By Joydip Gupta, Head-APAC, Scienaptic AI

In an evolving financial landscape, digital transformation is no longer optional but necessary. As credit underwriting is the bedrock of lending decisions, its modernisation is crucial for financial institutions (FIs), especially in India, where the diverse market demands efficiency, digital collaboration and financial inclusion.

Digital underwriting is not just about faster decision-making through automation; the process ensures greater financial inclusion, offers high straight-through-processing (STP) rates and maintains risk control. Traditionally, credit underwriting has depended on documented financials and credit bureau scores. This approach fails to cover a large part of the market that is new-to-credit. It is estimated that more than 400 million adults in India are credit un-served and another 160 million are credit underserved. Traditional underwriting often automatically rejects or approves a limited number of applications, pushing many into the review bucket, restricting STP rates and increasing inefficiency. 

Digital transformation offers a new paradigm, utilising alternative data, artificial intelligence (AI) and advanced decisionmaking engines to rethink underwriting. By integrating real-time data and alternative credit indicators, FIs can better assess creditworthiness, offer personalised lending and expand financial inclusion.

One of the key innovations driving this transformation is the use of alternative data.

Traditional credit scores give an incomplete picture of a borrower’s financial behaviour. With digital tools, lenders can incorporate information such as account aggregator banking data, financial transactions, GST or tax returns, e-commerce activity and even social media behaviour, providing a more holistic view of a borrower’s financial standing.

This shift has proven effective. A TransUnion study found that once underserved consumers become creditserved, they are likely to apply for more credit, demonstrating how access drives greater financial engagement. By leveraging this broader data ecosystem, India can expand credit to underserved populations, including small business owners and gig workers who may not fit traditional models or have consistent income streams.

Adopting flexible, analytics-driven credit decision-making engines is perhaps the most important lever for digitising underwriting. Traditional underwriting relies on static lending strategies that struggle to adapt to changing market conditions. New decisionmaking engines allow risk teams to quickly identify fluctuations in customer behaviour and their impact on portfolio quality.

This dynamic approach is proving successful. Advanced decision-making engines deliver 30-45 per cent higher approval rates and a 25 per cent reduction in default rates, while increasing STP rates by 50-65 per cent, boosting efficiency and improving customer satisfaction.

AI plays a pivotal role in transforming credit underwriting. AI-powered models can analyse vast datasets in seconds, identifying patterns that humans might miss. FIs using AI have reported 25-60 per cent improvement in predicting whether an applicant will default, enabling more reliable risk assessments and reducing non-performing loans.

AI models continuously learn and improve their accuracy. This adaptability is critical in India’s dynamic market, where income streams can be inconsistent, especially in the informal sector.

Credit underwriting is at the forefront of innovation in financial services. By utilising alternative data and AI-powered analytics, FIs can speed up decisions, enhance financial inclusion and risk management.

For FIs, the message is clear: The future of credit underwriting is digital and those who embrace this shift will lead the next era of financial services. By investing in technology, FIs can secure long-term success and help India’s economy in a digital world.