How AI Can Help in Increasing the Efficiency of Lending Process

How AI Can Help in Increasing the Efficiency of Lending Process

January 10, 2019

Lending process is extremely long and complex. Usually responsible for managing the processfrom pre-qualification stage to funding the loan – it is also a very expensive endeavor for any organization.

The Indian banking industry is going through tough times. In the financial year ending March 2018, banks have written off over Rs 1, 44,000 crores of bad loans attributing to massive losses and non-performing assets. The banks typically write-off the loans when they fall under the category of “doubtful recovery”. According to data from ICRA, two of the top public sector banks, SBI and Punjab National Bank, have written off bad loans worth of close to Rs 1,50,000 crore in the past 10 years.

Ensuring that customers with good profiles are onboarded is a prime priority for banks and for that, they need to do all the due diligence. However, customers want the onboarding to be quick and easy – According a report by Deloitte, 38% of new banking customers could drop the account creation process if the onboarding process takes too long.

AI, by automating key processes and leveraging decision-logic can help in increasing the efficiency of the lending process and make it easier for consumers to apply for loans, and for banks to approve them quickly. AI could be the solution to the growing challenges battling the banking industry such as

  • Regulations: The ever-evolving regulatory landscape not only contributes to rising costs but also put financial institutions under stress and increases complexity forconsumers.
  • Manual processes: The existence of several manual processes including application filing, data entry, evaluating creditworthiness, and making the lending decision not only increases the time taken to process the loan, but also the associated costs and risks.
  • Decision-making: Departments have to take in every aspect of theconsumer into consideration in assessing individual credit scores and then make the right lendingdecision.
  • Multiple channels: Loan departments often have to manage receipt of applications through multiple channels such as in-person, through the website, email or fax – which makes it extremely difficult for them to collate and store applications in one place for quick perusal.
  • Reporting: Uploading scanned documents to an application and then generating reports based on status, dealer, user or underwriter is a complex undertaking.

The Role of AI

With opportunities for greater efficiency and cost-per-loan reductions continually increasing,lenders can benefit a lot from AI. Today, the utilization of AI, Machine learning and RPA –along with decision logic – is helping loan departments to advance from the sluggish,error-prone processes to a far more efficient environment – with a higher focus on data integrity and customer experience. Here’s how AI can help in increasing the efficiency of thelending process:

  • Standardizing data entry: AI-powered machine learning tools enable technology to remember standardized forms, learn from them, and anticipate the type of information that should be in each field of the form. This way, departments can spend more time making sure the consumer’s experience is as trouble-free as possible and less on comparing and validating data on standardized documents. Professionals can also leverage AI platform’s image processing, computer vision and Natural Language Processing for structured, un-structured, printed, handwritten documents. Also leverage prior understanding to find what it is looking for, extract the required data, and improve the accuracy levels – the more it scans, the more it learns, and the more accurate it becomes.
  • Identifying irregularities: AI also helps greatly in detecting irregularities in the lending process and alerting professionals for quick remediation. AI can usedecision-logic to determine the favorable outcome and run algorithms that can be trained by the user for fast computations and decision process.
  • AI can also be used to compare: if information on a loan application meets thecriteria, and alert underwriters on occasions when it doesn’t.
  • Determining creditworthiness: Since the value of most loans is based on how likely it is for a consumer to pay back, determining how likely an individual will default is critical. Unlike traditional methods where lenders only looked at a few metrics such as income and credit score – and where the decision was prone to underwriter bias, AI determines the creditworthiness of consumers through detailed analysis.
  • Driving focus on core activities: Most often, loan departments end up wasting a lot of their valuable time shuffling between front and back offices and administrative tasks and are left with absolutely no time or energy to enhance the customer experience. By automating much of the labor-intensive work that experienced, well-trained underwriters and processors have been responsible for in the past, AI enables them to focus their expertise on higher-value tasks such as managing processing exceptions – rather than wasting their time in data entry and document-level work.
  • Speeding regulatory compliance: Financial institutions are always struggling to process loans, record each loan application and compile data to submit to
    regulators. Failure to submit on time or submitting erroneous data can result in massive fines. Using AI, organizations can detect regulatory exceptions prior to funding a loan, and save a lot of time and money. Automated reviews can reduce compliance time to as little as a few minutes.

Drive Better Customer Experience

With the lending process encompassing a host of activities, right from prospecting and receiving applications, to processing, underwriting, and finally funding – the industry is battling several challenges. These range from inefficiencies sprouting from the numerous hand-offs between front and back offices, the unusually long time it takes for processing and verification, and the existence of numerous manual processes that increases the likelihood of risk, and associated costs. With AI, banks, and other financial institutions can standardize data entry, identify irregularities, determine creditworthiness, drive focus on core activities, and speed regulatory compliance. By reducing the loan processing time, AI can expedite the lending process, and take customer experience to an entirely new level.