Artificial intelligence and machine learning are transforming credit decisions across India, according to an Experian study conducted by Forrester Consulting. The findings, based on input from 109 senior Indian credit risk decision makers, show that ML is helping financial institutions expand credit access, improve portfolio performance, and accelerate digital decision-making. The study also highlights challenges that continue to impede widespread adoption across the country.
As lending dynamics continue to evolve, ML is helping lenders make faster and more accurate credit decisions while proactively managing risk and extending responsible lending to broader customer segments.
ML as a driver of financial inclusion and sustainable growth
The report shows that ML is enabling lenders to expand access to financial services to underserved populations, such as thin-file consumers and consumers new to credit. ML models help make more accurate and comprehensive assessments by leveraging richer data and advanced analytical techniques.
According to a survey, 79% of ML adopters in India agree that the technology allows them to responsibly serve new customer segments that were often excluded by traditional scorecards. At the same time, 71% of respondents reported that ML improves profitability by enhancing risk prediction and reducing bad debts. This dual effect of expanding access while enhancing portfolio quality positions ML as a strategic asset for lenders seeking sustainable, long-term growth in a competitive and evolving market.
Automation, efficiency, and cost savings are the biggest benefits of ML
Nearly 68% of ML users cite improved risk prediction accuracy and operational efficiency as key benefits. These capabilities give lenders the confidence to automate, with 71% agreeing that ML allows them to automate more credit decisions, reduce manual workload, and improve time-to-decision.
Looking ahead, 78% of respondents believe that most credit decisions will be fully automated in five years.
Generative AI is emerging as a powerful productivity tool in credit risk
Generative AI is emerging as a powerful productivity tool, especially in traditionally time-consuming areas such as model documentation, reporting, and business intelligence. Approximately 84% of respondents believe that Gen AI can significantly reduce the time and effort required to develop and deploy new credit risk decision models.
More than two-thirds (70%) agree that the biggest benefits of Gen AI are streamlining regulatory documentation, enabling faster validation cycles, and improving collaboration between risk, analytics, and compliance teams.
Organizational resistance to ML adoption continues
Despite the benefits, many organizations remain cautious. The report found that cost, market uncertainty, and lack of in-house expertise remain major barriers to ML adoption. Two-thirds (65%) of non-adopters believe the costs of implementation outweigh the perceived benefits, while 44% admit they don't fully understand the value ML can bring.
Concerns around explainability and compliance also persist, with 54% of non-adopters concerned about model transparency and 55% concerned about regulatory inconsistency. These challenges are further exacerbated by legacy IT and data infrastructure, with 39% saying they are ill-equipped to support ML adoption.
Commenting on this insight, Manish Jain, Country Managing Director, Experian India, said, “India's lending ecosystem is undergoing a fundamental transformation, and machine learning is at the heart of that transformation. ML not only improves approval rates and reduces non-performing loans, but also contributes to creating a more transparent, efficient and inclusive credit journey. Institutions that invest early in ML and AI generation will be in a position to compete, comply and innovate.”
