Why is SME financing so difficult? And how to deal with it

There are 63 million small and medium enterprises (SMEs) in India, and they are one of the major sources of employment here. In addition, they represent about 50% of the country’s exports. Millions of entrepreneurs would have been created by this industry. The most exciting success stories in a variety of manufacturing and service sectors have recently been created by Indian SMEs. For India to achieve its goal of having a $5 trillion economy by 2025, the rise of SMEs is essential.

Despite their contributions, the main barriers for the SME sector have been stable cash flow and access to finance.

Being able to effectively assess the SME’s ability and willingness to pay is the biggest challenge for the majority of credit institutions, even those explicitly trying to enter this market. For this reason, the majority of SMEs find it difficult to obtain commercial financing from banks and other financial institutions and are forced to turn to unofficial sources of financing such as moneylenders. These are not only extremely expensive, but also often sporadic, forcing these businesses to operate well below capacity.

From a technology perspective, there should be a small, credit-based SME lending process that is both flexible and affordable enough to accommodate different SME business models.

Non-traditional risk assessment methods

Typical collateral that would reassure lending institutions, such as big books, long-time marquee clientele, heavy machinery or factories, etc., does not exist for SMEs. But the fact that SMEs represent nearly 20% of GDP is enough to show that this industry is functional. Lending institutions now need to take a new perspective on the problem statement. They should consider alternative methods of credit assessment which should be based on a careful examination of the available data points in a methodical and scientific manner, rather than focusing on the absence of collateral.

There are non-traditional data sources available in the form of sales records, customers, suppliers, temporary and permanent employees, business seasonality, and local environmental aspects such as location, place of business. raw material supply, local demand, etc. These data points can be compiled, summarized and analyzed using technology to create smart SME credit scoring models.

Multiple business models

SMEs operate under a variety of business models depending on the sector in which they are located. They will operate in a variety of ways, take varying degrees of risk, and adhere to various payout cycles, among other things. No two SMEs will have the same business model, not even within the same sector. They will serve a variety of markets. Therefore, the question is to develop a credit reporting procedure that can accommodate this variation without sacrificing efficiency or accuracy.

To overcome this, technology must be used to provide solutions. Starting with industry-specific credit scoring models and having the ability to add more features to comprehensively assess risk could be one solution. These can be related to location, target markets, and sources of funding or working capital. And after that, he can delve into the intricacies of a company to compare it to the best, average, and worst performers in the industry. Typical payment cycles and late payments, number of employees, provisioning rates, and some persistent issues the business faces can all be examples of such metrics. An SME’s revenue rating would likely be a reasonably accurate predictor of repayment capacity if several of these aspects were considered and studied.

Flexible financial product structure

Credit institutions are not able to advertise the same financial product to all SMEs, because no two SMEs will have the same business model. The product must be tailored to fit the particular sales and cash flow cycles of an SME. And the lending institution must have a high level of expertise and experience to achieve this. Should the loan be repaid on a monthly, quarterly or semi-annual basis? Can larger payments be made when a seasonal business is full of cash and smaller payments when it is not if the business is seasonal? Can payments be adjusted quarterly to reflect changes in cash flow estimates while covering the lending institution’s baseline costs? Can planned or unplanned moratoriums between payment cycles occur on certain loans without incurring penalties?

All of these facts indicate that it might not be enough to simply modify an existing loan product to meet the needs of an SME with erratic cash flow or high seasonal income. A technology solution should give designers the freedom to create custom product versions tailored to the demands of specific SMB customers without complicating or clogging the entire loan application process or sacrificing turnaround time or customer service.

The transaction price

The process of determining an MSME client’s credit eligibility can be costly and time-consuming. A typical appraisal cycle involves filling and collecting sheets of paper through numerous interactions with the consumer as well as a high level of cooperation and iteration between sales and loan officers. Loan processing time, which results from manual procedures, numerous iterations between the sales force and credit teams, and extensive documentation, accounts for a significant portion of the cost. The problems of automating field processes and the ability to analyze large amounts of data more meaningfully and faster can both be solved with the help of advances in mobile technology.

Additionally, a smart platform can consume specialized services in areas as diverse as bank statement analysis and credit scoring based on non-traditional criteria to create a strong and successful ecosystem and manage lending activity. SMEs more quickly and at lower cost.

Macroeconomic elements

Instead of an SME’s reluctance to pay, much of the risk in SME lending stems from a change in the macroeconomic and environmental circumstances governing a business that can play out adversely.

Changes in the business environment can cause a lending business that was lucrative when funded to suffer losses. Ongoing risk analysis is just as vital to the MSME lending sector as initial credit analysis, so it is crucial for credit institutions to keep a close eye on macro and micro issues affecting their clients. In this situation, technology can be used effectively to set up a process to collect, analyze and monitor relevant data to watch for early signs of stress.

This, combined with frequent communication with clients, can contribute significantly to lenders’ efforts to maintain healthy asset quality.

Conclusion

The ability to create financial solutions tailored to their particular needs will be the main trend in the BFSI sector over the next few years due to the growing proportion of SMEs in the economy, which is supported by a favorable government push. The fintech industry will seek to develop platforms and tools that will simplify SME lending and significantly reduce perceived risk.



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Disclaimer

The opinions expressed above are those of the author.



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