The growing world of MSME lending is also deriving value from the advancements being made in AI.
Authored by Tejamoy Ghosh
Back in 1950s, a man named Alan Turing wondered if machines could think. The question was posed in a paper – Computing Machinery and Intelligence, perhaps the most influential work in the field of Artificial Intelligence.
A few decades down the line, machines are now capable of understanding images, deciphering human speech and responding the same way, applying business logic for accelerating processes, and a lot more. It has come to a point where Turings of the present generation are now wondering what else the machines can think.
The growing world of MSME lending is also deriving value from the advancements being made in AI. They are using machine learning to make improved lending decisions in the absence of business documentation by consolidating data points from various social and demographic sources. This is allowing for a larger number of businesses, who traditionally have not been able to access funds from organised sources, to be brought into the inclusive folds of formal lending.
Let’s take a closer look at how these revolutionary technologies are helping these new age MSME lenders to bridge the gap between Grass root businesses and organised lending
Automating Decision Making & Lending Processes with AI
Decision making in lending is a tedious, costly affair. The cost of processing a loan application can easily go up to few thousands. This is one of the key reasons why majority of banks and traditional FIs focus on loan applications with a big ticket sizes, in order to optimize the costs and profit from bigger margins.
However, since loans required by the MSMEs can typically fit in a much smaller bracket, the segment isn’t as lucrative for the traditional institutions. Artificial Intelligence resolves this conflict by automating the processes. Since automation reduces the investment of time and human resources in processing smaller loan applications, AI makes it easier and cost-effective for lenders to make credit facilities available for the MSMEs.
Besides, by integrating AI-driven chatbots and the legacy systems, MSME lenders are further automating a host of workflow loops to be jumped in auto-pilot. Powered by AI’s natural language processing, chatbots can understand and process text and speech based queries.
With chatbots, MSME lenders are automating routine checks, address repetitive queries pertaining to processes, along with a host of checkpoints in the customer on-boarding journey. With AI automation bringing in operation excellence and cost optimization, digital lenders are able to best service the credit-starved MSME segment.
Expediting Credit Scoring with Machine Learning
While automation has come to the aid of MSME lenders, machine learning is helping these young and growing enterprises with predictive analytics. Simply put, machine learning can sieve through huge data chunks and uses its predictive algorithms to aid and expedite business decision making.
In order to cover the MSME segment, new-age financial companies must look beyond the traditional models of underwriting. Even though the sector lacks proper documentation, the recent developments like Aadhaar authentication, GST, Digital IndiaStack etc, provide a host of alternate data points to reckon for MSME lending. Furthermore, MSME lenders are considering industry clusters-based information, psychometrics etc to compute the payback ability and intent of the MSMEs.
Processing this huge boom in data from varied sources would otherwise warrant a huge effort, if one were to manually process the same. However, with the advent of machine learning algorithms, MSME lenders can simply automate credit scoring via alternate sources and have at their disposal, smart analytics that minimizes the effort and time in business decision making.
In addition, MSME lenders can further utilize machine learning to discover a number of borrowers left underserved due to traditional, obsolete processes. These borrowers can be targeted with focused digital and social media campaign, or offline outreach programs. Such a focused approach would reduce the cost of acquisition for FinTech lenders, helping them develop a focused and precise approach instead.
In a nutshell, innovation is going to separate leaders from the rest in the MSME lending sector. With Artificial Intelligence and machine learning, key industry players have found a ground-breaking way of doing things quicker, faster and more cost-effectively.
In times to come, innovating and adopting these technologies would no longer be a matter of choice and rather, will become a necessity in the ever-evolving business environment. Digital lenders should act fast and adopt these newer paradigms, in order to not only sustain their edge, but also make their services easily accessible to a staggering number of MSMEs requiring credit services.
Tejamoy Ghosh is Head - Data Science and Artificial Intelligence, Aye Finance
First Published: IST