By Akshay Mehtrotra, Co Founder and CEO, Fibe
The lending industry witnessed seismic shifts in recent years, with digital platforms transforming the traditional brick-and-mortar institutions. This transformation is being propelled by advancements in artificial intelligence (AI) and machine learning (ML), technologies that are reshaping the way loans are originated, approved, and managed.
Digital lending landscape
According to a recent report by IIFL FinTech, the Indian digital lending market is projected to soar to a staggering $515 billion by 2030, showcasing a compounded annual growth rate of 33.5%. Traditionally, lending was a time-consuming process with substantial documentation, manual underwriting, and limited credit availability. Digital lending platforms have expedited the process, allowing borrowers to request for loans online and receive quick decisions. These platforms have increased access to finance for previously neglected parts of the population.
AI and ML are the core of this revolution. These technologies are integrated into digital lending platforms at multiple touchpoints. AI-powered chatbots have the ability to guide borrowers through the application process, while ML algorithms can assess creditworthiness by analysing vast datasets.
The driving force
One of the most important applications of AI in lending is the improvement of credit scoring algorithms. Traditional credit scoring relies primarily on credit history, often excluding individuals with limited credit data. AI-powered credit scoring models are revolutionizing the lending industry in India. These models can incorporate alternative data sources, such as mobile phone usage patterns, utility bill payments, and social media activity, to create a more comprehensive and accurate assessment of creditworthiness. This approach can help to expand credit access to individuals who may have been previously overlooked.
AI can help lenders offer more affordable loans to customers. By optimizing pricing models and identifying cost-saving opportunities, lenders can reduce interest rates and fees. AI can also help borrowers find the most suitable loan products based on their financial profiles and needs, ensuring they only pay for what they require. This helps companies tailor the loans as per the needs of their customers.
Personalisation is another key benefit of AI in digital lending. By analyzing customer data, lenders can tailor loan products and offers to individual preferences and behaviors. This not only improves customer satisfaction but also increases the likelihood of loan repayment. Rigoros model governance and auditing are essential to ensure fairness and transparency. To address evolving risks, the RBI mandates regular recalibration of AI-driven algorithms, emphasizing the need for robust, tested, and periodically re-evaluated models.
Challenges and opportunities
The rise of digital lending has also brought new challenges, such as fraud and regulatory compliance. AI can play a crucial role in addressing these issues. Fraud detection systems powered by AI can identify suspicious activity in real-time, protecting both lenders and borrowers. By analyzing patterns in payment and data, identifying unusual locations and devices used for transactions, and even employing facial recognition for added security, AI can significantly reduce fraud risks.Furthermore, AI can help lenders stay compliant with ever-changing regulations by automating compliance checks and monitoring for potential violations.
However, the use of AI in lending is not without its challenges. Ensuring the fairness and transparency of AI algorithms is paramount to prevent discrimination. Additionally, regulatory compliance in the rapidly evolving AI landscape can be complex. Striking the right balance between innovation and compliance is essential for the successful adoption of AI in lending.
The potential impact of AI and ML on the future of digital lending is immense. As these technologies continue to advance, we can expect to see even more innovative lending products and services. For instance, AI-powered underwriting could enable lenders to offer loans secured by assets other than traditional collateral, such as intellectual property or human capital.
The lending industry is going through a positive disruption, driven by AI and ML. By embracing these technologies, lenders can improve efficiency, improve customer experience, and expand access to credit. However, responsible and ethical use of AI is crucial to ensure the long-term sustainability and integrity of the industry. As we move forward, it is essential to strike a balance between innovation and regulation to create a lending ecosystem that benefits both lenders and borrowers.