From algorithmic trading to the ability to pay for items using solutions like Apple Pay, the world of finance has some pretty impressive technology in play. One of the unsung heroes of the finance world? RPA. Short for Robotic Process Automation, RPA involves software “robots” designed to automate certain repetitive, high volume tasks. In doing so, it can improve compliance, result in better customer experiences, and — incredibly importantly — free up human employees to focus on jobs like one-on-one “relationship banking” with customers.
What are some of the ways RPA can help out in the finance sector? Here are six top examples to consider.
Processing Cost
Cost processing is a time-consuming task for those who have to carry it out, even with some of the automation that is built into many current banking systems. RPA automated systems for processing can greatly speed up turnaround times, thereby making things considerably easier for lenders (and, as a result of the faster decision-making, better for customers, too.)
RPA processing systems are able to extract data from electronic forms or even paper documentation, helping to automatically check information relating to applications, bank statements, income validation, and more, and then route it through to the required channels. It can also play an important role in fraud checks, before (should everything appear legitimate) proceeding to assist with the closing stage. This involves reporting and cross-checking across various systems and applications to make certain that everything is present and correct.
Assisting with Account Opening
Banks rely on new customers signing up to open accounts, and RPA makes this time-consuming task far easier. This process involves validating customer information, prior to setting up the account in question. As a way of cutting down on the wait time involved, RPA can aid with verifying customer identity, confirming previous credit scores, and checking information like address details and any compliance issues. It can then open up a new account to fit the customer requirements, and share this with the customer.
Not only is this speedier than having a human employee carry out these tasks, but it can minimize possible errors such as transcription mistakes as well. Similar processes can be used for closing accounts, too.
Lending Money
Another example of a potentially long-winded task that humans frequently have to carry out, which can be automated using RPA, is helping decide on applications. This important job requires plenty of assessment of documentation on the part of would-be customers: whether this is credit checks, insurance statements, assessments of previous mortgages, employment verification, and more.
RPA bots can be used for checking that these have been submitted as required, and extracting the relevant information so that the decision can be made. As such, they can play an invaluable role in the approval process.
Improving Customer Service
Customer service is important for every business. RPA bots can help ensure that customer questions are responded to quickly, identifying queries and ensuring that these are either answered using automated responses or putting customers through to the right people to answer them.
Attended automation RPA tools can also assist human employees (for example, those speaking with customers over the phone in customer service roles) by helping provide them with the right contextual information to better respond to questions. Finally, RPA can help prompt customers for feedback in response to service, which can be used to enhance the quality of service that the company provides.
New Credit Card Activation
When a new credit or debit card is activated, it’s essential that a series of guidelines are followed to ensure proper security protocols are followed. Fail to do these (sometimes due to humans rushing and therefore making mistakes) and the results could be negative. Take too long doing it, and customers may feel they are receiving poor quality service. RPA tools can assist when it comes to this validation process by following compliance rules and forwarding any potential issues to the right department.
Protecting Against Money Laundering
Money laundering is a serious concern for financial firms. RPA can be used to assist with cracking down on this challenge. There are multiple ways that this can work. For example, when alerts about potential fraudulent behavior are generated, systems may require further checks be made regarding customer transactions. This means retrieving information that can then be used to help investigators start their checks. RPA can be a useful player in this scenario by gathering the information needed for audit compliance systems, thereby giving investigators all the information they need.
RPA can additionally be used for generating reports that can help protect against potentially criminal actions such as money laundering. Other tools — like machine learning processes — are increasingly being used for this application. RPA bots have a significant role to play, too.
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