All’s well that repays well? Not necessarily.

By Vaishnavi Prathap, IFMR Finance Foundation

The past year has seen many commentaries on the rapid expansion of microfinance in India warning of the imminent consequences of unbalanced growth. The most striking statistic in this context — that the average client’s dues more than doubled in just four years (between 2012 and 2016), far outpacing only moderate growth in numbers of branches, employees or clients, and surely clients’ incomes — was estimated from data that, at best, captures only a large proportion of the microfinance market. While this has triggered ruminations of an emergent repayment crisis, these fears have been tempered on two grounds. First, the enforcement of new regulations since 2012 limit the risk of client over-indebtedness. Second, delinquencies have consistently remained low over the expansionary period, and wherever reports of distress have surfaced, they seem mostly uncorrelated with the sector’s growth rate.

But do these arguments show us the full picture? Considered against primary evidence from the financial diaries of low-income households in India, we find that often they do not. The data, collected by IFMR Finance Foundation during a study supported by the CGAP Customers at the Center Financial Inclusion Research Fund, provides rich detail on the financial lives of borrowers in a competitive and mature microfinance market. It reveals that the indicators cited by both arguments above are poorly correlated with the incidence of over-indebtedness and with the ways in which borrowers experience and cope with repayment distress.

Timely repayments and borrower distress are not mutually exclusive

Aggregated data from lenders’ administrative records, such as delinquency estimates published by credit bureaus, have traditionally served to indicate portfolio quality. When delinquencies are low, it is interpreted as a signal of positive borrower outcomes. However, the repayment record may not fairly represent borrowers’ experiences if lending practices emphasize timely collection above all else.

The financial diaries of over-indebted borrowers illustrate this fact. Of the 400 households we studied, nearly one of every five borrowers reported repayment obligations higher than they could reasonably afford, given their incomes and minimum living expenses. Yet, as many as 85 percent of those over-indebted borrowers never missed a repayment on formal loans, arguably since they had strong incentives (both institutional and social) to do so.

Further, the records submitted to bureaus seldom distinguish between repayments made by the client and payments made by group members on her behalf. Thus, perhaps as an unintended consequence of the design of joint liability, the administrative data reveal few meaningful insights at a sector-level on borrowers’ distress or well-being.

Not consumption smoothing but repayment smoothing

How is it possible for so many borrowers to consistently avoid delinquency while carrying multiple, unaffordable loans? The data suggest they are using several coping mechanisms, such as lowering consumption or postponing essential expenses; raising resources from friends and social networks; and using large formal loans when available to settle old debts, including smaller informal ones accrued in past months. This use of coping mechanisms in the face of shocks is not unlike previously documented evidence. Low-income households use a variety of strategies to insulate their consumption and standard of living from the risk of volatile incomes; alternatively, they try to minimize the impact of income volatility by diversifying their occupations and resources. These strategies have a limited ability to protect households from poverty, and it has been shown that severe or persistent shocks are a major cause for chronic poverty.

The use of coping mechanisms by over-indebted borrowers differed from these practices in one regard — the incidence of coping behavior was highly correlated with the unaffordability of household debt and appeared to revolve around insulating repayments rather than consumption. Borrowers with more unaffordable debt used negative coping mechanisms more often and to a greater degree than others. Their financial behavior was not unlike the expected response to an income or health shock. But in this case, the shock came in the form of multiple non-negotiable loan repayments. Unlike a random occurrence, these “repayment shocks” persisted month after month.

Additionally, not only was the level of debt correlated with distress, but also with certain product features embedded in the loan contract. For example, a subset of borrowers experiencing highly volatile cash flows might have more trouble meeting repayments at certain times of the year. We found that these borrowers, for whom repayments were occasionally unaffordable (when calculated against a given month’s income instead of the average), experienced higher levels of distress, almost on par with those for whom the repayments were almost always unaffordable.

The implication for microlending is that poorly matched repayment schedules and other product features could be just as harmful as too much debt — and more harmful if combined with high levels of debt. This is a critical dimension of the experience of over-indebtedness, yet it is often overlooked.

New lending rules to prevent unsuitable loans

It is evident from the observed level of financial distress that current practices to prevent over-indebtedness are not effective. In fact, critical fault lines in their implementation have created an environment where unsuitable credit remains the primary coping mechanism even for over-indebted borrowers. It is also concerning that they focus heavily on limiting the amount of client debt while ignoring other aspects of borrowers’ cash flows that are significant in mediating financial distress. These include large seasonal or cyclical effects for specific lines of income or, even more generally, total income volatility (the median household in our sample experienced monthly income swings as high as plus or minus 45 percent) as well as large and significant uninsured (but insurable) risks.

Beyond better repayment assessments

Microfinance in India is no longer dominated by monopolistic or mono-product markets. With the licensing of several large lenders as small finance banks, the expectation is now that low-income households will have access to better financial services. This means not only easier access to a wider set of services, but services provided by institutions that are better equipped to respond to low-income households’ primary needs and vulnerabilities.

Many have argued that the continued success of lending to low-income households will require the evolution of robust mechanisms to assess clients’ capacity to deploy credit and manage repayments. By itself, this will not be enough to prevent borrower distress since repayments alone do not signal that a loan is suitable.

Lenders must also adequately detect clients’ cash-flow vulnerabilities and respond to them with appropriate design and service improvements, complementary savings and insurance products, flexible repayment schedules where appropriate, and best practices for delinquency management.

Read the latest version of the paper here. This article first appeared on the CGAP blog.


Guidelines for Suitability in Lending to Low-Income Households

By Vaishnavi Prathap, IFMR Finance Foundation

Img_1In December 2014, the Reserve Bank of India published the Charter of Customer Rights as a commitment to protecting the interests of consumers of financial services. The charter includes the Right to Suitability, defined as the principle that “products offered should be appropriate to the needs of the customer and based on an assessment of the customer’s financial circumstances and understanding”. The MFIN and Sa-Dhan, in a joint Code of Conduct, also enshrine a similar principle but specific to the context of lending: “We, as part of the Microfinance Industry promise the customers that we will […] conduct proper due diligence to assess the need and repayment capacity of customer before making a loan and must only make loans commensurate with the client’s ability to repay”. Both the RBI and the SROs directed financial institutions to understand the parameters of suitability within the context of their respective product offerings and to formalize policies to prevent unsuitable sales to customers.

In a new research paper published as part of our Working Paper series, we focus on biggest barrier that financial institutions might face in complying with this directive – a lack of clarity on what may be deemed suitable and how this is to be determined for each client. Towards this end, our new research investigates the nature and incidence of unsuitability in a competitive lending market and the variety of ways in which low-income borrowers may experience or cope with loan-related financial distress. Our findings are both a reality-check on the effectiveness of the current approach to customer protection (particularly the efforts to prevent borrower over-indebtedness) as well as a guide to how, going forward, lenders can institute formal processes to prevent unsuitability.

In our previous writing on this topic, we have acknowledged that successful suitability practices must be iterative and that even at-best, they can in no way guarantee positive outcomes for clients. The focus of both compliance and supervisory efforts must rest instead on understanding patterns in product-client interactions – especially when such interactions result in substantial hardship to clients – and meaningfully improving sales processes to prevent unsuitable sales.

Key Findings

The primary data for this study was collected in a year-long panel survey of 400 low-income households in Krishnagiri district, Tamil Nadu; the full sample included clients of 7+ MFIs and 20+ formal financial institutions. The survey adopted a financial diaries approach and a detailed socioeconomic survey was administered every 4-6 weeks to capture the dynamics of households’ cashflows. The resulting dataset has a primary focus on the details of borrowing and loan servicing but also rich detail on the volatility of occupational income, the frequent incidence of small and large shocks to household budgets and the use of other income sources, resources from social networks and a variety of financial instruments to smoothen consumption, repayment obligations and other expenses.

From the survey, we were able to create a full picture of borrower indebtedness across multiple institution types – perhaps more completely than the credit bureaus for microfinance clients. Comparing the sum of monthly repayment obligations to borrowers’ average monthly incomes, we found that one of every five borrower households in the sample held an unaffordable level of formal debt. If we included informal loans or factored in the volatility of incomes, an even higher proportion held unaffordable levels of debt for a few or all months of the loan tenure. However, the incidence of repayment delays or the proportion of delinquent borrowers was much lower, and only weakly correlated with households’ debt levels. Even at very high levels of unaffordability, borrowers were prioritizing repayments on formal loans over essential expenses, and willing to take on even further unmanageable debt to get through a difficult period.

Further, the average households’ incomes varied month-on-month by as much as 45% and as a result, even borrowers with sufficient year-end surplus were observed experiencing periods of distress and using harmful coping mechanisms comparable to those whose incomes were much lower.

Implications for Suitability Practices

These patterns in borrower behaviour are perhaps not new to experienced practitioners of microfinance and further, may only be a reflection of practices designed to achieve repayment discipline. What is alarming however, is the relative ease with which some over-extended borrowers remained undetected, and were able to continuously receive new formal loans on the same terms as others.

NBFC-MFIs are subject to regulatory directives that restrict the level of indebtedness per client and additionally, a large part of the non-NBFC microfinance lending is also required to be reported to credit bureaus so that it may be available at the time of loan appraisal. Notwithstanding, we find that critical faultlines in the preparation and use of credit reports placed as many as 33% MFI clients in the sample at risk of being mis-sold an unaffordable loan.

More critically, the types of client assessments that inform loan-making are largely unregulated and often do not triangulate borrowers’ actual repayment capacity (relying instead on unverified or indicative measures, peer selection and group enforcement). Our results show that in a mature and competitive market, clients with similar incomes and livelihoods may in fact have very different borrowing portfolios and vice versa. In this scenario, universal lending limits— such as those currently in effect— poorly safeguard customers’ interests.

Instead, determined efforts should be directed towards building market capacity to conduct thorough client assessments and to respond meaningfully to clients’ financial situation. Credit reports urgently need to be strengthened to reflect a comprehensive view of all formal borrowing, without exception. On the lenders’ side, the use of comprehensive “combo” credit reports will still fall short if not also complemented by a robust understanding of what portion of household income can be made available for repayments. Further, clients with unique liquidity constraints or cashflow risks must receive adequate insurance either through appropriate products or through modified terms of service.

This research highlights not only how critical these measures are for borrower well-being, but also the challenges involved in suitably serving low-income households’ financial needs. As a step in this direction, this research outlines two minimum components for suitability assessments –

  1. All lenders should ensure that loan amounts are appropriate and the agreed repayment terms are affordable for every borrower given their income flows, outstanding loan repayments (including self-reported informal loans) and critical payment obligations.
  2. Lenders must also evaluate the harms of selling standardized products to those borrowers with highly volatile cashflows or those with unique liquidity or flexibility constraints. Uninsured cashflow risks must be provisioned for in the assessment, product design or terms of repayment.

The paper also outlines recommendations for coordinated regulatory, practitioner and research effort that can enable successful implementation. 

The working paper is available online here and we welcome both questions and comments.


NBFCs’ Collection Efficiency Takes a Hit Post Demonetisation

By Bindu Ananth & Kshama Fernandes

Non-banking finance companies (NBFCs) represent an important linkage between the formal banking sector and informal segments of the real economy in India (wage labourers, smallholder farmers, unorganised retail, and domestic workers) through the channelling of credit from the former to the latter.

They have a significant presence in the microfinance, small business finance and commercial vehicles finance segments. Of the 11,682 NBFCs registered with the Reserve Bank of India as of end-March 2016, 209 were systemically important non-deposit taking NBFCs which are subject to more stringent prudential norms and provisioning requirements. Loans & advances by these entities alone accounted for around Rs 10.7 lakh crore. Through the data lens of collection efficiencies and disbursement volumes of over 100 NBFCs, we take stock of the impact of demonetisation on them. This also provides insights on the ultimate impact on the informal economy in India.

From November 9 onwards, NBFCs were not permitted to accept repayments in Rs 500 and Rs 1,000 denomination notes. Given the lack of access to bank accounts, most NBFCs accept repayments in cash from their customers. The average collection efficiency of microfinance NBFCs was 99.02% for the 12 month period preceding Nov 16. As of end November, collection efficiencies dropped significantly for these NBFCs and ranged from 60% to 90%.

Vehicle finance NBFCs reported a collection efficiency ranging from 60% to 70% with a higher cheque bounce rate and reduced overdue collections. Vehicles engaged in the movement of goods/ passengers which are “discretionary” witnessed an increase in idle time of 15-20 days a month from the normal levels of 8-10 days. Nondiscretionary goods, including agri produce and dairy, witnessed a lower impact.

Small business lending NBFCs reported a collection efficiency ranging from 65% to 85% with entities lending to small manufacturers and traders being at the low end of the range. Informal salaried customers have been as affected as self-employed customers with collection efficiencies of around 70%. This is true across urban and rural locations. In the affordable housing finance segment, collections continue to hold strong. These are largely selfoccupied homes. LTVs in this segment are much lower and reflect significant borrower equity in the asset. The norm for fixed obligation to income ratios in the informal segment is significantly lower and may provide a reasonable cushion to absorb short-term cashflow shocks.

Many microfinance NBFCs had put disbursements on hold for all of November 2016 and are now restarting disbursements gradually. Some restarted disbursements partly from their own collections. In the vehicle finance segment, disbursements are at 50-60% of normal levels on account of the slowdown in demand. Fresh disbursements in the small business lending segment have almost stopped with fresh logins dropping to 25% of the normal monthly volumes. Overall, disbursements have been affected also due to shortage of currency in the banking channel and a weekly cap on cash withdrawal. Going forward, we also expect an impact on disbursements in used vehicle finance due to the anticipated crunch on margins for fresh borrowing by the end-customers.

In pockets of UP and Maharashtra, demonetisation has fuelled some political risk factors in the form of demand for loan waivers by local politicians. This needs to be tracked closely and prevented from escalating by local offices of the RBI and the district administration. Going forward, NBFCs will need to re-engineer operations to significantly move away from cash collections. The task of opening bank accounts with full functionality for rural customers is far from complete. The availability of payment mechanisms such as the Unified Payment Interface (UPI) on feature phones will greatly help this category of customers from the advances in this area. There is also a need for a sharp increase in cashin/cash-out points, particularly in remote rural India to facilitate ease of transactions as the progression to cashless/ less-cash economies will take time.

The disruption will have a marginal impact on profitability of NBFCs due to foregone disbursement. We want to share our concerns on the negative liquidity and income impact on customers of these NBFCs which may not show up in collection data of lenders. Salaried workers in the informal sector have been hurt through delayed payment of wages and self-employed workers have seen significantly lower business volumes. Disruptions in credit impact consumption for low-income households in terms of reduced expenditure on essential items such as food and health. There could be a possible loss of trust in formal financial institutions. We need to work hard to restore an environment that will ensure predictability and credibility of these institutions among this large segment of India’s working poor.

This article first appeared in Economic Times.


The Power of Frustration

In a recent report by Wharton Social Impact Initiative & Knowledge@Wharton on Innovative Finance and the various forms it has taken, the report highlights among others, the multi-originator securitization (MOSEC) transaction that was first pioneered by IFMR Capital. Tracing the origins of MOSEC and how the idea, brought about by an underlying frustration at not being able to cater to small but high-quality originators, came into being. The article throws light on what has since been one of the key vehicles for IFMR Capital in its endeavour to enable capital access to partner originators that it works with.

From the article:

In June 2008, IFMR Capital, a non-bank financial company based in Chennai, India, had opened its doors with the express purpose of providing access to the financial markets to the millions of Indians who lacked it. But, the small- and medium-sized originators who were making loans to the population that IFMR Capital wanted to serve were constrained by the sizes of their businesses.

IFMR had been trying to persuade investors to buy some of the debt of these small microfinance institutions so they could make more loans. But investors were wary. They feared the risk from loans from a single small originator from just one area of the country that was possibly subject to the same natural disasters.

“They were very high quality originators, but they were very small. They were not ready to go to the capital markets,” says Mukherjee, who was CEO of IFMR Capital at the time and is now CEO of IFMR Holdings.

Finally, Mukherjee, deliberating with her colleagues, blurted out, “Why don’t we just pool?” What she was suggesting, securitizing the loans of small- and medium-sized microfinance institutions, originators with portfolios as small as $500,000, had never been tried.

In January 2010, a little more than a year after Mukherjee asked the question, IFMR issued its first multi-originator securitization (MOSEC, now trademarked), a $6.5 million issue bundling some 42,000 microloans, with an average size of $200, from four originators. To date, IFMR has issued 89 MOSECs for microloans worth more than $675 million, representing some 3.7 million loans securitized.

Using a similar model, it has done another $2 billion of MOSECs of affordable housing, small business and agricultural loans. The securitizations give the microfinance institutions access to low-cost capital at a price some 200 to 250 basis points lower than what they’d had previously, and to a new group of investors, including mutual funds, private banks and high-net-worth individuals.

Crucial to turning the idea into action was the special combination of people around the table at IFMR, says Mukherjee. Besides herself, with years of experience in structured finance at Morgan Stanley and Deutsche Bank, was Kshama Fernandes, then chief risk officer of IFMR Capital and now CEO of IFMR Capital, who had deep experience in Indian banking and was a well-known figure who provided credibility to their at-the-time unknown institution; Bindu Ananth, the president of IFMR Trust, whose idealism was essential to making the group press on and tackle problems rather than being discouraged by obstacles; and Gaurav Kumar, the head of origination, who intimately knew the individual lenders and the details of their business and could vouch for their creditworthiness.

“There was nothing in the law that actually prevented it. It was an innovation waiting to happen,” says Mukherjee. “At the end of the day, you apply the same tools and principles of diversification (you’ve done in the past). What we did was contribute to the learning in developing our own underwriting standards for microfinance and small business lenders. What we brought was discipline, expertise, and we became the expression for self-confidence for these asset classes.”

The securitizations have now become so commonplace that they are no longer considered innovative. However, IFMR remains alone in both structuring the deals and retaining a portion of the debt on its own books, says Mukherjee. That way, IFMR ensures that interests are aligned and that the deals are designed for long-term profitability and sustainability, she says.

Read the full report here.


In Conversation with Kalpana Pandey, CEO, CRIF High Mark

In this blog post we feature a conversation between Bama Balakrishnan, CRO, IFMR Capital and Kalpana Pandey, CEO & Managing Director, CRIF High Mark. CRIF High Mark is one of the four credit bureaus that operates in the country.

What are your thoughts on the evolution of Credit Information Companies in India and your experience in this space?

Kalpana Pandey

Kalpana Pandey

India had one Credit Information Company (CIC) from 2004 till 2010. CIC(R)A 2005, the regulation for CICs, came into existence in 2006-07. Pursuant to that, CRIF High Mark (then High Mark) along with two other companies got license to operate as CIC in 2010.

CRIF High Mark was founded with a vision to create a comprehensive and all inclusive credit bureau. The Andhra Pradesh microfinance crisis of 2010 underscored the need for a bureau coverage for the sector, so we took the opportunity to partner with various participants of the microfinance industry and launched India’s first Credit Bureau for Microfinance lending in March 2011. We now operate World’s largest Microfinance Database and over past 5 years, we have supported this sector with reliable information on over 10 crore credit decisions.

CRIF High Mark now is a full-service credit bureau providing coverage for all borrower segments – group lending, individual lending and MSME/Commercial lending. We now work with not only MFIs but also Banks, NBFCs, Housing Finance Companies, RRBs, Coop Banks etc.

RBI since the last year onwards requires all financial institutions to report to all credit bureaus. This means CIBIL must be getting microfinance data, High Mark must be getting data from banks, HFCs, etc. Have you seen good progress in this process?

In addition to Microfinance data, as mentioned earlier, CRIF High Mark was receiving data from major Banks, NBFCs, HFCs, Coop Banks, and RRBs on retail, agri, rural, MSME and corporate lending even prior to 2015. We were missing data from a few players. Since the RBI Jan’2015 notification, these missing gaps have been filled up for us. Similarly, CIBIL must be getting microfinance data.

All systemically important institutions are now compliant with this regulation, and sharing data with all credit bureaus. The smaller cooperative banks and NBFCs are gradually signing up as members with CICs. Data sharing will be the next step for such smaller institutions. Each bureau deploys a filter criteria while uploading data from the files shared by Member institutions into its database. Our technology helps us differentiate ourselves in absorbing the maximum data out of those files and making sense from weaker data.

Bama Balakrishnan

Bama Balakrishnan

Our understanding is that compliance in this regard is still catching up – institutions are going through the process of registering with all the bureaus and would in due course commence sharing data regularly.

The other part which I wanted to understand is, what is your sense of the readiness of credit bureaus in being able to process this kind of information – such as the JLG data – which is different from traditional retail lending?

Where do you think the gaps might be even as institutions start reporting – do you think more needs to be done in terms of capacity building, technology, infrastructure by the bureaus to make sure that they can actually use this information and irrespective of which bureau the lending institution is pulling the report from, they would still get the full picture of indebtedness?

All large players are members of all credit bureaus and have shared data with all CICs. The smaller players while are registering with the bureaus, however these players do not have the IT wherewithawal and have higher dependence on their IT vendors – they have challenges with sharing of data, they will share data once their vendors are able to help them. Our Data Ops team hand-holds such smaller institutions through this process supporting them with mapping of data, file structure and best practices.

As regards data sharing, RBI has standardized the data sharing formats, and all institutions are expected to share data in these formats. CRIF High Mark’s data format was chosen as the format for group lending. Minor additions have been made to this format to cover reporting of SHG data. All these changes are now made in consultation with a Technical Working Group formed by RBI for this purpose.

One has to realise that the input data is becoming similar for the CICs, but each bureau brings its own differentiator through its underlying technology and products. Now CICs give Credit Score in the same range (300-900) to make it easier for people to understand.

In addition all of us expect an overlap between SHG and JLG — we found 40-45% overlap between the JLG and SHG customers on tests we did on data from a few banks. Banks, NBFCs and MFIs are entering into each other territories. So as a user, one should be able to get comprehensive view of customer in a single report. Though the group lending format is different from retail lending format, we are able to process these independently but bring them together to give one picture of the customer. We already have products to provide such full picture of Indebtedness of a customer across SHG data, JLG Data and Individual lending.

We have seen some KYC issues with microfinance customers where we see customers using multiple KYCs with different institutions. We know that bureaus may use relationship information to triangulate data but this may be approximate. With UID coming in and MFIN’s push to ensure authentication through UID, do you see the situation improving in terms of better triangulation of the identity of a customer?

When we launched our bureau for the microfinance segment, objective identifiers such as Voters ID etc were not consistently captured. Even names and addresses were not captured completely. Our technology worked on whatever was available (including relationship names) to bring out most relevant results.

Over the past five years, data quality has crossed many levels – IT systems are better, processes have improved, field staff is sensitized — objective KYC IDs come in now but are largely limited to Voters ID, Aadhaar and Ration Card. MFIN’s push to seed Aadhaar in every new loan being disbursed is seeing fantastic results.

Fragmentation of customer’s data across multiple KYC ID is not unique to Microfinance sector. It is observed in Retail lending space as well since PAN, Passport and Driving License ID are valid KYC IDs. Our bureau systems are tuned to handle these situations to provide comprehensive and also accurate credit reports.

The technology is not biased towards only objective KYC ID, it makes sense of data available across all fields – even single names, partial Voter ID, partial addresses etc – to bring best possible matches. Having said that, it doesn’t mean we would not use KYC ID – better KYC regime will certainly help. Today, we provide millions of credit reports every month with very minimal errors. We constantly invest in fine-tuning our technology, learning from the newer data that we see and the reported errors. With much better availability of a consistent KYC ID (such as Aadhaar) will minimize these errors.

One question on the recent trends of people trying to build platforms for lending using traditional and non-traditional data and algormithic underwriting. Do you think the Indian market is ready for these business models and secondly, do you see this transforming the microfinance lending business? We know that there is not much data, but do you think there is a possibility that with credit bureau data building up and more of it becoming available, people could think about such a business model where there is not much data available other than payment track record. Is that a possibility you have seen people starting to explore?

Our country has just seen use of traditional data (formal lending data). There is defintely an opportunity in exploring use of non-traditional data such as telephone or mobile data, utility bill payments. Many countries have seen benefits of expanding the coverage of population within the bureau with use of such non-traditional data. There have been studies highlighting linkages of such non-traditional data especially payment data with individual’s credit behaviour.

There was an RBI Committee to evaluate the possibility of getting utility data and telecom data into Credit Bureaus. The committee concluded that Telephone use data is meaningful, would help in the cause of inclusion and it should be brought into the credit bureau system. Some legal and regulatory amendments are required to enable telecom service providers to share data with CICs.

Many FinTech start-ups are bringing in novel ideas around providing alternate means of scoring customers and also on algorithmic lending. The success of these models are to be seen, but such new ideas is certainly driving more innovation in the lending related technologies. Most of these businesses are digital in nature, so they may not really be targeting the same customers as that of Microfinance institutions.

We are closely following these developments. RBI is also keenly watching the space, and has already taken initial steps in understanding the various models.

Looking forward, in the backdrop of small finance banks and payments banks that are about to enter the system and the increasing thrust towards financial access driven by various initiatives both by the regulator and the government, as a credit bureau, how do you see the road ahead and some of the key challenges that bureaus in general have to contend with going forward?

Small Finance Banks are none other than existing Microfinance players who will now be diversifying as Banks. They are not new to Credit Bureau environment, but will now expand beyond Microfinance lending and also beyond lending. They will now require Credit scores for Individuals as well as for MSMEs.

For Microfinance sector, the code of conduct guidelines may require a revisit. It currently applies only to NBFC-MFIs, but since Banks and other players are also competing in the same space, we suggest to make these guidelines applicable to all players into direct JLG lending. This is assuming more importance given many MFIs will be SFBs over next few months.

Payments Banks are not into lending so right now they cannot work with a credit bureau. But the payment data generated by Payments Banks is also a strong source of alternate data. Payment data from Payments Banks can expand information coverage across very large expanse of population, and could certainly supplement credit underwriting.

Credit Bureaus will have to constantly evolve to keep up with these changes, and to remain relevant. Newer businesses will have newer needs. Alternative data will require to be merged with the traditional data to make better sense for the customer. The road ahead seems very exciting.