For the last 5 yrs NBFCs have been leading in the rapidly evolving digital lending space; leveraging and role of AI and analytics for NBFCs have been playing a very important role by automating the digital journey of a customer using AI tech Platform, which includes Digital Onboarding, Auto Login Auto Sanction and Post Disbursement the life cycle of the customer is derived using AI and Analytics.
In the dynamic landscape of financial services, Non-Banking Financial Companies (NBFCs) have strategically embraced technological advancements, including Artificial Intelligence (AI), Machine Learning (ML), and big data. In the dynamic landscape of financial services, NBFCs have strategically embraced technological advancements, including AI & ML, and big data.
The future of NBFCs in India is brimming with potential. Their role in the financial ecosystem, especially in providing credit to underserved sectors, cannot be overlooked. They have adapted to the digital age, introduced innovative products, and navigated regulatory change.
Advanced analytics and AI have powered NBFCs with robust collections of payments and monitoring decisions. NBFCs have relied on customer account balances and credit scores to prioritise non-performing and delinquent accounts and formulate strategies for collections.
AI has helped financial services organisations to control manual errors in data processing, analytics, document processing and onboarding, customer interactions, and other tasks through automation and algorithms that follow the same processes every single time.
Also Read | Fintech NBFCs bridging the gap through digital lending
AI-powered document processing software compiles specific information from the relevant documents at scale. It also checks the authenticity of submitted documents and routes applications through the respective departments for approval. The result is quicker loan approval times and improved customer experience. AI systems can automate the monitoring of transactions, detect potential compliance issues, and generate reports required by regulatory bodies. This streamlines compliance processes and reduces the risk of human error. The impact of AI in the finance industry cannot be overstated.
Few Challenges of Using AI and ML in Fintech:
- Insufficient data.
- Lack of data standardisation.
- Data supplement concerns.
- Model selection and evaluation.
- AI and ML model training.
We have explored some of the key areas of concern:
- Embedded Bias. AI algorithms can unintentionally perpetuate biases if trained on biased data or if developers inadvertently incorporate their biases.
- Explainability and Complexity.
- Cybersecurity.
- Data Privacy.
- Robustness.
- Impact on Financial Stability.
Views expressed by Dominic Vijay Kumar, Chief Technology Officer, ART Housing Finance (India) Ltd
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