The financial sector is undergoing a technological revolution as AI and Machine Learning have become increasingly relevant. Modern disruptive technologies have transformed the traditionally time-consuming process of loan sanction that required a drawn-out procedure into a digitalized transaction requiring a couple of hours. Therefore, financial institutions are implementing artificial intelligence (AI) and machine learning (ML) to simplify operations, lower operational costs, and maintain a competitive edge. The following are some of the common uses of AI and ML in the digital lending industry:
Reduced operating costs:
Digital lending companies require little human intervention, thanks to the technologically advanced business models, which help in lowering manual operational costs. In addition to a person’s credit history, a digital footprint enables the firms to see how well they can pay back their loans. Documentation is uploaded as part of the online process rather than physical submission. This allows for virtual verification and evaluation, which streamlines the procedure.
Digital lenders can cut down on costs significantly by reducing the need for data entry corrections and errors, fines for non-compliance, and increasing onboarding time. The additional advantage of operating 24/7 with no break is automated KYC powered by AI identity verification, enabling customers to create a vetted digital identity that can be reviewed instantly. This allows financial institutions to increase the total number of clients they onboard each year. The automation of KYC also enhances the client experience by eliminating the frequent back-and-forth between customers and lenders.
Hasslefree lending process:
In the traditional lending market, loan processing is one of the most cumbersome processes. However, robotic process automation (RPA) powered by AI and ML can reduce months-long processes to just 10-15 minutes in the digital lending space. The automation process enables the firms to extract relevant information from the documents they receive from the customer to verify all the details. A data-driven approach backed by machine learning enables digital lenders to make more precise and accurate decisions. Automated confirmation letters and intermediary bots help safer loan decisions, requiring customers to fix all inaccurate entries. AI-powered automated notifications notify the borrower on their loan application or make further information requests. The digital lender also provides customized automated alerts that can be sent by email, SMS, and other text-based communication methods.
Customers benefit significantly from AI-powered chatbots because they are accessible 24/7 and provide a wide range of services without human involvement, including automated asset management and customized recommendations. The AI-powered chatbots can gather any information that customers require to plan for their loans, including their financial situation and requirements. Additionally, offering information about loans, interest rates, eligibility criteria, and more. Chatbots save time and money by enabling lenders to respond to customer inquiries faster, resulting in a more satisfying customer experience.
Detection of fraud and risk
The practice of loan stacking is prevalent in the digital lending sector, where consumers obtain multiple loans from various lenders. This risk can be mitigated if digital lending enterprises utilize AI and machine learning capabilities to analyze customer behavior and evaluate vast amounts of customer data and transactions to identify suspicious transactions. Machine learning algorithms help lenders rethink their loan terms and predict customers at risk of default. The digital lending companies have access to actionable intelligence to make decisions using ML technology.
Agility is essential for financial organizations undergoing digital transformation to adapt to a business landscape that is changing quickly. Delivering and eclipsing organizational expectations requires the application of a robust digital mindset supported by innovation. Modern technologies like AI and ML enable organizations to make intuitive decisions automatically and achieve scalability through advanced analytics based on real-time solutions, with massive data accessibility across functionalities.
The article has been written Praveen Paulose, MD & CEO, Celusion Technologies