changes. Livemint, November 22, 2017.7IFC. 2017. MSME Finance Gap, Assessment of the shortfalls and opportunities in financing micro, small and medium enterprises in emerging markets.8Chengappa, S. There is a credit gap of 56% in the MSME sector. The Hindu Business Line, July 2, 2014.

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1.2 DiagnosisCATALYST carried out a Credit Needs Assessment Survey (CNAS) where 1,140 small merchants in Jaipur were interviewed in September 2017 to understand their credit demand and digital payment usage. This study was specifically commissioned for scoping and assessing needs to feed into testing the “credit as a hook for digital payments among merchants” hypothesis.

The key findings of the study were as follows:

• 69 percent of the total sample of merchants reached during the survey sourced their credit from informal sources such as friends, family and local moneylenders;

• Qualitative analysis suggests that merchants expressed dissatisfaction with local moneylenders because of the exorbitantly high interest rates, going up to 30 percent per month;

• Despite getting lower rates of interest from formal sources, qualitative analysis also suggests that merchants preferred informal loans because of no hassle of documentation and speed of processing loans; and

• Of the 92 percent of business owners who were aware of digital payment solutions, 53.5 percent said they would be interested in availing credit through a digital platform.

In order to field test the hypothesis, we approached the Payment Service Provider (PSP) and Non-Banking Financial Company (NBFC) partners to launch the Credit as a Hook pilot in 2017 and thereafter also completed the CNAS to test the market readiness of accessing a digital loan product. Finally, in June 2018, the partnerships were finalized and the pilot initiated. The 53.5 percent merchants who had expressed

interest in availing credit through a digital platform in the CNAS formed the first base sample for the pilot.

Pilot StrategyUse of merchant survey data: For the pilot launch, as the first step of market entry strategy, the CNAS database of merchants who had shown interest in accessing credit through a digital platform was selected.

• Training Feet on Street (FoS) team: Following the data selection, CATALYST’s FoS team was trained in office for two days with a prescribed phone calling script to market the bundled product to the merchant.

• Phone-calling exercise: After this, a phone-calling exercise was carried out to reach out to the merchants who had expressed interest in accessing digital credit during the CNAS.

• Meeting merchants on ground: After the second round of confirmation on the interest in the loan product from the phone-calling exercise, the FoS team, along with field staff of the partner organization, reached out to the merchants, gave them a demonstration of the machine and marketed the product.

However, the phone-calling exercise revealed that the FoS team could only reach out to 308 of 648 interested merchants from the CNAS. The percentage of valid phone numbers was as low as 47 percent (308) almost half of the merchants who showed initial interest because the first phone-calling exercise used the CNAS data which were six months old. It was difficult to reach out to merchants as they had changed their phone numbers. Challenges included a permanent loss of numbers due to the withdrawal of two telecom operators (Reliance and Aircel) from the region. Besides, merchants frequently changed numbers to avail of promotional offers.

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Figure 1: Data filtration funnel: pilot 1 data selection and calling exercise

The conversion funnel shown in Figure 1 denotes: the filtered data set from the CNAS, 648 of 1,140 merchants who had shown interest in accessing digital loans. Of 648, only 308 merchants could be reached through a phone-calling exercise. These 308 merchants were called to confirm their interest in accessing a loan, of which 136 reconfirmed their second round of interest. However, only 12 merchants were initially shortlisted by Arthimpact, the NBFC partner for the first pilot, based on its internal filtering process in which trades such mobile merchants, juice shops, tea shops, etc., were excluded for the first batch of loan disbursal. Of these 12, only six merchants could be reached out to in person to confirm their final interest. However, none of the six agreed to adopt the bundled product. Also, it is important to note that the conversion funnel in Figure 1 shows that only 308 out of

648 numbers were valid for use after six months.

• Forging the right partnerships at the right time: Of the multiple PSPs and NBFCs available in the market, it was important to find the right partners who would be willing to deploy their local resources and provide necessary handholding support for pilot implementation. The process of finding these partners took longer than anticipated, which resulted in project delay.

Attributes required in a partner included:

1. Product viability: Be ready to test the market feasibility of launching a new product bundle in a low-income and fairly uncharted market with little to no history of credit worthiness.

2. Readiness to learn: Be able to bear the operational

cost of deploying sufficient ground forces to reach out to customers and provide them continuous handholding support.

3. Flexible product structure: The generic product should have options to quickly customize to suit specific customer needs, including pricing and offers.

4. Digital payment partner: Be willing to partner with a PSP or a NBFC or vice versa as an implementation partner for testing and be able to abide by each other’s terms and conditions for a successful launch.

After considerable effort and negotiation, CATALYST began work with two sets of partners for the two different pilots, the details of which are explained in the following sections.

1,140Total no. of merchants from

CNAS

648Merchants interested

in loan

308Valid phone nos.

136 merchants agreed to access digital loans

165 merchants were not interested4 asked to call later Miscellaneous - 3

12 eligible merchants selected for pilot launch

6 merchants agreed to meet

Reach out & deep-dive analytics

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1.3 Stakeholder analysis The roles and responsibilities of three major stakeholders involved in the pilot, i.e., CATALYST’s FoS team, PSP partner and NBFC partner, were:

CATALYST FoS team PSP partner NBFC partner

1. Scope the local market

2. Generate positive leads

3. Share the data of positive leads with the PSP and NBFC partners

4. Provide handholding support to onboard merchants

1. Reach out to merchants who are interested in adopting the mPoS machine

2. Share data with the NBFC partner for processing the loan request

3. Provide handholding support for merchant conversion (i.e., use of the mPoS machine)

1. Reach out to merchants interested in the loan product

2. Share the data with CATALYST team on merchants’ loan requirement and the reasons for them being accepted or rejected for loan disbursal

3. Provide handholding support to collect Know Your Customer (KYC) documents, explain loan and repayment cycle to customers

CATALYST's FoS team was trained on a short survey, the purpose of the intervention and use of the PoS machine

for 2 days in office

CATALYST's field supervisor guided and supervised the FoS team on mock surveys and demo demonstration in the field for 2 days.

This was the time for possibble rectification and clearing of doubts

For the next couple of months, the work of the FoS team was to generate positive leads, maintain a database of both positive leads

and conduct a small survey on merchant behavior

The positive leads were passed on to the PSP partner's field team which then proceeded to onboard the

customers and collect payments

Figure 2: CATALYST’s FoS team onboarding and field work process

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PILOT DESIGN AND IMPLEMENTATION

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2.1 Theory of changeThe aim of the Credit as Hook pilot was to provide incremental loans to small merchants through a Starter Builder Model based on the usage of digital payments. This would help merchants build both transaction and credit history and thereby ease the loan underwriting process and help them access bigger ticket size loans in the future. Specifically, the aim of the first pilot was to test a short-term loan with a daily repayment option.

2.2 Scope2.2.1 Target segment

The database of fixed store merchants from the CNAS was used for the first pilot implementation of Credit as a Hook. The details of the conversion funnel are shown in Figure 1. For the second pilot, fixed store merchants from six major markets in Jaipur (Shastri Nagar, Sanganeer, Durgapura, Hasanpura, Bais Godam and Sodala) were reached out to following a stratified sampling methodology. The stratification was based on geography, i.e., reaching out to a relatively low-income market in Jaipur which had low digital exposure and

usage and type of fixed stores, i.e., fixed stores with revenue. At the first stage of implementation, a small scoping exercise was conducted with a local field supervisor to determine the market and visiting hours.

2.3 First pilot: Mswipe and ArthimpactCATALYST launched the first pilot in partnership with Mswipe (PSP partner which provided the PoS or card swipe machines) and Arthimpact (NBFC/credit partner). Both Mswipe and Arthimpact had ample local presence and had expressed an interest in

testing and expanding into the unchartered small merchants’ market in Jaipur.

2.3.1 Product design (data filtration funnel

Of the 136 merchants from the CNAS who had responded positively about accessing loans after a phone-calling exercise, Arthimpact agreed to provide 40 merchants an initial loan with the ticket size of INR 5,000 (US$70.89)9 to INR 25,000 (US$354.45) at an interest rate of 2 percent per month on a reducing balance basis, to test the market. Interest had to be paid daily using the Mswipe solution by either swiping a debit or credit card.

Figure 3: Theory of change

Buy a mPoS machine to accept digital payments from customers + get a short-term business loan as a bundled product

Use the mPoS machine as frequently as possible to create digital footprint of business transactions + repay the loan digitally

Get bigger ticket size business loans based on the digital transactions + loan repayment history

Have larger business investment and greater/faster growth

9The US$ to INR exchange rate of 70.53 as on January 11, 2019 (http://dollarrupee.in/) has been used through this document.

Figure 4: Pilot 1 work flow - Mswipe and Arthimpact

CATALYST’s FoS team reaches out to merchants,

studies them through a short survey and

generates positive leads from the field

Digital footprints used as proxies for bigger credit

appraisal after a period of 3 months

Mswipe’s Mumbai team explains the cost of the machine and the loan

Mswipe’s team in Jaipur disburses the machine and collects

KYC documents for the loan within a period of

15 days

Arthimpact assesses merchant’s credit worthiness and

determines loan amount

List of positive leads are passed on to Mswipe’s

team in Mumbai

Mswipe team reaches out to merchants in Jaipur and

gives a machine demo

Confirmed leads list is passed to Mswipe’s

Mumbai team

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2.3.2 Outcomes

The CATALYST team contacted merchants from the CNAS over phone to check willingness to participate in the pilot (refer Data Filtration Funnel 1 for details). Of the merchants contacted, a set of six merchants who fulfilled Arthimpact’s credit - worthiness requirement were contacted in person for the first pilot. However, there was no digital conversion at this stage due to a mismatch in loan approval and loan expectation amounts as shown in Table 1.

Merchant outreach in Pilot 1: inferences

• The merchants envisaged the loan amount as a one-time investment and demanded amounts which were at least five to 10 times higher than the amount approved by the NBFC;

• All of the merchants perceived the Mswipe machine to be too expensive to get a loan amount as small as INR 3,000 (US$42.53) to 15,000 (US$212.67); and

• Delays in delivering the loan due to partnership issues between Mswipe and Arthimpact

2.4 Second pilot: Capital First and NupayFollowing the learnings from Pilot 1, CATALYST partnered with Nupay (PSP partner, an early stage startup) and Capital First (NBFC partner). Additionally, CATALYST also trained a six-member FoS team in marketing and customer acquisition strategies to provide greater handholding support, which was difficult during the first pilot as the partners operated out of Mumbai. This was a step to leverage the resource crunch and provide better field support. Capital First, the chosen NBFC for the second pilot, had greater operational experience in Jaipur and, being a relatively larger NBFC than Arthimpact, had a bigger appetite for risks.

2.4.1 Implementation challenges

Despite CATALYST providing extra field support through the FOS team, there were additional challenges in the second pilot’s implementation:

• Nupay, being a startup, had a serious resource crunch in terms of field support; and

• The follow-up process between lead generation and actual sale of the mPoS machine suffered as Nupay had operational delays due to the absence of robust processes which can be attributed to its vintage. Merchants who had shown initial interest lost their keenness by the time the Nupay field staff reached out to them in person.

2.4.2 Product design

Capital First agreed to provide a long-term starter loan with the ticket size of INR 25,000 (US$354.45) to INR 500,000 (US$7,089) at an interest rate ranging from 18 percent to 24 percent. The loan amount had to be repaid within a period of nine to 36 months depending on the ticket size and repayment capacity.

Nupay’s card swipe machine had a monthly rental of INR 350 (about US$5) plus 18 percent Goods and Service Tax (GST). As per the product bundle, pilot merchants would be considered for an incremental loan basis repayment history of the first tranche of the loan plus increase in digital transactions.

Sl.no Type of shopApprox. monthly revenue in INR

Loan eligible Loan requirement

Interest in Mswipe/ PoS machine

Follow up for Mswipe machine

1. Masala chakki 12,500 4,000 4,00,000 No No2. Motor parts shop 20,000 6,000 5,00,000 No No3. Kirana store 50,000 15,000 1,00,000 No No4. Cosmetic shop 10,000 3,000 1,00,000 No No5. eMitra 37,500 12,000 3,00,000 No No6. Electrical shop 20,000 6,000 3,00,000 No No

Table 1: Information on the selected merchants for the loan

Figure 5: Pilot 1 work flow - Nupay and Capital First

CATALYST’s FoS team reaches out to merchants,

studies them through a short survey and

generates positive leads from the field

List of positive leads is passed on to Nupay's team

Jaipur

Nupay's team reaches out to merchants in Jaipur and sells the machine. Capital First’s loan agent gets the

loan and reaches out to the prospective merchants

Digital footprints used as proxies for bigger credit

appraisal after 9 months to 3 years.

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OBSERVATIONS AND INSIGHTS

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3.1 Metrics3.1.1 Conversion funnel

Ten of 746 merchants reached out to during the survey adopted Nupay’s mPoS machine. Some of the major reasons for non-conversion or non-adoption are shown in Figures 6 and 7.

• Customers’ lack of interest in using digital payments was cited by merchants as a major reason for non-adoption of the mPoS machine. About 6 percent of the merchants cited non-exposure to digital transactions and recordkeeping as a primary reason for non-adoption while about 1 percent thought either the machine (one-time installation) or the monthly rental was expensive;

• In terms of the loan, 97.2 percent of merchants denied having taken a loan earlier, whereas 2.8 percent (21) of a sample of 746 merchants confirmed having taken a prior loan for business. One (of 21) reported that he had taken a loan from a public sector bank whereas the remaining 20 said they had accessed loans from moneylenders; and

• Twenty-five merchants expressed an initial interest in the loan product but backed out later.

3.1.2 Challenges and barriers to conversion

Perceived vs. real interest in loan: When offered the bundled product of payment device and credit, 25 merchants showed initial interest solely in accessing the loan during their first interaction with the FoS team. However, 24 had changed their minds when the lender’s agent approached them in a week’s time, perhaps because merchants always look for options in credit but may not access it even if they express an interest initially.

The bundled product did not meet customer demand: The bundled product, i.e., the mPoS machine and the loan, was explicitly termed as expensive by about 1 percent of the merchants reached out to during the survey.

1

4

725

Will take a Govt. loan

Will never take a loan

No need for a loan now

800

Figure 7: Reasons for not taking a loan

N=730

0.46%

0.91%

5.63%

85.54%

0.46%

7%

Already requested for another machine

Rent is expensive

Don’t want to show digital transactions

Customers are not interested

The machine is expensive

Already using a PoS machine

100%

Figure 6: Reasons for not buying mPoS machine

N=657

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Non-disclosure of digital transaction and data sharing problems: About 6 percent of the merchants in the survey did not want to adopt the machine because they did not want to disclose their digital transactions and thereby share the data with CATALYST’s implementation partner. There is an existing level of resistance among a section of merchants on data sharing which was difficult to overcome in the short span of the pilot.

Poor customer experience and unforeseen complications in accessing loans: One merchant, who agreed to try the combination of an mPoS device and loan, owned a fixed cloth store in Shastri Nagar market. He wanted a loan of INR 100,000-200,000 (US$1,418-2,836). Unfortunately, the request was denied since his residence was located outside the serviceable area set by the lender. This fact was discovered after the processing was done, and resulted in a poor customer experience for the merchant.

Overall, the experiment shows that, while there was individual adoption of the card swipe machines (10), there was no uptake of the bundled product. Technology did seamlessly bind the products together, but the communication to merchants was often unclear and did not explain how payment device usage would help them get a higher loan in the future.

ResultsOf the 10 merchants who had bought the mPoS machines, three could start active usage within a month whereas the other seven were still awaiting digitally active customers.

• Uptake of digital solutions at merchant locations depends on customer readiness: The first women’s garments store located in a traditional community found it hard to find digitally active customers. Of the large section of women from the local community who visited the shop, none had cards. The shopkeeper thinks that only when the husband accompanies the wife/children, can he expect a payment by card.

• Six (five sellers of apparel and one of accessories) of the other nine merchants have had similar experiences. However, all six do not want to lose out on the small section of card owning customers who visit their stores.

• All 10 merchants view the mPoS machine as a means to accept a different mode of payment and acquire more customers.

• However, at the end of both pilots, the number of loans issued remained nil. Therefore, it was impossible to fully test whether credit (with its particular set of ticket size, rate of interest and other terms and conditions) can actually be a hook to drive merchant digitization.

Sl.no Name of the merchantStatus (active/closed/ not started)

Date of activation No. of transactions in October 2018

Value of transactions in October 2018 (INR)

1. Women’s garments shop Closed 0 0

2. Watch and bag shop Active August 1, 2018 0 03. Medical store Active August 28, 2018 104 89,6874. Restaurant Active September 5, 2018 21 9,2025. Kirana store Active September 10, 2018 5 5,7916. Swags Zone Active September 5, 2018 0 07. Garments store Not started September 27, 2018 0 08. Medical store Not started October 28, 2018 0 0

9. Garments store Not started signed up on October 29, 2018 0 0

10. Garments store Not started Signed up on October 31, 2018 0 0

Table 1: Status and transaction value of mPoS devices by merchant

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3.2 Key learningsLoan structure: While the lender assured the merchants of a credit build-up model, the merchants were keen to understand the exact qualifiers for the build-up process, i.e., the number and/or value of transactions required to qualify for the next tranche of loan. Additionally, they wanted to know by what percentage the loan amount could grow, if they opted for it, through increased usage of digital transactions. None of this information was provided to merchants since the lender had not yet thought it through.

The product’s value proposition stated in one line by the lender as ‘enhanced loan size for incremental usage of digital payments’ failed to gain the merchants’ trust.

Single interface for credit and digital payments: During the pilot, the partner PSP and NBFC used two separate applications to onboard customers. For the merchants, who saw the two as a single product, it was inexplicable that a single solution should have two applications rather than one for simplicity and ease of use. The existing process offered a poor customer experience because filling out two applications is a lengthy process.

Long time lags: The process of loan disbursal was lengthy, i.e., lead generation by field agents (CATALYST’s FoS team) and an initial interaction were followed by a calling exercise by the credit assessor and then a site verification. This time lag between the initial contact and disbursement was a pain point. Additionally, there were delays in disbursing the card machine. Partnering with an early stage startup for the card machine led to a resource crunch, which resulted in operational delays. The time lag between initial lead generation and delivery of the machine ranged from 15 to 20 days which was too long a period to retain merchants’ interest.

High cost of onboarding: The loan offer had a customer onboarding cost plus GST that increased the already existing rates of interest by 3 to 4 percent by which the lending interest rate works out to be around 30 percent annually. These nuanced details deterred many merchants from finally accessing the loan even though they showed initial interest in the loan product.

Short tenure of pilots: One must note that three or four months is too short a time to launch and iterate on a product bundle that includes a loan repayment timeline of nine to 36 months. To understand the access and usage of repeat loans, the pilot experiment should essentially be of a much longer tenure.

Changes in market conditions: The implementation process also brought to the light the fact that market forces change faster than human behavior – which often depends on definitive nudges, networking effect and trust building interventions before showing any visible signs of change. In the case of the second pilot’s implementation, market forces reacted faster, i.e., Mswipe, the earlier partner and now a major competitor of Nupay, removed the rental cost for buying the mPoS machine and made it rent free for lifetime. This price shock was hard for Nupay to bear and, being an early stage startup, it had too few resources to either indulge in a price war or device an alternate strategy to beat the big market players. As a result, merchants’ digital conversion became doubly difficult during the second pilot’s implementation.

3.3 Cost-benefit analysisSince there was no conversion within the pilot period for the bundled product, the break-even commercials are difficult to be estimated at this point. Limited time and slow customization of products hindered conversion.

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3.4 SWOT AnalysisThe SWOT analysis for this pilot has been done considering two dimensions, i.e., the product and its stakeholders, and value to merchants. The impact on the merchant business needs to be understood more in-depth based on uptake and usage of credit and digital solutions. However, due to no uptake of the bundled product resulting in lack of usage data, we are limited to drawing findings from surveys.

The estimated strength of the pilot are:

1. Quick and easy access to loan through a digital platform

2. Reduction of paper work due to the use of digital document collection, verification and possible repayment records

3. Hassle-free loans: easier digital KYC

4. Faster processing time for loan disbursement through digital approvals

1. Untapped market – small ticket size mass numbers could change market demand

2. Building digital transaction history for credit approval to formalize the informal sector merchants

3. Access to larger ticket size loans for small businesses

4. Encouraging digital transactions among customers

The observed weakness in the pilot are:

1. High cost of purchase/rent of the mPoS machine (one-time installment)

2. Lack of sufficient digital literacy resulting in apprehensions about transaction failures

3. Only a part of the business transaction takes place digitally while most customers prefer to or use cash for small ticket transactions

4. mPoS machines having only card swipe options

1. A potential price war with mPoS competitors leading to market volatility

2. Machine frauds – card details being stolen

3. Machine maintenance and repair – after-sales services

4. Transaction failures – loss of trust

Strengths

Opportunities

Weaknesses

Threats

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RECOMMENDATIONS4

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Need for a local presence: An implementation challenge that needs to be addressed in order to iterate on the pilot experiment and help it succeed is decreasing the time lags between the first point of contact to in-person onboarding with the card swipe machine and the loan. To avoid such operational delays, it is advisable to work with a local company with greater field presence than with a well-known company based out of another metropolis but with limited field support as was the case during this pilot. Otherwise, the card swipe company/loan company should partner with a channel partner who should be assigned locally to cover the high customer acquisition cost that has to be incurred (by default) for wider reach and impact among the segment of merchants who are new to digital payment usage.

Alternate digital payment solutions: The current credit products are more suited to card swipe machine uptake and usage. However, given the increase in use of other digital payment modes such as Unified Payments Interface (UPI), e-wallets and other Aadhaar-based solutions, there could be faster and cheaper adoption among merchants.

Simple product structure: As the pilot results suggest, clear communication to the merchants on the exact qualifying factors for incremental loans will help develop trust and better customer relationships for a credit-builder model.

Provide digital training and awareness: Multiple field visits and available data on awareness on credit history or usage of digital payments suggest that small fixed store merchants need substantial handholding, training and sensitization to understand fundamental financial concepts, the importance of formal loans, and uses of credit history. The experiment results suggest that the small merchants would benefit from expert handholding support and training from the first point of contact as well as from absence of operational delays. Further, training and awareness-building must extend to customers who shop at the merchant locations, since customer demand is a huge driver in merchant acceptance of digital solutions.

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Annex 1: Pilot 2: Sample population demographics and responses to survey questions

Summary StatisticsSl.no Categories / Responses Number Percentage

1.

GenderMale 735 98.5Female 11 1.5Total 746 100

2.

Education levelBelow class 10 110 14.7School pass 243 32.6College pass 281 37.7Diploma 57 7.6Post-graduate 55 7.4Total 746 100

3.

Store ownershipYes 707 94.8No 39 5.2Total 746 100

4.

Shop typeGeneral store 132 17.7Medical store 46 6.2Cloth shop 125 16.8Footwear shop 26 3.5Bakery 8 1.1Vegetable/fruit shop 3 0.4Dairy shop 5 0.7Book shop 6 0.8Salon/parlor 1 0.1Tailor 11 1.5Hardware parts 13 1.7Toy shop 7 0.9Jewelry shop 3 0.4Bangle shop 7 0.9Electronic shop 29 3.9eMitra 5 0.7Electronic shop 10 1.3Tea shop 1 0.1Sweet shop 9 1.2Cycle/bike repair shop 5 0.7Others 294 39.4Total 746 100

Table contd. to next page

Summary StatisticsSl.no Categories / Responses Number Percentage

5.

Ownership registration status of this businessOwned solely 649 87Owned jointly with someone from the household 89 11.9Owned jointly with someone from outside the household 7 0.9Others (Specify) 1 0.1Total 746 100

6.

Is the business registered?Yes 617 82.7No 129 17.3Total 746 100

7.

Type of registrationShop establishment license 435 70.5GST registration 77 12.5Both 78 12.6Others 27 4.4Total 617 100

8.

Owners have other sources of incomeYes 15 2No 731 98Total 746 100

9.

Current use a PoS/ Mswipe machineShop 21 2.8House 350 46.9Both 347 46.5Others 28 3.8Total 746 100

10.

Is the business registered?Yes 46 6.2No 700 93.8Total 746 100

11.

Use of other digital solutions/apps to carry on business activitiesYes 390 52.3No 356 47.7Total 746 100

Table contd. to next page

Table contd. to next page

Summary StatisticsSl.no Categories / Responses Number Percentage

12.

Whom do they connect/pay/transact for their business using these apps?Customers 382 97.9Distributor/wholesaler 6 1.5Business partners 1 0.3Others 1 0.3Total 390 100

13.

Credit History: Have they ever taken a loan?Yes 21 2.8No 725 97.2Total 746 100

14.

Purpose of the loansBusiness growth 12 57.1Business growth, family emergencies, housing loans 1 4.8Housing loans 5 23.8Others 3 14.3Total 21 100

15.

Credit sourcesMoneylenders 20 95.2Public sector bank 1 4.8Total 21 100

16.

Awareness on credit scoreYes 171 22.9No, never heard 447 59.9Heard of it, not sure of what it means 128 17.2Total 746 100

17.

Trust on a digital payments /solution productsNo trust 160 21.4Low trust 282 37.8Medium 239 32High 65 8.7Total 746 100

18.

Willingness to get training, handholding to use various means of digital paymentYes 69 9.2No 677 90.8Total 746 100

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Summary StatisticsSl.no Categories / Responses Number Percentage

19.

Common concerns on buying the machineCustomer care issues/query 16 57.1Cost, rental, payment query 10 35.7Usage query 2 7.1Total 28 100

20.

Other surveyor observations, if the merchant was not interested in the productAlready using a PoS Machine 46 7Machine is expensive 3 0.5Customers are not interested 434 66.1Will contact you, when I need a machine 96 14.6No reason, do not need the machine 32 4.9Don’t want to show digital transactions 37 5.6Rent is expensive 3 0.5Already requested for another machine 6 0.9Total 657 100

Annex 2: Collaterals from the second pilot (Nupay mPoS machine)

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NBFC loan pamphlets distributed during the second pilot

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