On one hand the growth of Micro, Small and Medium Enterprise (MSME) is mushrooming in India, while on the other hand survival of MSME sector is getting challenged due to lack of availability of adequate finance. With the economy heading towards a downward spiral, more and more businesses, especially MSMEs, are turning to fintech lending institutions and banks for financial help and loans. The government has also churned out schemes and measures for MSMEs’ revival. This has created a vast opportunity for lending institutions to plan their assets and build a robust credit portfolio.
Challenges in lending to MSME
1. High acquisition cost
Given the long lead cycle, documentation requirements and complex eligibility criteria, lending to businesses result in high acquisition costs for banks and financial institutions. The MSME financing requirements however are often of smaller ticket size which does not justify the high costs. As a result the vast MSME market though a ready market for lending cannot be tapped.
2. Lack of enough data to fill credit models
Large entities, listed companies and reasonably sized businesses have to meet with various compliance requirements. As a result, they often prepare reports such as balance sheet, trial balances, inventory statement etc. at frequent intervals. Traditional credit models so far have been fed with numbers coming from such reports. However, due to relaxed compliance obligations MSMEs may not be preparing reports and also do not have large teams dedicated for legal and compliance issues. As a result, creating reports and data as per the lending institutions’ format, which could vary from one to another, turns out to be a time consuming and costly activity
3. Concerns on data authenticity
Even if data is prepared by MSME as per bank’s template, establishing the authenticity is another challenge given that it is self-declared and also may not be audited by third parties or accountants.
So this makes the lending to MSME a risky proposition.
GST Data Based Lending – The Emerging Case for MSMEs
Reliable, Recent Data Source : GST Data
GSTis often looked upon as a heavy-duty transformtion when it comes to compliance requirements. However, alongwith compliance requirements, it has also brought along availability of granular and timely data. With reporting frequency ranging from Monthly to Quarterly reporting and submission of invoice level data in GST Returns, it has become one of the richest data source to churn and get insights into business mechanics. With public availability of compliance related details of GST registered entities and detailed information available on consent, the credit models have now evolved to handle GST data.
With the advent of technology, several old and rigid mediums and processes that reduce efficiency can be dropped. With technology, financial lending institutions can effectively carry out their lending processes to businesses and MSMEs without having the hassles of traditional and elaborate credit appraisal process.
GST system being fully API driven and standard data definitions for all GST registered entities, automated and system driven risk assessment models have emerged. The reduction in time and cost for loan processing, makes the MSME market lucrative. While the credit appraisal model is adapting to this new data source, even as of today, There are numerous Fintechs, neobanks and technologically advanced banks who have their mobility and quick lending solutions making it literally possible to get loan amount transferred to the borrowers account within few minutes and with few clicks.
GST Data based lending gives a more realistic view of business operations and hence better estimate of the business’s credit-worthiness. GST Data based lending can be transformational if used correctly. It is not only just a more efficient way of lending but also a safer one.
Benefits of use of GST Data and Technology
Let us understand how technology and GST data together can help lending institutions:
Here are some of the benefits of data-based lending:
If technology is leveraged properly and is supported by GST data it can help in reducing much of the operational cost. Fintech companies, banks etc. will save all the cost that goes about in traditional asset-based lending procedure. Fintechs and banks can use data-based lending software tools that can aid in the process and bring down the lending cost.
2. Saves a lot of time:
In traditional and non-digital credit appraisal processes, checking the credit history of the business takes a lot of time and resources on part of the lender. The decision takes time and again it takes months to process the loan smoothly to the businesses. On the other hand, data-based lending – especially the new GST data-based lending is more systematic and can offer the information required to the lender in just a matter of a few minutes. Thus the process becomes very smooth and saves a huge amount of time.
3. Reduces the risk factor:
The interdependent nature of GST returns and an external system i.e. GST system being the centralised and hence single source of truth, add a layer of reliability to the data. While the formal acceptance of invoices is not yet implemented via GST returns, the flow of data from supplier’s return to buyers return does act a basic check and balance.
Further, advanced AI and ML methods and continuous learning algorithms help is making the credit assessment and risk profiling accurate and robust.
As bank or lending institution, you have your credit models ready, while as fintech you have developed assessing algorithms. All you need now is the GST data and IRIS Credixo is the best enabler to go along with.
IRIS Credixo – a cloud software that empowers financial institutions with data-based lending using GSTN Ecosystem:
India is expected to have huge credit growth across sectors and more lending to MSMEs is in the offing. This provides us with a unique opportunity to re-imagine credit products like never before.
IRIS Credixo, our credit assessment and monitoring tool, helps lending institutions to move from traditional and manual-credit assessment process to automated and data driven lending. The likes of Banks, NBFC’s and Fintechs can simplify their credit assessments with consented GST data. This helps to bring down their cost of processing and arresting increase in NPAs. Use of GST data transforms turnover and cash flow based financing to one based on the first hand, real-time information.
How does IRIS Credixo work?
IRIS Credixo offers set of APIs covering publicly available GST data and consent based data filed in GST returns. Additionally pre-processed data sets, reports and insights are also available as enhanced data APIs which can quickly plug into any system. Banks, lending institutions and fintechs can integrate these APIs in their credit models and provide faster and seamless lending experience to the MSMEs.
IRIS Credixo APIs can embed into your existing credit appraisal or loan origination systems. Alternative, institutions can also build new applications and expand to new use cases based on the GST data available.
A full-blown web-application is already set-up for IRIS Credixo, which help data users i.e. the banks and fintechs to visualise the spread of GST data.
Credixo stands at the intersection of Data and Lending Experience. It allows lenders to grow volumes, stand out from the competition and gather meaningful customer data to provide seamless “lending in the box” credit experience and design tailored customer journeys.