According to a TransUnion global study titled “Empowering Credit Inclusion: A Deeper Perspective on Credit Underserved and Unserved Consumers,” more than 160 million consumers were underserved in India by the end of 2021. New era lending platforms are trying to fill this gap.
By offering micro-loans to underserved middle/low income segments, these platforms have simplified and increased lending in India. They are fully digital, have instant payout and lower ticket prices (as low as INR 1000).
Mumbai-based digital lending company CASHe uses an AI-powered social behavior-based credit scoring system called Social Loan Quotient [SLQ] to assess the borrower’s goodness quotient and repayment capacity.
The company caters to young professionals who are near-prime or subprime borrowers with or without a credit history. It leverages a combination of Big Data Analytics and proprietary algorithms to analyze non-traditional data derived from multiple online and offline data points, like smartphone metadata, social media footprint, education, compensation , career and financial history and calculate the creditworthiness of the borrower. The platform measures a borrower’s propensity to default based on their current behavioral information instead of traditional credit scoring systems that deliver a score based on historical financial behavior. Scores are generated in real time, letting customers know, in seconds, if they are eligible for a loan with CASHe. A higher SLQ score represents a lower propensity to default.
Recently, CASHe expanded into the wealth management space by acquiring Sqrrl, a Gurgaon-based WealthTech platform. Founded in 2017, Sqrrl is a mobile wealth management platform focused on Millennials and Gen Z. It offers unique offers to invest and grow their income without the hassle of tedious paperwork through its multiple wealth management products. savings and investment. Sqrrl uses powerful data analytics and automated processes to deliver the best possible investment experience at the lowest cost.
Bengaluru-based SmartCoin Financials leverages AI and ML algorithms to provide low-cost loans to ensure access to credit to underbanked and underserved sections. Furthermore, they use AI to digitize and streamline various operations such as delinquency prediction and fraud detection, which include both KYC – information extraction and face matching, revenue prediction, analysis and categorization SMS, collection dashboard, assisted customer support and cost optimizations.
SmartCoin uses alternative data from mobile phones and digital fingerprints for user onboarding and verification. For example, the platform uses facial recognition algorithms to validate the documents of the potential borrower.
“Our proprietary AI/ML models trained on billions of alternative data points covering transactional and behavioral attributes go beyond traditional sources to predict fraud and default risk by predicting the best loan terms tailored to the profile Our credit score has consistently outperformed standard bureau scores in assessing risk for various cohorts of users, especially those with little or no credit history. our text extraction and language and image processing engines play a vital role in creating a 360-degree profile of users that is not possible with traditional form-filling approaches,” said Rohit Garg , CEO and co-founder of SmartCoin.” Our app also takes the user through a gamified credit ladder journey with audiovisual cues and a vernacular medium, allowing us to create an array of personalized products.”
The company has designed the entire loan lifecycle to be 100% automated, digitized and paperless, significantly reducing operating costs. This makes all sorts of loan customizations sustainable and the model highly scalable across segments and geographies.
“Full-service technologies were designed in-house to ensure a fast and seamless experience in using credit and to support the scaling of our financial services with minimal operations. Having received the license from RBI (India’s central bank) to expand our financial services portfolio, we are well positioned to become the first ‘neo-bank’ for emerging India,” Rohit added.
“Traditional loans are subject to higher biases due to human decision making. I still remember a conference I attended in the United States where I was told that people who joined the bank after a vacation had a higher lag in terms of who they approved of compared to other people. That’s because they were generally in a good mood. If you think about it, that’s a direct bias I think a machine-driven decision-making approach can yield better results,” said Yashoraj, CASHe’s Chief Commercial and CTO.
Check out: Talking Ethical AI with Yashoraj Tyagi
“All teams are deeply focused on business objectives through the OKR framework. Our technical team is primarily focused on building efficiency/scalability and AUC optimization. The risk team is primarily focused on the explainability of the model, the adjustment of the thresholds for the follow-up of the delinquency portfolio which are used for the detection of the biases, while the analysis team focuses on improving the quality of the data. ethical principles related to AI and AI-based applications in our platform by ensuring 100% digitization, which means that no human decision-making is involved.As a result, biases can be eliminated and fairness can be ensured by examining the distribution of scores on different variables and extending continuous experimentation on various micro-segments,” Rohit said.
SmartCoin is committed to protecting consumer data. “We collect explicit consent from users with contextual details of how their data will be used. We ensure that every bit of data is encrypted in transit and at rest. In addition, we also find that all CISA and ISO-27001 guidelines are followed to confirm data privacy and security,” Rohit said.