Putting the tech in fintech: RPA

David Barton
David Barton

In our previous post on the technology behind fintech, we looked at web scraping. But while web scraping can be a useful tool, robotic process automation is at the heart of how fintech companies are using technology to modernize financial services.

What is robotic process automation?

Robotic process automation (RPA) is the use of software robots to mimic human interaction with digital systems. The bots are given instructions for a logical sequence of actions to perform, enabling them to carry out any task that a person can perform on a computer. RPA allows for the automation of mundane, repetitive jobs, removes the risk of human error, and massively increases both the volume and speed at which those tasks can be performed. Examples of the kinds of activities that are good for RPA are copy-pasting data, filling out forms, moving files from one location to another, processing sales or returns, invoicing, or compiling reports. If a task can be described by rules and has clearly defined inputs and outputs, it can be automated at scale.

Robotic process automation is a relatively new concept, but the entire RPA market is forecast to grow at a CAGR of 32.8% and reach USD 13.74 billion by 2028. With the digitalization of the economy a cornerstone of European and global policy, RPA has the potential to spread to every aspect of our lives, including financial services.

What are the advantages and disadvantages of RPA?

As with any technology, robotic process automation has its pros and cons. While we believe that the pros outweigh the cons with no contest, there are a couple of caveats.

Advantages of RPA

  • Reduced human error. People make mistakes, especially when they’re carrying out boring, repetitive tasks. This vigilance decrement, as it is known in psychology, describes how the mind wanders briefly and errors inevitably creep in. It comes as no surprise that us humans are usually identified as the no.1 culprit for financial errors. Automating back-office processes can help fintechs avoid these costly mistakes.
  • Efficiency boosts: It’s easy to see how robots designed to operate without stopping and at high speed can be more efficient than humans who need rest and coffee breaks. Removing the human bottleneck allows workflows to operate at the pace of machines, not people.
  • Increased productivity: Enhanced efficiency increases output, but freeing your employees from mundane tasks makes it possible for them to prove their value in other ways. If you’ve hired the right people, you’ll see productivity go up. And because the work won’t bore them, you’ll see lower employee turnover.
  • Higher customer satisfaction: People hate to wait more than ever these days and bots help them avoid a lot of waiting. Being able to use web-based systems to carry out transactions, make investments, or authorize payments means no more lines for tellers or listening to elevator music on a customer service line. And behind all of those processes are bots. One of the biggest strengths of fintech innovation is in customer service, and automation is a big part of that innovation.
  • Cost savings: All of the above come together to save money and boost revenue. Robots are faster, untiring, and don’t make mistakes if they’ve been correctly programmed. Any company that implements RPA will almost immediately notice improvements in its balance sheet.
  • Scalability: And finally, the big one, literally, is that RPA allows companies to scale their products and services. After a certain point, it no longer makes sense to grow your company by just adding staff to deal with manual tasks. That’s where RPA comes in.

Disadvantages of RPA

  • Upfront investment. There’s no getting around the fact that there is an initial cost to automating any workflow. For RPA, this can be significant, especially for older companies that need to completely change how they work and modernize legacy systems. This cost is something that every business has to weigh against the risk of being left behind by newcomers that can start from scratch. Some banks are going the greenfield route and launching their own modern ventures to avoid the cost of modernizing old systems.
  • Makes some jobs obsolete. This is an inevitable side-effect of digitalization and in fact all technological progress. Roles involving data entry, clicking a button to authorize or transfer funds, processing invoices, or any other easily automated task can often be made completely unnecessary. But like the armies of clerks or telephone operators that existed in the last century, people find other, often more meaningful, ways to earn money and spend their time.

Automation and robots in financial services

Chatbots are big in fintech and banks right now. Chatbots are artificial intelligence (AI) software programs that simulate the experience of chatting with a customer service representative and can interpret and solve most typical user queries. As AI improves, chatbots improve, and they enable financial institutions to grow their customer base without needing to commensurately grow their personnel costs.

But chatbots are not the only bots that are taking off in banks and fintech. Behind the scenes, robotic process automation also has a role to play in helping these companies serve their customers at the level of efficiency and speed expected in the digital age. Chatbots can even interact with these RPA bots, with a user request causing the chatbot to trigger other bots and carry out instructions. In fact, you could argue that a chatbot, even one powered by advanced AI, is the user-facing side of a whole host of other bots designed to automate financial services.

RPA in fintech and banking

Much of the current wave of innovation in the banking sector is customer-focused, and RPA offers huge potential when it comes to ways to make life easier for fintech and bank clients. But it also offers better ways to keep on the right side of legal requirements, process data, and deal with all kinds of formulaic tasks.

9 ways RPA is already being used in fintech and banking:

Customer onboarding

Onboarding a new commercial client involves a costly process that can take weeks. Account owner data needs to be collected and validated, credit lines and limits need to be set up, the legal due diligence has to be completed, and reporting set up for compliance and cross-selling.

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Onboarding a new client can be costly and slow. Source: Deloitte Analysis (PDF).

Deloitte Analysis issued a special report in 2018 that came down strongly on the side of using RPA in customer onboarding to save time and money, with estimates that banks could see overall savings of approx. 30-50% with automation.

Fraud detection

Banks and fintechs are required to carry out extensive Know Your Customer (KYC) and Anti-Money Laundering (AML) checks. While there is lingering distrust over automating some of the steps needed to avoid fraud and verify customers, there are obvious benefits to at least speeding up some of these processes. Automation can be used to move files, check databases, and compile reports, with the last mile of oversight still delegated to staff with the necessary expertise. RPA doesn’t have to mean that everything is automated. Automation can fit into, and optimize, any part of the workflow.

The latest Basel AML Index shows that there is huge potential worldwide for solutions to fight global money laundering.

Compliance

The need to prevent fraud and enforce AML regulations naturally means that fintechs are exposed to compliance risks. Digital-only companies are increasingly required to adhere to the same strict regulations as traditional financial institutions. The fines for failing to enforce these regulations are usually measured in the millions of dollars and recent scandals even involved employees being detained by the authorities. Financial regulators are playing for keeps, so robust compliance audits and audit trails are essential. While it may again always be necessary for experienced staff to ultimately monitor compliance, there are many aspects of the process that cry out for automation. The rise of regtech to complement fintech indicates that this need has been identified and that RPA in compliance will continue to grow. In fact, the latest Thomson Reuters Regulatory Intelligence Report on Fintech, Regtech and the Role of Compliance in 2021 stresses “increased reliance on technological solutions as a result of the pandemic”.

Monitoring compliance is at the top of the list of activities likely to be affected by regtech, according to the 2021 Thomson Reuters Regulatory Intelligence Report

Data entry

This is where the error-free nature of RPA really shines. Data entry is inherently prone to decreased vigilance on the part of human data entry operators. But in many cases, the data is being transcribed from predictable sources that follow a particular format. Once they have been correctly set up, bots can read PDFs, extract data from web pages, forms, or copy and paste information from any structured source.

Reporting

Once the right data is in the system, it can be used in reports to stakeholders. Again, RPA can compile these reports effortlessly and automatically. The same goes for any reports that need to be generated from predictable sources, whether they are intended for internal or external use.

Loan processing

Huge numbers of loan applications can be processed using RPA. From the mundane paperwork to the generation and reporting of financial spreading data, automation makes it faster and easier to approve straightforward loans, while leaving loan officers free to spend more time evaluating more difficult prospects.

Claim processing

Claims against banks and fintechs can arise from interruption of services that resulted in financial losses, human error, or any number of points of failure in complex systems designed to deal with a lot of money moving around rapidly. Insurtech has been busy in the field of automating and streamlining insurance claims for a number of years, but any company can benefit from shifting some of the work to RPA. Easy wins from automating filing and reporting can pay dividends over the years.

Invoicing

The processing of invoices is often one of the earliest areas in any company to be automated and it is still one of the easiest to use as a proof-of-concept. Invoices are designed to be predictable and so are good candidates for bots. Alongside processing, bots can monitor payment terms and dates and make sure that penalties don’t add up from missed deadlines. RPA can also be extended to payroll processing to boost employee morale and loyalty.

Accounting

Year-end and month-end closing usually involve a flurry of intense activity for accounting departments in fintechs just as in any company. Bookkeeping at this level is often guided by detailed checklists that make it another good candidate for automation. While the human element can guide the process, parts can be picked for RPA and the entire sequence streamlined and speeded up.

Beyond fintech: post-covid, open banking, APIs and AI

The COVID-19 pandemic has accelerated and strengthened the process of digitalization that was already in play in the banking world. Going digital could even be seen to have saved banking from suffering too badly from the pandemic, as technology such as mobile, always-on banking enabled even locked down customers to effortlessly interact with their banks. Digital banking is here to stay and it will now enter into a phase of optimization and consolidation, with new opportunities and challenges.

COVID-19 has accelerated the use of technology in fintech and regtech companies, according to the 2021 Thomson Reuters Regulatory Intelligence Report

An application programming interface (API) enables systems to talk to each other, to exchange instructions, messages, and data. With open banking entering the field, the ability of even small fintech companies to disrupt banking will grow. Giving third parties the opportunity to interact with bank systems opens up opportunities for surprising synergies that we can’t even imagine yet. But it also enables established banks to close the digital gap, by partnering with fintechs. More banking APIs means more potential for RPA.

With repercussions for chatbots, RPA, and every aspect of the industry, artificial intelligence (AI) is the hulking elephant in the room. In a recent study of 305 global banking executives, the Economist Intelligence Unit found that “77% believe that unlocking the value of AI will be the difference between winning and losing”.

Disruptor brands such as Wise (formerly Transferwise) and N26 have been transforming banking for some time now, based on the drive to make financial services easier for the customer. That kind of innovation is only the beginning. The future of banking is digital and the rise of fintech and mobile banking were just the initial steps on the path to that future. The spread of robotic process automation into every aspect of our banking and financial lives is likely to be the next milestone on that path and the source of a new wave of disruptor brands. At Apify, we’re already there waiting to help you get ahead of the pack and automate your workflows and processes.

You might find ready-made automation tools in Apify Store to immediately solve some of your RPA needs. Something generic such as our Google Sheets Import & Export tool can save a lot of time, while our Content Checker can be configured to monitor any website for changes.

But to automate your processes efficiently, you should request a custom solution. We partner with global companies of all sizes, so you can rely on us to complete and maintain your project, no matter the scale. Just email sales@apify.com and tell us what you need.



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