Deep Dive: How This Startup Is Using ML To Provide Quick Credit
Emerging technologies are having a far-reaching impact on financial services by assisting them in growing customer expectations enhanced through convenience and accessibility. Adoption of technologies such as artificial intelligence and cloud computing have positively influenced almost all components of the supply chain across the bouquet of financial products: payments, lending, savings, and insurance. To understand how lending firms are using technologies for opening up the line of credit for their customers, Analytics India Magazine interviewed Jitin Bhasin, managing director for RupeeRedee and FincFriends, for our weekly column Deep Dive. RupeeRedee’s Journey Founded in September 2018, RupeeRedee is a digital platform to borrow money for short-term requirements at the click of a button. It is assisting loan seeker in getting instant credits for their unexpected financial expenses. The idea is to serve India’s massive population with hassle-free credits. “NBFCs in the background to facilitate short-term personal loans coupled with PhyGital, POS, LaaS and Brokerage services to various customer segments including salaried, self-employed, first-time borrowers,” says Bhasin. RupeeRedee has deployed various forms of underwriting including alternate data sources and is not restricted to credit score-based underwriting only,” he added. The firm is tapping into India’s vast open market, where the household debt to GDP ratio is as low as 11%, which is among the lowest in the emerging economies like Russia, China, and Brazil. In just one year, RupeeRedee is now facilitating tens of thousands of loan every month due to integration of the latest technologies. Their website and mobile application on an average get 1.5 million visitors from 25 cities. The Secret Sauce Of RupeeRedee Rise “RupeeRedee is entirely automated customer journey wherein customers can get instant loan disbursals. This is possible because of our deep technology integrations like optical character reader (OCR) based document verification, alternate credit scoring and underwriting, instant fraud checks, and digital offline KYC,” says Bhasin. For quick scale and delivery of services, the firm uses microservices architecture — a technique that structures an application as a collection of loosely coupled services. Besides, they also use technologies like PHP, Angular, .NET, MySQL, Kotlin, and Redis. While expediting the processes of application approval and delivery involves a lot of risks, the firm doesn’t ignore the risk of potential misuse. Consequently, they leverage machine learning techniques for fraud detection, predicting risk, and more. However, the use of technology is not limited to security. Machine learning is also actively used for innovating to stay competitive and obtain client satisfaction. For example, RupeeRedee has trained multiple models for regulatory and non-regulatory. While the former is for calculation probability of default (PD) and loss given default (LGD), the latter helps in fraud detection and pre-approving customers. To maximise the accuracy of their model, RupeeRedee utilises an exhaustive list of demographic info with the behavioural data. “We go a step further in ensuring that our model keeps delivering the best result in this volatile market. As there are rapid changes in the finance landscape, we pinpoint the emerging challenges and re-train the ML model for improving its dexterity,” explains Bhasin. Unique Value Proposition Unlike other lending firms that limit themselves to serve customers with strong credit history, RupeeRedee offers a suite of loan products to everyone, including salaried, self-employed and first time borrowers. Adding to this, Bhasin also revealed that the firm is devising a plan to offer a dynamic platform for matching clients with lenders. Apart from offering superior products and catering to diverse customers, RupeeRedee focuses on delivering a better customer experience through transparent product structure and intuitive process of availing credit. What’s Ahead The firm is committed to severing the largely ignored customers by big financial institutions. Thus, RupeeRedee is creating a ‘Product Ladder’ which will help customers move up the credit curve. “This will allow us to offer financial products at various price points based on the profiles and histories,” says Bhasin. Scaling is vital for businesses to achieve business growth, therefore, the firm is developing relationships with lending institutions and distribution partners (both digital and point of sale based) to expand the offering for mutual benefits further.
Emerging technologies are having a far-reaching impact on financial services by assisting them in growing customer expectations enhanced through convenience and accessibility. Adoption of technologies such as artificial intelligence and cloud computing have positively influenced almost all components of the supply chain across the bouquet of financial products: payments, lending, savings, and insurance. To understand […]
Quick credit is a saviour for people to fullfill thier needs, thus this firm uses machine learning to deliver instant credit for all.
["Deep Dive", "ML"]
["machine learning", "artificial intelligence", "AI", "cloud computing", "Redis", "ML", "RAG", "microservices", "analytics", "Deep Dive", "fraud detection"]
["AI", "artificial intelligence", "machine learning", "ML", "analytics", "RAG", "fraud detection", "cloud computing", "microservices", "Redis"]
Rohit is a technology journalist and technophile who likes to communicate the latest trends around cutting-edge technologies in a way that is straightforward to assimilate. In a nutshell, he is deciphering technology.
Email: rohit.yadav@analyticsindiamag.com