Embedding Ethical AI into credit lending business: Yashoraj Tyagi, Chief Business Officer &#038; CTO, CASHe
According to the TransUnion Cibil reports, nearly 22 million Indian consumers apply for credit every month. However, the majority of them have been denied credit due to poor credit history or the lack of it. To address the issue, Mumbai-based digital lending CASHe introduced a first-of-its-kind social behaviour-based credit-rating system, called Social Loan Quotient [SLQ]. “CASHe caters to young working professionals who are either near-prime or subprime borrowers with or without a prior credit history. Our goal is to make credit available to the underserved (new-to-credit, thin-file customers) and bring them to the formal credit system through technological advances ushered in the era of automated underwriting in which computerised systems built in-house analyse hundreds of data points from loan applications and arrive at near-instantaneous, logic-based decisions to approve or deny loans,” said Yashoraj Tyagi, Chief Business Officer & CTO, CASHe. In an exclusive interview with Analytics India Magazine, Yashoraj spoke about how CASHe embeds ethics into its AI-based credit lending system. Understanding SLQ SLQ is a robust, AI-based credit lending system that assesses the goodness quotient of the borrower and their ability to repay. It leverages a combination of Big Data Analytics and proprietary algorithms to analyse non-traditional data derived from multiple online and offline data points, like smartphone metadata, social media footprint, education, remuneration, career, and financial history and calculate the borrower’s creditworthiness accordingly. SLQ is dynamic and forward-looking by design. It measures a borrower’s propensity to default based on their current behavioural information instead of traditional credit scoring systems that deliver a score based on historical financial behaviour. The scores are generated in real-time, which enables customers to know, within a few seconds, if they qualify for a loan with CASHe. A higher SLQ score represents a lower propensity to default. “CASHe aims to transform the digital lending industry in India with its proprietary tech and credit writing system while offering credit to the unserved and underserved – those who otherwise do not have access to credit through traditional mediums. With 3,000 crore loans disbursed to date, 18 million app downloads, 4 lakh loyal customers and 75% repeat users, CASHe is today the country’s fastest-growing digital lending platform,” said Yashoraj. Data privacy Security is the bedrock of any good fintech company. As fintech companies deal with sensitive eKYC data of the customer, it is prudent to put the necessary safeguards in place to secure the data. “As part of a multi-pronged security approach, we at CASHe make sure customer data and their interactions are secured at the highest levels,” added Yashoraj. Here’s how CASHe ensures security at all levels: CASHe mobile apps, access (login authentication via social login, two-factor authentications), API authentication via tokens and role based authorisation on what users can see and what actions they can perform. All customer data is encrypted using Secure Socket Layer (SSL) technology to ensure personal details are safe while being stored on Amazon web services. There are security group and firewall checks to control who accesses what API, and there are multi-level authentication, authorisation and verifications in their integrations with all partners. CASHe has regular third-party scans and vulnerability checks of all internal and external-facing apps. “Security is not an afterthought, but part of our culture and design. In addition, security review is a constant improvement process, and regular audits (internal and external) are done to validate and enhance the security of the data and the application,” said Yashoraj.
SLQ is a robust, AI-based credit lending system that assesses the goodness quotient of the borrower and their ability to repay.
SLQ is a robust, AI-based credit lending system that assesses the goodness quotient of the borrower and their ability to repay.
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["AI", "analytics", "Aim", "RAG", "R", "Go", "Git", "API", "big data", "cloud_platforms:Amazon Web Services"]
Sri Krishna is a technology enthusiast with a professional background in journalism. He believes in writing on subjects that evoke a thought process towards a better world. 
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