Robotic process automation can help agencies make underwriting decisions in each step of the process, from loan origination, screening, validation to loan management -- automating them partially or entirely.
In the days following the pandemic, central banks around the world, particularly the Federal Reserve and European Central Bank, moved with extraordinary speed to shore up financial markets and calm volatility. The banks’ willingness to support the financial sector softened the economic impact of the crisis, with the S&P 500 index recording its best quarter in over two decades. By keeping credit flowing to the real economy, the speed and disbursement of loans has had a far-reaching impact on the health of the U.S. and global economies.
In recent years, however, turnaround time for borrowers to get loans processed in a national emergency has been growing longer, given the larger numbers of applications, legacy systems and limited manual processing capacities. The primary reasons for the delay are usually application errors, manual time-consuming processes and the involvement of various stakeholders in the approval process.
Considering the impact these loans have on worldwide economic stimulus efforts, should the manual processes that takes weeks or months for loan disbursement continue? Replacing manual processing of federal loans with robotic processes will ensure radically improved speeds. We have seen robotics process automation (RPA) enhancements provide a 10- and sometimes even 100-fold improvement in processing time when implemented in other areas of the financial services industry.
While the federal government offers loan programs to farmers, businesses, homeowners, students and veterans, each loan has its own requirements, data points and predefined approval processes. However, a majority of the loan workflows have a number of the same processes for underwriting, loan origination, screening, validation, etc. This makes it easy to develop accelerators for automation with a build-once, use-often strategy.
RPA can help agencies handle the end-to-end processing of these loans and make underwriting decisions in each step of the process, from loan origination, screening, validation to loan management -- automating them partially or entirely.
Underwriting is the most pivotal step in lending. Unfortunately, approvers sometimes get it wrong because they end up relying on inaccurate information. The manual process of collecting information is tedious, complicated and prone to error.
The federal loan processing starts from extracting inputs from paper documents, emails, fax or other online portals, followed by a 360-degree screening for completeness, background review and credit check of the applicant. There are more than 1,700 data points per loan to be extracted and compared.
RPA-powered software enables the compilation of an applicant's record from multiple systems, channels and service providers to be collected and entered into the government’s systems for underwriters to analyze it.
Apart from just supporting the underwriting process, RPA can also help federal financial institutions in automating the processes of loan origination, loan servicing, risk and fraud review, document routing, task assignments, email notifications and collateral management and imaging.
Moreover, with RPA the government can provide instant responses to inquiries through online portals and chatbots. With all the processes automated, government can realize the true RPA-driven benefits of reduced operational expenditure, accelerated operational efficiency and the ability to leverage existing data and infrastructure.
Still some agencies may be relying on mistaken impressions for their reluctance to implement RPA.
Expense: Although the cost of deploying RPA is one of the biggest reasons why organizations hesitate to adopt it, a McKinsey study suggested that “RPA is a promising new development in business automation that offers a potential ROI of 30-200 percent — in the first year.”
Lack of skills and technical ability: While existing IT teams may hold back, thinking RPA requires significant technical skills and knowledge, with the right tools and training, the learning curve is negligibly small and less disruptive than assumed.
Legacy infrastructure: Although RPA is aimed at leveraging existing resources, the implementation may require a bare minimum infrastructure refresh.
Resistance to change: Some organizations believe that bots may replace a majority of their human workers, but in fact RPA actually supports the work of employees.
With its ability to reduce loan-processing time by up to 80%, RPA is poised to take the world of financial services by storm, as evidenced by its rapid growth. It minimizes and reduces human errors, automates mundane tasks, assists with regulatory compliance, enables significant cost savings, operates 24/7 support and lowers the risk of cyber fraud.
Implementing RPA within federal agency loan services is an ideal way to cut costs, reduce error and expedite processing and disbursement – better serving federal clients and the workforce too.