How is Machine Learning Enhancing Credit Access in India?
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Synopsis
Discover how machine learning is transforming credit access in India by increasing approvals and reducing bad debts. This insightful report reveals the growing impact of ML technology on financial inclusion and risk management. Learn why lenders are optimistic about the future of automated credit decisions in this rapidly evolving landscape.
Key Takeaways
- Machine learning enhances credit access in India.
- 93 percent of lenders report increased vehicle loan approvals.
- 90 percent have reduced bad debts using machine learning.
- 79 percent believe it has fostered financial inclusion.
- 71 percent say it improves profitability.
New Delhi, Dec 4 (NationPress) Machine learning (ML) is significantly enhancing access to credit across India and minimizing instances of bad debts. A recent report indicates that 93 percent of lenders utilizing this technology for vehicle loans are seeing increased approval rates.
According to the report by Experian, machine learning is aiding lenders in improving their portfolio performance while expediting digital decision-making processes. The findings reveal that 90 percent of users have experienced a reduction in bad debt related to credit cards thanks to this innovative tool.
Feedback collected from 109 senior credit decision-makers in India shows that 79 percent believe machine learning has broadened access to new customer demographics and has fostered financial inclusion.
Additionally, 71 percent of respondents stated that machine learning has boosted profitability by enhancing risk predictions and lessening bad debts. Moreover, nearly 68 percent highlighted improved accuracy in risk predictions and operational efficiency as significant advantages.
“Machine learning is not merely increasing acceptance rates and diminishing bad debts; it is contributing to creating more transparent, efficient, and inclusive credit experiences,” remarked Manish Jain, Country Managing Director of Experian in India.
“As India progresses in its digital credit landscape, organizations that prioritize investments in machine learning and Generative AI will be better positioned to compete, comply, and innovate,” he added.
Lenders are now able to automate processes with confidence; 71 percent indicate that machine learning has enabled them to automate more credit decisions, lessening manual workloads and accelerating decision-making.
An impressive 78 percent predict that most credit decisions will be entirely automated within the next five years.
Generative AI is emerging as a robust productivity tool in credit risk management, with 84 percent of respondents asserting it can significantly reduce the time needed to develop and implement new credit-risk solutions.
However, 65 percent of non-adopters stated that the costs of implementation outweigh the perceived benefits, while 44 percent expressed uncertainty about the value of machine learning. Additionally, 54 percent were concerned about model transparency, and 55 percent feared regulatory misalignment.
IANS
aar/na
Point of View
The report highlights a significant shift in India's credit landscape due to machine learning. The findings emphasize the importance of embracing technology for financial inclusion, showcasing how lenders can enhance efficiency and transparency in credit decisions. This evolution is crucial for the nation as it seeks to expand its digital economy.
NationPress
04/12/2025
Frequently Asked Questions
What percentage of lenders report higher approvals using machine learning?
According to the report, 93 percent of lenders using machine learning for vehicle loans have reported higher approval rates.
How has machine learning impacted bad debts?
90 percent of respondents noted a reduction in bad debt for credit cards through the application of machine learning.
What do experts say about the future of credit decisions?
An impressive 78 percent of lenders believe that most credit decisions will be fully automated within the next five years.
What challenges do non-adopters of machine learning face?
65 percent of non-adopters indicated that implementation costs outweigh perceived benefits, while others expressed concerns about model transparency and regulatory alignment.
What is Generative AI's role in credit risk?
Generative AI is increasingly recognized as a powerful tool in credit risk management, with 84 percent of respondents stating it can significantly reduce development time for new credit-risk solutions.
