We are all aware about the impact Robotic Process Automation (RPA) is creating across different sectors like healthcare, banking, finance, manufacturing, etc. In this article, I’ll be discussing how the Banking and Finance industry is able to optimize costs, boost productivity, and provide enhanced services to its customers through automation.
Let’s take a look at some of the potential use cases of RPA in Banking,
1. Loan Processing
Loan processing is one of the most important and tedious processes across the banking sector. Using RPA, banks can cut the processing time from hours to minutes, as it allows extraction of only relevant information from the documents submitted by the customer. Automation can help banks handle end-to-end processing of loans and make critical decisions in every step of the process including loan origination, screening, validation, management, etc.
2. Account Closure Process
Banks usually struggle with a lot of account closure requests which are too heavy to manage. The main reason behind getting overburdened is the clients’ non-compliance, leading to delayed submission of mandatory documents. Robotic Process Automation can help banks tackle this issue by seamlessly tracking all the accounts and sending them continuous automated notifications and additional reminders for timely submissions.
3. Know Your Customer (KYC)
KYC is mandatory for verifying the client’s identity when opening an account and periodically over time. It is not only a critical compliance process for banks, but it is also the most complicated one. A survey says that few banks spend a minimum of US $400 million annually on their KYC compliance. To minimize the costs and time spent on verifying their customers, banks have now started leveraging RPA to collect customer information, screen that information, and perfectly validate it. This allows banks to complete the KYC process in a shorter duration with limited staff and minimal errors.
4. Fraud Detection
Although Robotic Process Automation has existed in the banking sector for quite some time now, its renaissance with the help of technologies like Machine Learning (ML), Artificial Intelligence (AI), and Natural Language Processing (NLP) makes it a powerful tool to identify any potential fraud in real-time.
5. Anti-Money Laundering (AML)
AML is an extremely data-intensive process that can be simplified using automation. Whether it is identifying any suspicious banking transaction or automating the manual processes, RPA implementation proved instrumental in saving both time and cost when compared to traditional banking solutions.
6. Customer Onboarding
Customer onboarding in banks usually involves manual verification of several documents that drains a lot of time. Robotic Process Automation makes this process easier by capturing the data from the documents through Optical Character Recognition (OCR) technique. The data obtained using RPA can be matched against the information provided by the customer in the form.
7. Credit Card Processing
Earlier, credit card applicants had long waiting periods to get their card in hand. This resulted in customer dissatisfaction, sometimes even forcing them to cancel their request. However, with the arrival of RPA, banks have speeded up the process of dispatching credit cards promptly.
RPA software takes not more than a few hours to gather all customer documents, make credit checks with detailed verifications, and then take a wise decision based on predefined parameters to check customer eligibility. In this way, Robotic Process Automation makes credit card processing seamless, making the lives of banking staff and customers easier.
8. General Ledger
It is mandatory for banks to keep their general ledger updated with crucial information like revenue, assets, liabilities, and expenses, which is necessary to prepare financial statements. Managing this vast amount of data from diverse systems is very difficult and may also lead to errors. In this case, RPA comes to the rescue, integrating data from diverse legacy systems and presenting them in the required format, thereby reducing the amount of data handling efforts and time.
9. Mortgage Processing
This is highly labor-intensive and tedious for both banks and the customers. Banks take at least a month to manage their mortgage process that includes numerous steps like employment verification, credit checks, and inspection before approving each loan request. Even a slight error from either the customer side or bank side could result in the delay of mortgage loan processing. However, automation has accelerated this process for banks through a well-defined set of rules which help accelerate mortgage processing by eliminating any potential bottlenecks.
How to kick-start your automation journey with RPA?
Some banks and financial institutions have already started implementing RPA to facilitate automation of various business processes using bots. RPA, if implemented properly, can reduce human intervention to a large extent, automating mundane, repetitive, and time-consuming tasks. However, implementing the right RPA is neither hard nor easy. You need a partner with proven expertise in RPA tools and technologies to guide you on how to get started with RPA and drive better business outcomes.
