The Impact of Process Automation in Mobile Lending on Credit Risk and Loan Portfolio Performance: A Study with Reference to Bajaj Finance Limited

This study examines the impact of process automation in mobile lending on credit risk and loan portfolio performance, using Bajaj Finance Limited, one of India's leading non-banking financial companies (NBFCs), as the reference institution.Drawing on secondary data from Bajaj Finance's annual reports, investor presentations, RBI reports, and CRISIL research for FY2020-FY2024, the study applies trend analysis, Pearson correlation, and simple linear regression to examine the relationship between automation KPIsloan turnaround time (TAT), digital application share, and auto-approval rateand credit risk and portfolio performance indicators such as Gross NPA, Net NPA, provision coverage ratio, and portfolio growth.The findings show that Bajaj Finance's loan book grew from Rs.1,47,203 crore in FY2020 to Rs.3,30,615 crore in FY2024 (about 125% growth), while Gross NPA fell from a COVID-period peak of 2.96% in FY2021 to 0.85% in FY2024, well below the NBFC sector average.Average loan turnaround time fell 89%, from 72 hours to 8 hours, digital application share rose from 38% to 83%, and the autoapproval rate rose from 31% to 76%.Statistical analysis confirms a very strong, significant positive relationship between auto-approval rate and loan book size (Pearson r = +0.9367,R² = 0.8773, p = 0.019), and a strong negative relationship between turnaround time and loan book size (r = -0.8630),while the relationship between digital application share and Gross NPA is a directionally consistent but statistically weaker moderate negative correlation (r = -0.6193,p = 0.265).The study concludes that process automation has been a primary structural enabler of both portfolio growth and credit quality improvement at Bajaj Finance, and offers suggestions for strengthening model risk governance, portfolio diversification, and financial inclusion as automation deepens further.