4 Reasons Why Digital Lending is the Future for Banks Conclusion

AI-driven business solutions are changing the future course of lending business both for enablers and end-users. The and borrowers are experiencing a paradigm shift from manual to commercial loan origination software at lightning speed. 

 

Let us scrutinize the reasons that are conducive to a shift in the way banks and lending institutions operated to date:-

Big data offers big results

Neural networks with their complex algorithms churn big data, and slice and dice it into easy-to-understand computations that can be interpreted for easy decision-making purposes. A Series of mathematics and statistics formulas are used in algorithms that are useful in the operational workflow. What used to take analysts weeks to compute using spreadsheets can be achieved with AI and machine learning within minutes. 

Data science exerts an unflappable disposition in this age of information. AI helps in making sense of complex data into applications that can extrapolate insights that drive strategic decisions. The accuracy of the curated observations helps in optimum utilization of resources with maximum benefit. 

Big data can be processed to make strategic decisions by lenders in different aspects like:

  • Risk Management and Fraud Control
  • Round-the-clock customer-centric service
  • Credit analytics and easy-to-understand data-centric points
  • Business penetrations opportunities
  • Tracking and monitoring of loans
  • Data integrity and regulatory compliance

Getting the basics right

The basics of any customer-dependent business will try to focus on their needs. In an age of smartphones where people can use neural networks to speak with robotic assistants, borrowers are not interested in walking into a branch and standing in line to apply for a loan. They want their loan-applications process experience to be smooth and seamless. 

Smooth onboarding of clients, transparent credit decisions that help a borrower understand how their application fares and scaling-down of costs through enhanced efficiency are the drivers of this change. For the growth of a business, these benefits are non-negotiable. 

In addition to the ever-changing needs of the tech-savvy borrower, the availability of solutions provided by technology companies serving the niche is on the rise. It is a given fact that sooner or later, a lender will pioneer the change to loan origination software. If lenders don't want to lose their market share of different types of loan products, they will have to join the bandwagon of digitized lending. 

Elevated role of banker

The difference between knowledge and its application is the wisdom that will be demonstrated by any banker who uses AI-powered analytics offered by digital lending solutions. Loan officers can manage their customers better when they have insights into the data at their fingertips. 

Data analytics gives them the relevant intelligence to structure the right product for their prospective borrower. A high-risk loan applicant will be offered a product with more covenants and a higher rate of interest for the loan. In this manner, the risk metrics of banks are not compromised. This decision is also transparent, thus allowing an applicant to work on their shortcomings for a future requirement. 

Current shortcomings overhauled

Optimization of costs alone will not drive up profitability. There are evident lacunas in the current lending system. Banks and lending institutions need to pay attention to solutions that can help them overcome those shortcomings. A digital lending platform helps lenders cross these barriers with ease while not compromising on the quality of the loan portfolio. 

Here are a few of the shortcomings of manual lending that are being overhauled by AI-powered digital lending solutions:-

  1. Time and efficiency

Manually entering all the details from borrowers' documents by banking staff is slow and often a process prone to human errors. Different stages of loan applications are serviced by different departments. In the manual process, there is no easy communication between different departments. Often the email-based communication takes time to be cleared through the piling files. 

Digital lending solutions use neural networks to capture data with the permission of the borrower from the relevant sources. This data is pre-filled by populating them in templates that will be captured by the system for all cycles of the loan. There is no need to email between different functions to know the data points for the workflow. 

  1. Customer experience 

There were times when borrowers did not complain about walking into a bank to apply for a loan. But today a borrower would like to employ his time doing things that matter to them. Queuing up in a line is treated as a redundant chore and customers prefer digital interfaces that allow them to upload their documents and finish their applications in an easy-to-use interface. They also expect a quicker turnaround time for approval of the loans. 

AI-powered solutions provide chatbot assistance to a loan applicant at every stage of the process. They can seamlessly scan and upload their documents. Requisite data sharing permissions are sought just like a traditional system requires to sign the waivers. The data is then captured from the source of information like tax returns and pay stubs. This data is processed further and displayed utilizing analytic tools. These analytics are again interpreted with a recommendation to approve or reject loan applications based on pre-qualifications and data at hand.

All this is achieved in a matter of a few business hours spanning max to a single business day. The result is communicated to the applicant and upon acceptance of terms and conditions, the loan is disbursed swiftly. The ease of business and the transparency with efficient timescales will bolster the customer's experience. Borrower-centric experience that is unmatched is sacrosanct for lending businesses in the future. 

 

Conclusion

Banks cannot fall back to cost optimization models to drive up growth. They have to tap under-serviced niche areas. The financial inclusion of small businesses and retail customers can be easily embedded through digital lending solutions that are efficient, transparent, and low-cost in comparison to traditional lending practices. Banks have always understood that change is constant and they need to keep up with the times. The current wave of AI-powered lending solutions should and will be adopted soon by the banks and lending institutions.

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