Artificial Intelligence Triggers a Paradigm Shift in the Digital Lending Industry
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Today, terms like Gen-Z and Millennials are the craze words for most businesses world over as they account for more than 60% of the demography. Unsurprisingly, everyone wants to understand what moves them emotionally, physically and financially. Moreover, their communication and consumption behavior is shifting trends and in many cases, causing trends to emerge.
One of these trends is that of the Digital lending marketplace where one can avail any kind of loans at the click of a button! Notwithstanding the higher cost of capital, the enticing factors of this digital lending marketplace are bespoke lending products, convenient & quick disbursement and completely paperless transactions.
In India, the consumer debt totaled nearly 50% of the Gross Domestic Product ( GDP) in 2016, much higher than other leading economies, and is expected to keep growing as higher disposable incomes fuel consumption further. Couple this with an increasing inclination towards digital lending platforms and it seems certain that this trend is about to stay.
Currently online lending constitutes about 15-20% of the total personal loan market, which is set to cross 50% in the coming years. This begs the question; how do these platforms ensure that they ride this trend that too with utmost financial prudence? The answer lies in technologies that will help these platforms in searching for even the smallest of improvements in returns on loans and increases in market share.
To identify the right technology, let us delve a little deeper into what constitutes digital lending at its core. Since these platforms facilitate paperless transactions, they rely on data gathering from sources like PAN, Aadhaar, Income statements, Credit Reports, etc. for verification, credit decisioning and faster disbursement. Since the value of the loan depends upon the user’s creditworthiness, more user data like value of collateral, future inflation trends and predictions of overall economic growth will only help lenders secure their loan book. Thus, with increasing volumes of users and transactions, digital lending is ending up being a big data problem which makes it suitable for machine learning. And this is where Artificial Intelligence (AI) emerges as the technology that not only offers solutions but also promises to take customer experience to the next level
Here’s a look at 5 ways in which AI will bring about a paradigm shift in the digital lending industry
#1: Replacing paper with data; humans with machines
The limitations faced by traditional banking in that it involves the borrower to approach the lenders branch physically with a set of predefined documents, that too during operation hours. This is exactly what AI enabled digital lending promises to dispose of with where papers will be replaced with data from customer and other sources and humans with machines having AI. In addition, the cost of operations absorbed by the lender and the risk of losing a potential customer due to the manual decision-making process will also be mitigated by AI. So, when a user accesses the digital lenders platform and uploads his/her information like PAN, Aadhaar, etc., AI will proceed to convert this into data points which can be used to assess the users request for credit extension
#2: Data digitization & Automation of decision-making processes
Most times traditional banking cannot facilitate easier and quicker lending to pre-existing borrowers due to limitations of banking officials being unable to recognize the borrower’s creditworthiness, unless there exists a personal relationship manager. With AI enabled technological solutions, the entire credit history & income history of an existing borrower can be interpreted online in seconds and a decision on further credit extension can be relayed to the borrower immediately. This speedy decision making is instrumental in garnering new Gen-Z users who are shunning traditional banking for digital lenders.
#3: Identifying trends to make unbiased and safer lending decisions
The value of loans and a lender’s business sustenance depends entirely upon the borrower’s ability to make timely and complete payments. Determining this ability to repay is one of the most complex tasks even when complete information is provided, and borrowers often provide incorrect information to take advantage of the credit extended. However, with AI enablement, digital lenders can even evaluate the vast digital footprint of the borrower or a section of borrowers, and this alternate data along with traditional data will offer the lender more insights into determining the risks and make more prudent lending decisions
#4: Making lending robust; from being reactive to a proactive approach
When lending to new customer sets, it is imperative to be a few steps ahead in determining their credit limits or their payment ability. AI backed companies are able to predict this even in emerging markets where the new borrowing class lacks traditional credit histories or even a bank account in many cases. This is possible by AI since it accesses traditional and digital history of the borrower and combined with other indicators, can proactively identify potential opportunities or defaults in the lending space
#5: Exploring untapped markets with new unconventional credit models
As is natural in an increasing market share scenario, digital lenders will have to offer credit to a new set of customers with entirely different repayment tenure or credit limit requirements. In order to understand what product is best suitable or to develop an entirely new credit instrument to cater to them, AI offers the ability to learn from all available user data with unparalleled speed and countless iterations to arrive at a sound credit model. This ability will usher the digital lending industry into markets hitherto untapped.