Loan processing is a mission-critical task that’s core to the business of many financial institutions. The primary objective of loan fulfillment operations is to process applications quickly and accurately while minimizing underwriting risk.
In the current low-interest-rate environment, it is more critical than ever to process loan applications as efficiently as possible since the operations team has limited capacity to handle the surge in loan application volume. According to McKinsey, decreasing the time to approve small and medium enterprise loans from 20 days to approximately 10 minutes increased average profit margins by 50 percent for a prominent European bank.
Robotic Process Automation (RPA) is ideal for streamlining the steps across the entire end-to-end lending process. Intelligent bots can retrieve data from a variety of different sources to validate information on loan forms, quickly identify any inconsistencies or missing information on applications, and automate almost every step, including deciding who to approve and for what amount.
Intelligent automation makes it possible for financial organizations to dramatically speed up the underwriting process while reducing costly mistakes caused by human error. It enables the origination function to be performed more efficiently and at a far greater scale to boost overall productivity and revenues.
Financial institutions must gather data from several different sources to validate the loan application information and assess each applicant’s risk. Corporate or commercial loans require even more data sources.
Previously, this step required underwriters to manually access several different databases to verify this information, which was too time-consuming. Today, bots can perform this legwork on behalf of the underwriters to ensure they have comprehensive and accurate information for each applicant.
Another manual task that can be eliminated by bots is the transferring of information from completed forms into the appropriate IT systems for risk analysis. Traditionally, this task has been prone to error when people inadvertently input incorrect information.
Bots can eliminate this risk by ensuring that information is accurately transferred into analytics systems. By using bots to fulfill these critical tasks early in the underwriting process, companies can complete more applications in a day while enabling human workers to concentrate on the more complex loans which require further analysis and judgment prior to approval.
Another critical consideration for issuing or denying loans is that much of the information involved in risk assessment comes from unstructured data sources. The information gained from social media profiles, letters of credit, news reports, scanned financial documents, and other sources can influence whether or not to approve loan applicants.
Intelligent automation is one of the best tools for analyzing unstructured data. When properly implemented, bots can extract relevant information from these sources, input them into the appropriate fields for analysis, and greatly reduce the time required to review this data for relevant information.
Automating the analysis and extraction of information from unstructured data is vital to accelerating loan processing — especially since the proliferation of data today is mostly unstructured data.
Perhaps the most valuable benefit of expediting loan processing with intelligent automation is increased customer satisfaction. By using bots to automate the most time-consuming steps in the underwriting process, organizations can quickly approve and close loans. Speedy loan approval is a great way to retain customers and attract new ones, which is particularly crucial in a market where they’re likely to go to another institution if the process takes too long.
Intelligent automation is critical for expediting the underwriting process and facilitating quick loan approval. This enables organizations to process more loans at a greater scale — which boosts revenues.
The speed and accuracy with which intelligent automation enables loan approval also increases customer satisfaction, which in turn leads to a more extensive customer base
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Ken Mertzel is senior director of industry marketing for banking and insurance. He translates financial data into strategic business information to improve business performance and organizational effectiveness.