How Can RPA Help Banks Automate Loan Management Processes?
How Can RPA Help Banks Automate Loan Management Processes?
Traditionally, bank processes like loan processing and approvals have been burdened with extensive documentation and paperwork. On average, banks take around 35 to 40 days to approve a loan.
But modern-day consumers can’t bear to wait for loan approval. Customer expectations have changed as the digital age has set in. Borrowers want fast and smooth access to various types of loan-related products. This is where automation technologies like Robotic Process Automation (RPA) can make a difference.
By deploying RPA bots, lending banks can accelerate the loan approval process and make it more reliable. A McKinsey study found that a bank that optimized its credit assessment using automation improved its productivity by 80%.
Here are some of the other benefits of RPA in loan management:
Multifold increase in the speed of customer onboarding and account opening.
Time efficiency for generating external loan-related reports.
Increased speed in processing customer complaints.
Reduced time in loan application and processing.
Reduced headcount in loan management personnel.
Next, discuss how an RPA-powered loan management process can deliver business value and benefits.
How RPA Can Improve the Loan Management Process
Effectively, RPA technology can impact multiple loan management aspects, including application, approval, documentation, and processing. Here are 5 areas in loan management where RPA is making a difference:
Using RPA technology, intelligent automation can quickly obtain customer data and streamline the initial loan application process. This includes automating the entry of customer data – along with validation and verification of the customer information, including their:
Annual income and expenses
Around 56% of bankers claim that manual customer data collection is the most challenging part of the loan management process. With RPA-enabled processes, banks can complete the loan application process through online mediums. Besides, borrowers can submit their digital documents on the bank’s online loan portal.
After the initial loan application is complete, bank loan managers have to evaluate it and check if they have received all the necessary loan documents and customer information. They also need to check if they have received the latest documents and up-to-date customer data — for instance, recent bank statements and the latest address details.
Manual loan approvals can consume a lot of time and effort. On the other hand, RPA can expedite the loan approval process by checking:
If the customer has filled all the necessary fields in the loan application.
If the submitted documents meet predetermined approval criteria.
The credit score & other credit-related information of the loan applicant from third-party websites.
Risk assessment is an integral part of the loan management process. However, only around 30% of banks deploy automation technologies in risk assessment.
An efficient loan underwriting process can evaluate the risk quotient of any applicant and the type of loan they qualify for. By combining RPA with machine learning models, banks can accurately determine the applicant’s risk profile by:
Measuring the possibility of a loan default based on the applicant’s line of work, income, and tax bracket.
Comparing the applicant’s profit-to-revenue index with similar applicants and the prevailing industry standards.
Besides, RPA can speed up the loan documentation process with data-driven insights from various financial documents, including account statements, tax returns, and income statements.
Once the loan is approved, RPA-enabled tools can also help in loan disbursement and monitoring. This includes sending the loan approval email to the borrower and other details like the interest rate, repayment schedule, and loan amount.
Additionally, RPA can enable banks to automatically send reminder emails & messages about the due date of the next installment. Besides loan servicing, banks can also automate loan monitoring to ensure the borrower pays back the installments on time.
To save time and improve productivity, RPA can also automate other aspects of loan servicing, including:
Flagging any unpaid loan installment
Customer Experience (CX)
Be it for loans or other banking services, RPA can positively impact the overall customer experience and brand reputation. For instance, using RPA in loan management can cut short a long and cumbersome application process for loan borrowers. Banks can also deliver a personalized CX for loyal customers based on the customer profile.
It also helps automate most of bank employees’ manual and repetitive tasks. This frees up valuable resources to improve the overall loan management process for customers. Further, RPA implementation can cut operational costs by 40-75% – thus saving unnecessary expenses for banks.
Next, let’s discuss how Ellicium can help with Robotic Process Automation (RPA).
How Ellicium Can Help with RPA
Over the last few years, Ellicium has successfully designed and implemented RPA solutions for customers across industries. We use RPA to improve business efficiency by:
Automating multiple manual tasks that require human intervention.
Eliminating human errors from critical tasks and processes
Utilizing skilled human resources for high-value tasks
Our customized RPA solutions can automate many business processes like loan approvals, legal documentation, and customer contracts. Our team is skilled in RPA technologies like UiPath, Automation Edge, and Blue Prism.
Here is a successful RPA case study where a leading financial auditing company reduced the time spent monitoring CCAR regulations.
Beyond loan management, RPA technologies can deliver business value in the banking sector in customer onboarding, insurance, and KYC compliance. By partnering with the right RPA implementation company, banks can successfully implement RPA for business success in a competitive market.
At Ellicium Solutions, we have the right expertise to facilitate your business transformation. Contact us today.