Robotic Process Automation in Federal Loan Processing

RPA

RPA

How Beneficial can RPA be for Federal Loan Processing?

Robotic Process Automation (RPA) is snowballing and transforming every industry, including finance and banking. Businesses are realizing their potential and incorporating it into their daily operations to stay competitive, and so are the banking industry. This has some pretty significant implications when we ask the question, just how long does closing on a house take? with new RPA practices proliferating in the industry, it may be faster than you think. Banks are increasingly embracing RPA to become agile, competitive, and profitable, automate the mortgage processing.

ICICI Bank, one of India’s leading private sector banks, has adopted RPA in 2018 and using it on a large scale. It is the first bank in India that integrated robotics to automate manual and repetitive tasks such as IT support, customer email response, and portability of accounts. ICICI bank has deployed 750 robots to facilitate processing over 20 lakh transactions every day. Additionally, ATM cash disbursal grievances have come down to 4 hours from 12 hours, with 100% accuracy. Although the bank is widely using RPA to serve its customers, it hasn’t automated its loan processing entirely.

During the global pandemic, central banks worldwide, specifically the Federal Reserve and European Central Bank, adopted RPA to shore up financial markets and calm volatility. These banks’ support to strengthen the financial sector has made it easy to cope with the economic crisis. The speed and disbursement of loans have had a long-lasting impact on the U.S and global economies’ health by keeping credit flowing to the real economy.

However, in recent years, the turnaround time for borrowers’ (Businessmen, Farmers) loans takes a long time to get processed due to a large number of applications, legacy systems, and limited manual processing capacities. Application errors, time-consuming manual processes, and various stakeholders’ involvement in the approval process are the primary reasons for the delay.

In this case, where such loans contribute to economic stimulus, the solution could replace the manual processing of federal loans with RPA. It will improve turnaround speeds and provide a 10-and even 100 fold enhancements in processing time when implemented in other financial services industries.

Although the federal government offers loan programs to farmers, enterprises, homeowners, students, veterans, loan requirements, data points, and predefined approval processes are different. However, most loan workflows have many the same processes for underwriting, loan originating, screening, validation, etc. This makes the process easy to develop accelerators for automation with a build-once, use-often strategy.

Robotic Process Automation can help borrowers automate the end-to-end processing of these loans partially or entirely and make underwriting decisions in each step of the process. It includes loan origination, screening, validation, and loan management.

The federal loan processing starts from collecting inputs from paper documents, emails, fax, or other online portals, followed by a 360-degree screening to complete the applicant’s procedure, background review, and credit check. There are over 1,700 data points per loan to be extracted and compared.

RPA-infused software enables compiling an applicant’s record from various systems, channels, and service providers to be collected and then entered into the government’s systems for underwriters to scrutinize it.

Besides supporting the underwriting process, RPA can also help federal financial institutions automate the processes of loan origination, loan servicing, risk, and fraud review, email notifications, task assignments, collateral managing, document routing, and imaging.

With RPA, the government can respond instantly to questions through online portals and chatbots. It can realise the real RPA-driven benefits of reduced operational expenditure, stimulated operational efficiency, and the capacity to leverage existing data and infrastructure if all the processes are automated.