AI-based Detection and Prediction of SMEs Finance by Lenders
SMEs are the backbone of every economy. Yet they struggle with the funding to run and grow their businesses. Also, insufficient funds are one of the key constraints due to which SMEs fail to do business.
Big Data Smart Credit’s Research shows almost 75% of SMEs face loan rejections from banks where 36% of rejected trade finance are feasible and the four key causes of rejection are:
- KYC concerns (29%)
- No appropriate financing (20%)
- Required more collateral/information (21%)
- Low profit of banks (15%)
To minimize the funding failure and bridge the gap between banks and SMEs, it is vital to building an intelligent SMEs financing ecosystem with the help of FinTech. Henceforth, AI and ML are few of the leading FinTech’s that provides the promising solution. Also, as per Forbes, it has been anticipated that across the world, the AI FinTech market would reach up to $22.6B by 2025 and 70% of financial services use machine learning to forecast flow, tune in with credit score and detect fraud.
The following part of the article will cover how AI can help lenders in detecting and predicting SMEs financial position.
Real-time financial and accounting data gives credit visibility: The real-time, accurate data are the driving elements for SMEs to get access to credit. Previously lenders used to determine the credit position of SMEs based on FICO score and revenue. However, with the help of an AI, lenders can broaden their scope of assessing the creditworthiness of a borrower.
Using AI, lenders can transform raw accounting and financial data into a meaningful information. Further results in optimizing the process of underwriters by making speedy, risk-free lending decisions at a reduced cost. Also, accessing and translating a wide range of accounting & financing raw data with the combination of AI, in-depth insight of the SMEs finance and their behaviour along with real-time evaluation of every transaction can be evaluatehttps://businessfinanceintelligence.weebly.com/blog/3-ways-financial-technology-fintech-is-reshaping-the-lending-service-industryd. This transmits the borrower’s eligibility to repay the borrowed amount (principal and interest) and is particularly useful for lenders to assess the potential risk for themselves and determine the credibility of SMEs.
Streamlining: AI enables the structured approach for lenders in multiple aspects. Integrating SMEs finance with the third-party application, involving AI attributes can ease out the operational process for lenders. Replacement of manpower work with AI/ML automation increases the speed of lending process with little or no error. Moreover, dealing with real-time data, open finance data will promote transparency of all types of borrower’s transactions. With the help of an integrated, finance ecosystem, SME’s income and expense behavior, or other trends can be analyzed. The trends determined through AI and financial & accounting data, can be used in building smart, communicative, and intelligent dashboards using business intelligence tools.
Anticipating cash flow: AI holds a significant role in identifying the borrower’s capital management, expense behavior using its historical and present, banking and financial data. Also, with the help of AI, the process of converting raw accounting data to meaningful information, uncertainty for lenders, regarding future risk & return can be diminished. The streamlined, integrated data and trend analysis using past and present will give foresight to the lender, of a borrower’s future cash flow, revenue, profit, payment behavior. This predictive analysis of future cash flow with the help of AI not only fasten the lending process but also act as a key element in risk management or giving early warning.
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The Perfect blend of financial tool & AI, have radically transformed the lenders and SME’s financial assessment approach. Further, giving a cutting-edge competition across all the banking and financial industries. SMEs can leverage the benefits of AI that would promote them to be proactive with investment and financing decisions and assess their credit before applying for a loan. While lenders can optimize the lending process and enhance the customer experience by providing personalized services.
