Right now, the fintech industry is experiencing a major revolution. Customers have easy access to credit which makes it possible for transactions and payments to be made as simple as ever. This is possible thanks to advances in technology such as open banking and the rise of AI/Machine Learning. The credit-hungry youth of India are constantly increasing their per capita spending. Customers used to have to go to the bank branch to present the documents and wait at least 15 days before they could get credit or a loan. The bank used to take a long time to process documents, conduct credit risk assessments, and perform KYC through personal visits. Banks and lenders can now lend money in a matter of days, rather than days. This has made the entire lending process shorter and more accessible to the average person.
Digitalization, open API integration and Machine Learning integration have given Fintech a major overhaul. Lenders are able to process loan applications, conduct e-KYCs, credit appraisals, assess creditworthiness and process the loan amount within a matter of minutes. There are many options available to those looking for credit. Millions of people apply for loans every month, but only 10% to 15% are able complete the loan application process. Only 2 to 5 percent of those who are successful can get the loan.
Reasons for Loan Dropout
Both pre-processing as well as post-processing are the places where loan defaults occur. The pre-processing stages include filling out an application, receiving an offer, providing KYC documentation, providing account statements, tax returns, and providing income tax returns. Credit appraisal, credit decision, loan disbursement, and final payment are all part of the post-processing stage. There are many factors that can lead to loan cancellation at different stages.
AI-driven Intelligent Automation is gaining popularity
Digital lending companies have seen a drop in loan applications due to a decrease in loan amounts at all stages. This has made it more expensive for them. AI-driven intelligent automation systems, which are powered by AI, can help financial institutions automate this process and significantly reduce costs. They also assist customers to make informed decisions during the loan application process.
Lending companies find it difficult to do their homework. They need the expertise of credit policy makers, credit risk managers, legal resources, and a team to review documents submitted by customers. It is difficult to assess creditworthiness and risk in the digital age. This makes it impossible for most applicants to review documents.
This challenging situation was solved by AI and ML-based intelligent automated systems. They can process this humungous amount of documents, analyze payment patterns and classify anomalies, automate risk decisions, and assess creditworthiness. Credit risk managers can now use AI to better understand each customer’s risk behavior and persona, and determine the cause of credit risk.
AI helps lenders predict the likelihood of customer loan defaults. This can be used to filter out qualified applicants and optimize the funnel. It also allows them to target quality customers and improve the application process.
This AI model can predict which customers are most likely to be approved for loans after they have submitted loan applications. It also helps in creating a pattern of quality applications. This allows lenders to quickly identify high-quality customers and help them improve their conversion rates and decrease loan dropout. This helps to reduce customer acquisition costs.
The lender can also use AI-backed intelligent automation to predict which customers are most likely to abandon the digital loan application process at various critical points such as document upload, KYC, avail offer, and document upload. Combining AI and Automation creates a powerful customer service strategy that helps to avoid loan dropout. This knowledge allows the lender to optimize customer campaigns and call center efforts.
Banks can use digital technologies such as artificial intelligence to streamline their loan application management processes, increase efficiency and make it easier for employees to provide value-added services.