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Author's profile photo Olivia Diaz

How Robotic Process Automation Helps In Financial Industry?

Hello readers, I know everyone is interested in robots and artificial intelligence. Some like them because robots do their work for them whereas others fear them because they think one day AI will take control over the world. Are you feeling that whole terminator vibe now?

What if I say to you that judgment day will come soon? Because today robots might already be in control of your finances. Feeling worried now, are you? Well, fret not, they are not going to shop for a screwdriver to tighten the screw of their head without asking you, they just keep an eye on your finances so that your banks can provide better personalized financial services to you.

You know how artificial intelligence and machine learning technologies are now implemented widely across almost every business sector to revolutionize the way of working. Companies want to leverage the benefits that AI brings with them like increased revenues, enhanced user experience, reduced costs, and more. RPA is just one part of the world-class technology ecosystem that enables organizations to achieve these goals.

RPA can be used in many ways across the financial services industry and as a result, it can be used in multiple roles and functions within a company. However, there are some common use cases for RPA in banking and finance:

Top 5 use cases of Robotic Process Automation in the Finance Industry

RPA for report generation

Instead of doing it all manually, Robotic Process Automation can now help you generate all the reports automatically. For example, a stock market report can be generated based on the price of an equity share. A bank would use RPA to generate a credit card transaction report that would show all transactions made by a customer in one day.

This allows banks to create automated data-driven reports that contain real-time data from their internal systems as well as external sources such as credit bureaux or third parties such as data providers like Bloomberg or Factiva. Now, these reports can help banks make informed decisions about their critical financial operations.

RPA can also be used to generate reports on financial information such as assets under management (AUM), balance sheets, and other metrics specific to a bank or investment firm’s business needs. These reports are created automatically through RPA programs that analyze data from internal systems like accounting software or order management systems (OMS).

RPA for accounts payable

RPA for accounts payable is a relatively new use case for RPA. The automation of accounts payable processes, especially those that are repetitive and manual, can help banks and other financial institutions to reduce costs and improve the efficiency of their operations. This type of software can also help them to increase their customer satisfaction as it allows them to process payments quickly and accurately.

The use case for accounts payable involves automating the following functions:

  • Processing invoices from customers
  • Disbursing payments
  • Generating reports on transactions processed

The use of RPA in payment processing reduces errors, speeds up transactions, reduces the time to process payments, and improves customer satisfaction. RPA can also help banks improve their financial services offering by automating manual processes and increasing efficiency.

RPA for mortgage processing

The mortgage industry is a good example of where RPA can help banks and other financial institutions. And it is needless to say how many troubles banks have to face in this particular sector.

First and foremost, they need to deal with increasing regulatory pressures as well as rising funding costs. In addition, they have to take care of the legacy systems that are not fit for purpose anymore.

RPA can help banks address these issues by automating various processes and improving efficiency while reducing labor costs. Banks can use RPA to generate new revenue streams by offering their customers more flexible products or services. For example, instead of lending money directly to borrowers, banks could offer them loans based on their credit scores or other factors beyond the traditional underwriting process used today.

Now, this mortgage processing is considered to be a very labor-intensive and time-consuming process. But using RPA will allow you to reduce your workload so you can free up your mind to finally focus on more important tasks at hand. RPA can also help banks automate mortgage loan origination and underwriting functions, which can reduce the risk of errors and make it easier for customers to get a mortgage.

RPA in Know Your Customer (KYC)

The Know Your Customer (KYC) process is a leading-edge technology that allows financial institutions to track and monitor the activities of a customer. It can be used for identity verification and fraud prevention, as well as for compliance with anti-money laundering (AML) regulations.

Another technological advancement complementing RPA in the financial sector is the use of Python web crawlers. These crawlers can automatically navigate the web to gather financial data, news, or updates, which can then be processed by RPA tools. For instance, a Python web crawler can be programmed to fetch real-time information about users financial activities and RPA can use this data for automated reporting.

KYC processes are typically performed by humans, who need to be trained on how to conduct these tasks. RPA has the potential to automate this work and reduce costs significantly while improving service delivery. This could also reduce errors associated with manual data entry, resulting in fewer customer complaints and a more efficient KYC process for banks.

RPA in fraud detection

RPA is being used to automate fraud detection in banking and finance. In the past, one of the key challenges for fraud detection was the high volume of transactions that are happening daily. With RPA, banks can now detect fraud at scale by using analytics to identify anomalies in customer behavior.

For example, if a customer opens several accounts in the same bank account or purchases a large amount of money with a single credit card, it could be an indication that something is wrong with their identity. Here, RPA can help banks identify such anomalies and investigate them further. There are many cases where RPA has helped save a huge sum of money from fraud.

  • An IT firm called NICE helped Bank of America detect $6 billion in fraudulent transactions in 2017 by using RPA technology.
  • IBM’s Watson was able to spot suspicious patterns in financial data that enabled it to spot almost 1,000 suspicious transactions before they happened.
  • In the process of monitoring its fraud detection systems, Wells Fargo uncovered nearly $10 million in fraudulent charges including some that had been reported over five years.

Final words

There is no doubt in the fact that if your employees get overwhelmed with the work, they can not focus on work let alone add value. It’s time to stop doing everything manually and start working more smartly or in this case, employ smart technology at your service.

When you replace the outdated mundane operations with smart automated processes, it will enable you to save your resources as well as increase work productivity at the same time. Not to mention that it will empower your employees to work on some real strategic tasks that could boost your business growth.

RPAs are not only effective but also very accessible solutions that could change the way how financial operations are conducted traditionally. And with the rise of AI, more and more financial organizations are now utilizing artificial intelligence to increase the efficiency of financial operations and ultimately grow their business. So now I want to ask you, how can your financial organization use Robotic process automation for its benefit?

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