The SME industry is the cornerstone of the Indian economy accounting for approximately 48% for all exports and around 30% of the country’s GDP. It has been the key propeller of economic growth, innovation and employment generation in India. But, lack of financial resources from conventional lenders has been a major hurdle for its growth.
Similarly, lenders have also lacked adequate mechanisms to measure risks and protect their investments. Now, with advanced technologies like Artificial Intelligence (AI) and Machine Learning (ML) lenders could explore opportunities for dynamic and equitable lending practices specifically across the SME industry.
Need for Digitization of Banking Industry for SME Lending
According to estimates, the size of the Indian SME lending industry including the size of transactions among different players stands at Rs. 35 trillion (as on March 2024). Even though the Government of India has implemented a number of policies and programmes to address funding concerns for SMEs, there are several loopholes existing which hinder its ability to operate effectively. A Mavenark report suggests that the Indian SME industry faces a credit gap of Rs. 28L Cr. signifying a sizable unexplored lending opportunity.
Lack of necessary paperwork, compliance reports and adequate credit score, etc. led SMEs to borrow funds from the informal sector to meet their financing requirements. However, Digitisation of financial services could be a giant leap for closing this huge credit gap for SME lending gap in India.
Digitization and Process automation could assist lenders in increasing efficiency and lower the cost of lending for lenders in India. For instance, the usage of alternative data sources and big data analytics could help to fetch additional data sources for credit risk assessment processes, enabling certain SMEs access to funding which was not possible earlier.
Additionally, innovative techniques such as Open banking, digitization of business operations, sharing economy, etc. could offer inclusive data on SME operations and their cash flows enabling SMEs access to personalised financial products.
AI in SME financing
Role of Open Banking for SME Lending
Along with the advancement of lending practices in India, Open Banking has the potential to become an invaluable tool for lending practices helpful to better serve neglected consumer segments and SMEs businesses. Conventional credit score models often include information from three major credit rating agencies with outdated information. Open Banking could offer instant access to up-to-date financial information which can improve accuracy, speed and economy of lending decisions.
Additionally, the ability to view real time financial data could be one of the key benefits of Open Banking. Traditional lending may not consider businesses with limited or no credit history, Open banking allows lenders to assess applicants on the basis of real time data (i.e. cash flows, current business revenues, supplier transactions, etc.) apart from limited credit history.
For instance, instead of patiently waiting for applicant SMEs to submit copies of balance sheets, lenders could make faster lending decisions by extracting banking data, examining income and expenses in a matter of minutes. AI models analyze cash flow patterns of SMEs improving accuracy of affordability assessments.
Use of AI for Crucial Lending Functions
Conventional Lending systems which could involve lengthy procedures, complicated processes and lack transparency are being progressively substituted by AI powered systems that offer speed, efficiency and personalization. AI technologies have evolved from a theoretical concept to a revolution across major industries, especially the financial sector.
New technologies such as machine learning and artificial intelligence have drastically altered the SME financing industry by providing solutions to long standing challenges. Now, SME business owners have access to information to help them make better borrowing decisions, build strong credit profiles, and get loans approved faster. Other than this, here are some of the ways in which these technologies are helping to improve SME lending processes-
Faster Approvals and Disbursements
SME businesses may sometimes need quick access to funds to not to miss out on growth opportunities. While traditional lending systems could take weeks or months to be approved, AI technologies could help the process of loan application to be completed in a matter of minutes. Automated credit rating processes and borrower data analysis in real- time, could help lenders to ensure easier and quick access to funds to SMEs.
Personalized Customer Experiences for Borrowers
The capability of AI to handle enormous volumes of data enables lenders to provide business owners with customized services. It can obtain the necessary data to create required data points, including personal as well as business to business credit, etc. as it knows lender eligibility requirements.
Further, AI algorithms could offer personalized financial advice to the customers through in-depth analysis of their past transactions, market patterns as well as their financial behavior. Such adaptable strategies go beyond standard lending procedures and offer businesses access to personalized funding solutions tailored as per their requirements. For instance, an AI powered lending platform could recommend a certain loan product on the basis of type of business, its objectives and financial health.
Improved Consistency and Speed in Underwriting for Lenders
AI could also assist lenders to leverage their lending skills by consolidating and automating the professional expertise and knowledge of skilled underwriters. It reduces the risks of encountering underwriters who are inexperienced with a business owner’s financial situation. It also decreases the likelihood of errors combined with regular audits by experienced individuals who understand borrower requirements across different industries.
Although human consideration is necessary for data analysis and recommending appropriate action, to ensure certain credit facilities have intended results, AI could help to reach the decision faster through augmentation, collection and data processing. Thus, with major tasks automated by AI, skilled underwriting analysts could focus on regulation checks to ensure every borrower receives a thorough assessment.
Document Preparation and Collection for Lenders
AI enhances workflows and procedures using machine learning algorithms, which renders them adaptable to ever-evolving business demands. AI systems are tailored to collect and store documents required for different applications. It accelerates document collection and offers lenders with useful credit insights on applications. Such adaptability ensures lending institutions can keep up with evolving trends without having to incur large expenses on technological upgradation.
Data-Driven Risk Evaluation
AI powered systems could analyze and process massive data volumes from different sources which could help businesses to comprehend risks involved in SME lending space. Rather than relying solely on credit score and credit history, AI systems could incorporate a wide range of metrics i.e. past sales records, payment records and customer behavior, etc.
Furthermore, a detailed evaluation of additional elements like market dynamics, industry developments, economic insights, etc. AI algorithms can also provide a detailed picture of a SME’s future growth prospects and repayment potential. These data-driven procedures produce accurate risk assessments through elimination of human error and bias from decision making. Additionally, research indicates that such lenders are more likely to offer loans to SMEs normally rejected by larger financial institutions.
Access to Alternate Financing
AI powered solutions facilitate SME businesses access to other alternative means of financing i.e. invoice financing, peer to peer lending, income-based financing along with traditional loans. These alternative means of financing have lesser stringent requirements compared to traditional loans including greater flexibility for repayment.
AI powered lending systems make it easier to examine the feasibility of alternative financing sources by assessing a greater range of data. For instance, AI may help to analyse the monthly revenue of a business and forecast its future profits making revenue-based financing more secure. Thus, SME businesses failing to qualify for traditional lending could look for alternative means of financing to meet their business needs.
Future of SME Lending in India
The SME lending industry is expected to rise tremendously in the future due to changing business requirements and technological advancements. Some key future trends in SME lending could be-
Financial Institutions and Fintech Working Together
The growing popularity of digitalization and online payment systems has led banks to consider collaborating with online fintech service providers. Such collaborations have the potential to enhance loan disbursement for SMEs. For instance, credible banks are partnering with prominent financial companies offering competitive business credit cards. Such credit cards help SMEs to meet their cash flow requirements with simple transaction procedures and relaxed norms for repayment.
More Emphasis on Process Automation
Subsequent advancements in AI and Machine Learning techniques are poised to simplify and further automate SME lending processes. The digitally verifiable information about prospective customers will eliminate the need for enormous paperwork and expedite the loan approval process. Automation will also assist lenders in allocating resources as efficiently as possible which will further reduce operating expenses and overhead costs for applicants. Thus, automation of manual processes will play a crucial role in simplifying SME financing in future.
Higher Security Through Blockchain
Blockchain technologies will revolutionize SME funding by assisting in provision of safe and impenetrable transaction records. Blockchain technology will assist to build trust between the lenders and borrowers through fraud prevention and increasing transparency leading to a safe and robust lending ecosystem.
Advancement of Neo-Banking Facilities
Neobanking facilities are financial institutions that do not have any physical branches and are available digitally only. Since these institutions offer credit facilities at cheaper rates of interest with lesser compliance requirements than conventional banks, they have grown more prominence among SME businesses. Moreover, their user-friendly interfaces allow quick loan application and disbursements which is beneficial for most SME businesses.
Growth of Alternate Financing Solutions
With the advent of the fintech industry, a variety of alternative funding options have emerged particularly for small businesses in India. Such funding options could be chosen by businesses as per their growth and expansion requirements. Some popular financing options which are expected to be popular among SME businesses include- Peer to peer lending, invoice financing, crowdfunding, etc.
Government Based Lending Programs
Considering the significance of the SME industry, the Indian Government has put in place certain programs encouraging its expansion. These programs have been digitalized from this year with the primary objective of enhancing SME’s access to financing and closing the credit gap. PM Mudra Scheme, Stand Up Scheme, Credit Guarantee Scheme, SIDBI Direct lending, etc. are some of the key programs launched by the Government for enabling easier credit access to SMEs.
Conclusion
As a result, innovative technologies such as machine learning and AI are aiding lenders by offering liberalized credit access to SMEs across a variety of industries. Employing such an innovative approach breaks down credit access obstacles building a more dynamic and inclusive SME sector that supports the nation’s economic expansion.
Technology driven financing to SMEs plays a vital role in the economic development, integrating expansion, possibilities and financial inclusion. In the years to come, there are enormous opportunities for further innovation further providing readily available, effective, and robust lending ecosystems from SMEs in India.
FAQs
How does digitisation reduce SME lending risks?
Digitisation helps lenders improve the speed and accuracy of credit assessment for borrowers, thereby reducing the credit risk and speeding up the credit disbursal process for SMEs.
How does open banking help SMEs?
Open banking helps SMEs to share their critical financial data with lenders. This helps lenders in evaluating how SMEs are managing cash flows and other financial aspects letting them assess their viability even when there are no credit scores available to new businesses.
Can SMEs with no credit data history get loans with AI based systems?
Yes, AI will help lenders create a credit profile of the borrowers using alternate data like sales, invoices, banking transactions, debtors, creditors etc. This will enable SMEs to get easy access to loans even in the absence of any credit scores or history.
How can BankKeeping help SMEs in getting better credit for their businesses?
With its advanced software and dedicated team this SaaS based fintech can help you manage all your loans at one place. It can help in CMA data report preparation, credit renewals and interest charge monitoring; reducing your loan cost tremendously.
See how SMEs are saving lakhs in their business loans with BankKeeping.