Challenges with MSME lending and how Embedded Finance solves them

Why do MSMEs remain chronically credit-starved? Are there models for credit distribution that can solve MSME financial inclusion? We address these questions and propose an innovative partnership-based model called “Embedded Finance” to meet these challenges.

According to a report by IFC, India’s 56.1 million MSMEs contribute 31% to the GDP, employ 124 million people, and make up 45% of India’s exports. Although they are the backbone of our economy, they are extremely credit-starved. The current addressable credit gap forMSMEs in India is still estimated to be at $397 billion.Read a full list of credit products here.

Systemic Challenges to MSME Financial Inclusion

Formal credit distribution infrastructure is still developing

No Sachetized MSME-focused products
Most MSM’s require credit for filling working capital gaps. This requires small amounts (₹5–15K) for small durations (2–10 days), also known as sachetized loans. These transactions are extremely rapid and high volume. To be profitable, sachetized loans require a technology product-focused approach, which sometimes includes acquiring a large number of customers at zero or negative transaction value and effectively driving repeat behavior through multiple touchpoints. This relies on machine learning models that enable banks to understand and cross-sell to borrowers

The current bank-driven lending model is unable to cope with the size and speed of these needs and also runs afoul of most risk managers. The lending process of banks is focused on large ticket size loans owing to the cost and time required for underwriting. Sachetized products will need a complete reimagining of the lenders’ onboarding, decisions, and loan servicing technology stacks.

Lack of open APIs
Lenders can make some of their functions accessible to tech players by providing Open APIs, enabling tech players to collaborate and build atop lenders’ infrastructure. However, lenders do not have open APIs. Digital platforms with reach therefore cannot easily link with lenders to provide credit to their customers.

Lenders are risk-averse

Lenders focus on thick file customers

Banks are traditionally risk-averse and often don’t cater to customers without rich credit bureau data. They rely on the past loan performance of the enterprise rather than future opportunities. Banks rarely leverage alternative data (cash flow data or device data) to identify credit-worthy customer sets.

Traditional banks serve NTC customers in a limited and often ineffective way. This excludes 80% of MSMEs from formal credit since they don’t have a bureau history. MSMEs are therefore stuck in a vicious cycle — their applications are rejected due to a lack of credit history and they are unable to build a credit history as they are unable to avail formal credit.

Lenders rely heavily on assets

Banks assess borrowers’ creditworthiness based on their assets, rather than evidence of their cash flow. Popular asset-based lending models such as gold loans and loans against property have hence become the mainstay of MSME financing. Not all MSMEs have assets to collateralize their loans, or have their assets already earmarked against term loans. This leads to smaller businesses being left out, especially for sachetized loans for working capital gaps.

No avenue for MSMEs to make their data count

MSMEs are accumulating rich data sets, while using a plethora of digital tools such as khata-apps, online accounting, online cataloging and B2B E-Commerce apps. They also have rich alternative data on their smartphones. Proven credit models and technologies are available to leverage this data for cash-flow based underwriting. These datasets are proven to be much more effective compared to traditional methods. However, understanding and acceptability of these datasets among lenders remains low. When using traditional methods, lenders manually underwrite borrowers, which is a time-consuming and expensive process that leaves out a large chunk of MSMEs.

Lack of visibility on the MSME Sector for Financial Institutions

Most MSMEs are structured as proprietorships and partnerships There is no central registry of MSMEs, so institutions have to work on broad estimates about their geographical location, or the industry they operate in. This lack of data handicaps financial institutions in meeting the credit needs of such enterprises.

Practical Challenges

While technology solutions have started bringing MSMEs into the fold of financial inclusion, the fact remains that MSMEs have recently digitized and face a unique set of practical challenges. These include:

Low familiarity with digital solutions

Low acceptability of digital footprint for underwriting
While there are measures in place to facilitate digitization (such as GST and advent of retail-tech platforms geared towards MSMEs), adoption remains slow. Most small businesses prefer informal methods of cash flow documentation such as bahi khata and register.

Most MSMEs aren’t formally registered. Their data is available as a digital footprint, but not with formal sources.

MSMEs are unfamiliar with UI/UX norms
MSME owners aren’t familiar with regular UI/UX flows, which are derived from Western apps and are suited to Tier 1 city demographics. The user journey is often complicated, has a lot of points of friction, and includes large, complex forms. Digital discovery of credit i.e discovering several credit offers and comparing them online is difficult for them as well

These factors lead to MSMEs favoring informal sector for financing, or self-financing, because they have a hassle free process, are dictated by personal relationships, and have shorter turnaround times. However, the terms of informal credit hinder their growth of MSMEs in the long run.

Low financial literacy related to credit

Limited understanding of credit products
Due to their lack of affinity to technology and formal lending institutions, MSMEs often can’t find the right credit products at the right time suitable for their needs. MSMEs have diverse use-cases and hence require customised credit solutions.

Limited understanding of credit scores— Often, MSME owners are unaware of their credit bureau footprint. Most MSMEs owners do not understand the consequences of defaulting on loans, the impact it has on their creditworthiness.

Establishing Business Identity is hard

Most MSMEs are informally run and family-owned. owners are not equipped with the required documents and information. GST certificates are often not handy and ownership proof is often non-existent. There is also significant commingling of cash between the “business” and “personal” accounts. This becomes a major roadblock for lenders trying to determine the legitimacy of such units.

Language barriers

According to research, 80% of India’s users prefer their interfaces to come in vernacular languages, not English. But, English remains the language of choice for building new technology. In order to effectively tap into the largely vernacular-speaking MSME segment, apps, web pages, and marketing collateral need to be in the local languages.

How Embedded Finance addresses these challenges

Embedded finance combines sophisticated tech infrastructure, know-how of distributing financial services at scale, with the capital from financial institutions to increase credit access for MSMEs. Here’s how Embedded Finance addresses the challenges listed above.

Platform Data Underwriting

Embedded finance leverages platform data for cash flow-based underwriting. Creditworthiness is then based on data available with various digital platforms. For example accounts receivable from a khata app, data on past orders from a B2B E-Commerce app are used to augment creditworthiness decisions

Tailoring user experience in close collaboration with digital platforms

Embedded finance tailors loan application experiences in collaboration with digital platforms. Through this enhanced understanding of the customer, the customer experience is engineered to become flexible, simplified, and guided. credit is then offered in-context to reduce the effort of digital discovery and application for the MSME borrower.

Leveraging the relationship built between digital platforms and end-customer

Embedded Finance companies leverage the trust built by the digital platform to offer loans, facilitate applications, and repayment. They can educate MSMEs via the anchor platform.

Digital Platforms also have rich demographic data about MSMEs that isn’t centrally available. This data can be leveraged to understand the heterogeneity of the MSME sector and tailor financial products and processes to each segment.

Conclusion

Financial Inclusion of MSMEs is a complex problem, and requires financial institutions, digital platforms, and fintechs to forge deep partnerships. It requires building a technology-driven credit product innovation and distribution strategy. Lenders must digitise their processes and leverage alternate data underwriting to lower their acquisition costs and use data deeply to recover them by driving repeat transactions. They must leverage partnerships with Embedded Finance infrastructure providers to quickly go to market with MSME credit products and iterate rapidly to tailor and innovate for the heterogeneous MSME sector.

Learn more about how FinBox is revolutionizing Embedded Finance: https://www.finbox.in/