Fintech 2020-Fintech, a portmanteau of the words ‘finance’ and ‘technology’, refers to technology enabling banking and financial services. However, several new technologies such as AI, ML and Blockchain are not only enabling existing services via traditional business models, they’re also disrupting the industry by the introduction of new services, especially by born-digital ‘TechFin’ firms.
Adoption of fintech around the world has grown rapidly, from 16% in 2015 to 64% in 2019, reveals the Global FinTech Adoption Index 2019 by EY. The awareness of fintech, too, is now higher than ever. Along with startups, large corporates and established banks have forayed into this space, underlining the immense potential of fintech.
In India, fintech has gained strong traction in recent years, buoyed by the significant increase in smartphone usage. At an exciting time like this, let us take a closer look at the major tech-driven trends that will dominate the fintech industry in 2020.
AI-Assisted Credit Underwriting
Artificial intelligence (AI) is a truly transformative force in FinTech. While most companies are aware of this technology, very few have realised its ability to make smarter lending decisions. Of course, other AI-based applications such as chatbots have seen high adoption rate, but fintech firms are yet to recognise the merits that artificial intelligence can bring to the credit underwriting process. AI-driven credit underwriting combines data derived from both traditional and alternative sources.
The use of AI on alternative data sources such as statutory filings (GST, EPFO etc.) statuses, news sentiment, court cases and proceedings in other tribunals (NCLT, DRT etc.), external credit rating history (migrations and downgrades) provides valuable insight on the willingness-to-pay of the borrower and hence improve the robustness of the loan-underwriting process.
Organizations with an AI-assisted loan-underwriting system can have a 360-degree view of the applicant. In 2020, more companies will consider supplementing traditional credit underwriting methods with AI-powered models on alternative data, thereby facilitating faster, simpler and better decision-making.