Monotonous activities in Banking/Finance segment where RPA can be utilized

There has been a major push on how organizations and countries can thrive by focusing on building a ‘knowledge economy’ and this is where digital technologies are playing a vital role in making this dream a possibility. Each and every sector, be it manufacturing, banking, retail, etc. is going through a digital transformation, to reduce the overhead costs and engage their employees in jobs that can go beyond normal ‘mundane tasks’. Technologies like Machine Learning, Artificial Intelligence, Image & Speech recognition, etc. are being used across different business verticals to cater to changing customer’s demands, reduce manual intervention by automation of tasks; thereby improving the overall operational efficiency.

‘Banking’ is one industry which is undergoing a significant amount of transformation at a rapid pace due to cut-throat competition from other traditional banks and Fintech companies that offer financial services using technology. So how can traditional banks stay ‘relevant’ and meet the rising customer demands? Robotic Process Automation (RPA) is one mechanism through which banks can reduce costs and improve human efficiency by getting the RPA bots to execute mundane & repetitive tasks.

“According to the Harvard Business Review (HBR), human error costs almost $3 trillion per year in the US alone.”

Banks have to deal with a humongous amount of data every day and by using RPA, they can minimize errors. By embracing RPA, banks can engage their employees with tasks which are more challenging & interesting, helping them stay ahead of the knowledge curve. Let’s take a look at across ‘processes’ where RPA can be used in a traditional financial institution without compromising the compliance and security norms of the institution.

1. KYC Process & Customer on-boarding

Know Your Customer (KYC) is an important compliance process for on-boarding a customer and any delay in that process can result in an average customer experience. As per a report by Thomson Reuters [Reference], some financial institutions spend close to $500 million on KYC and customer due-diligence. By using AI, Image Recognition, Cognitive Computing with RPA, banks can speed up the on-boarding process by a huge margin, reduce the errors involved due to human intervention, screen & validate customer information.

2. Customer Service

In today’s highly connected world, one bad experience with the customer service can spread like wildfire and can result in creating significant damage to your brand. Imagine a scenario where you have called up the customer service department of a bank for reporting a serious issue with your account, but you have to wait for minutes to get your issue resolved? It is bound to make the customer frustrated and the possibility is that the customer might look for other banks that offer better service.

Banks deal with multiple queries that range from bank accounts, financial services, loans, mortgage, etc. and the customer service department can function to its maximum potential only if they are aware of their priorities. RPA can be instrumental in answering ‘customer queries’ that are linear in manner and do not require any human intervention. This not only speeds up the resolution process but also helps the customer service team to focus on high-priority issues

3. Back-Office Operations

In order to stay relevant & competitive, Banks are enhancing their customer-facing or front-end operations. However, there are too many processes that still require manual intervention and hence are prone to errors. There exists a huge scope for optimizing the back-office or back-end department, where RPA can be used for transformation of the back-end department responsible for accounting, compliance, etc.

Bank reconciliation and Report generation are some of the back-office tasks that can be automated by using GIBot’s Enterprise RPA platform. We have already deployed the GIBot solution in a couple of banks in India and the output of the back-office team has significantly improved after the deployment.

4. Fraud Detection 

Digital Banking is growing at a rapid pace and as per a report, close to 3 billion users would access financial services on either smartphone/tablet/wearable [Reference]. Along with the meteoric rise of digital banking, there has been a significant increase in the number of financial frauds. Banks have to be proactive and fast to alert the customer/concerned department in case they observe any suspicious activity in his/her account, that speed & scale can only be achieved by automation.

AI and RPA will check several databases in order to check suspicious activity in customer’s account and report the same to the ‘Fraud Detection/Prevention Department’. RPA bots analyze customer’s transaction patterns and many other data points in order to predict the spurious/suspicious activity. Signature matching feature in GIBot platform uses Artificial Intelligence (AI), Machine Learning (ML) and Image Processing for fraud-detection, as well as minimizing the error scenarios encountered in the signature verification process.

5. Loan Processing 

Customer looking out for any kind of loan, be it personal loan/vehicle loan/home loan has to submit tons of documents like loan Application form, Income proof, Property Documents, Credit Check report, etc. Any kind of manual error on the bank’s side can result in slowing the loan application which might give the customer an opportunity to apply for a loan with a competitor bank. RPA can be used to automate many tasks involved in loan processing, thereby reducing costs, speeding up the process and minimize the mistakes encountered in processing a loan application

At GIBots, we constantly strive on how our RPA solution can be used to accelerate the Loan Application process. Enterprise RPA platform from GIBots can be used for auto-filling of the loan application forms. Back-office staff need not enter any customer details ‘manually’; instead the Bot would be doing that tedious activity. Our product also does the following,

  • Workflow Automation of Document collection, Credit score & Background check validation, and approval
  • Notification about the result to the respective stakeholders.

By doing so, back-office resources can be better utilized for other business-critical activities and automated configuration of approval process results in faster loan processing. It is a win-win situation for the bank, the back-office staff, and its customers.

6. End-Of-Day Closing Process

End-Of-Day closing in a bank refers to the process where the banking staff has to record the collection of cash, checks, as well as credit card payments. Banks could perform the end-of-day processing either once at the end of the day or at regular intervals (in a day) based on their requirements. Most of these tasks are repetitive but have to be performed with precision, as any human error in the calculation has huge financial implications.

GIBot’s Enterprise RPA platform can be used for automation of the end-of-day jobs at scheduled intervals, sending out alerts to the concerned personnel and generating end-of-day reports by fetching information from multiple databases. Since there is no human intervention, there are minimal chances of an error being encountered in the process.

There are many other areas like credit card processing, mortgage loans, ledger updation, etc. where RPA can play a role in maximizing efficiency by minimizing costs.

GitBots team has gained a significant amount of expertise in the banking domain and our Enterprise Robotic Process Automation Platform has the most advanced AI-powered bots. These bots can be utilized by small scale and large scale banks in order to reduce the overhead costs, improve the efficiency of their staff and creating a ‘delightful or WoW’ experience for their customers!


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