Skip to content

Putting the tech in fintech: RPA – How automation is modernizing financial services

Hi there! Robotic process automation (RPA) is one of the most exciting technologies that is enabling fintech innovation and disrupting the financial industry. As someone who has worked in web scraping and proxies for 5+ years, I‘ve seen firsthand how RPA can optimize workflows and dramatically improve efficiency for fintechs and banks.

In this guide, we‘ll look at what exactly RPA is, its key benefits and limitations, and how leading financial institutions are leveraging RPA right now to better serve customers. I‘ll also share my insights on where RPA is heading next as fintech continues to evolve in our post-COVID, API-driven, AI-powered era.

Let‘s dive in!

What is robotic process automation?

Robotic process automation (RPA) utilizes software "bots" or AI agents to automate high-volume, repetitive tasks previously performed by humans. Think of RPA bots as virtual workers that can replicate the manual steps a person takes on a computer, such as copying data between systems, filling out forms, or even having text conversations.

According to Gartner, the RPA software market grew a whopping 65% in 2021 to $1.89 billion in revenue. By 2024, they predict RPA adoption will triple and reach nearly $4 billion.

For the financial sector in particular, RPA has become mission-critical. A survey by EY found that over 60% of bank executives said RPA is enabling them to reduce costs and boost productivity. Another 74% said RPA improves compliance processes.

As a fintech or bank, anything that can be consistently defined as inputs, rules, and outputs is a prime RPA use case. Here are some common examples:

  • Data entry or data transfers
  • Submitting and processing loan applications
  • Filling out customer onboarding paperwork
  • Managing invoices and accounting
  • Generating reports for compliance
  • Fielding customer service inquiries

RPA allows fintechs to achieve new levels of speed, accuracy, and scalability by removing human limitations. Let‘s examine the key benefits and potential drawbacks of RPA for financial services.

Advantages and limitations of RPA

5 main benefits of RPA

  1. Increased throughput: RPA bots work 24/7 without breaks. One bot can do the work of multiple employees. Leading RPA provider UiPath has shared case studies of banks handling up to 300,000 daily transactions with just 3 people supporting the bots!

  2. Improved data quality: Bots don‘t make typos or accidental mistakes that humans do. RPA ensures greater data integrity across core banking activities.

  3. Faster processes: RPA slashes processing times through automation. For example, invoice processing can be up to 70% faster. New client onboarding drops from days or weeks to hours.

  4. Enhanced compliance: By removing human error, RPA results in fewer compliance failures. Bots can also take over creating audit reports, monitoring risks, and other compliance procedures.

  5. Cost savings: According to Deloitte, RPA can cut costs by 25%-50% for banks. Bots don‘t require salaries or benefits. Increased efficiency also saves money.

Potential limitations to consider

  • Upfront investment: Developing RPA bots has high fixed costs. Transitioning legacy systems to automation also requires significant effort.

  • IT bandwidth: Your tech team must have expertise in RPA to develop, test, monitor, and maintain the bots. Lack of support can undermine ROI.

  • Displaced roles: Automating repetitive manual work does eliminate some human jobs. However, it also allows employees to focus on higher judgment-based responsibilities.

The consensus among financial leaders is that the long-term productivity and innovation gains far outweigh the risks. Now let‘s look at real-world examples of RPA in action.

How fintechs and banks use RPA

RPA is making major inroads across the financial sector:

  • HSBC automated over 150 business processes to reduce costs by $100 million annually
  • Santander‘s RPA program handles 85% of all incoming credit card applications
  • Deutsche Bank‘s bots process 5 million payment transactions daily
  • Citibank‘s "Citibot" answers 20% of all inbound customer service inquiries

Here are some of the most common and impactful use cases I‘m seeing for RPA in banking and fintech right now:

Streamlining client onboarding

Manually onboarding business banking clients – including KYC checks, documentation, credit decisions – can take days or weeks. RPA radically speeds this up by programmatically:

  • Gathering client data and paperwork
  • Checking watchlists and verifying identities
  • Fulfilling compliance requirements
  • Opening accounts, provisioning tools, and more

One major European bank cut client onboarding time from 20 days to just 1 day with RPA, while staff hours required dropped by 75%.

Detecting fraud faster

Banks lose over $100 billion annually to payment fraud. RPA augments fraud monitoring by:

  • Screening transactions against risk models
  • Cross-checking names against sanctions lists
  • Flagging suspicious activity for human review
  • Filing regulatory reports

Using RPA, one bank was able to cut false positives by 60% and detect 95% of fraud prior to payment.

Streamlining compliance

Staying compliant with regulations like AML (anti-money laundering) requires extensive data checks and reporting. RPA can automate:

  • Retrieving customer info from core banking systems
  • Checking against PEP (politically exposed persons) databases
  • Producing compliance reports for auditing
  • Monitoring transactions and accounts for risks

For one wealth management firm, RPA reduced compliance reporting costs by $700 per case, while avoiding regulatory penalties.

Handling loan/credit applications

Processing loans is paperwork heavy. RPA bots excel at:

  • Importing applicant data from online forms
  • Checking credit scores and eligibility
  • Fulfilling identity verification
  • Preparing underwriting documents
  • Booking approved loans into systems

At mortgage lender, RPA processes handle 88% of documents and cut loan closing time from 21 days to 8 days.

Managing accounts payable

RPA alleviates the invoice and payment headaches of accounts payable, including:

  • Extracting invoice data received by email/post
  • Matching with purchase orders
  • Updating accounting systems
  • Scheduling payments
  • Generating bank transfer files
  • Sending remittance advice to vendors

Overall RPA can slash invoice processing costs by 60-80% while achieving near 100% accuracy.

RPA beyond fintech: APIs, AI, and the future

RPA is already mission-critical for today‘s fintech needs. But it‘s just one technology driving the industry‘s digital transformation. Here are two other key trends to watch that will shape fintech‘s future:

Open banking APIs

Open banking regulations are requiring banks to open up their most important capabilities via modern API interfaces. This levels the playing field for fintechs to integrate with banking systems and data.

APIs also enable RPA bots to plug directly into core banking functions. With APIs, bots can complete end-to-end processes without human involvement.

As a fintech, combining RPA automation with open banking APIs gives you unlimited potential to innovate on top of bank infrastructure.

AI-powered "hyperautomation"

AI is supercharging RPA with skills like computer vision and cognitive intelligence. We‘re moving towards "hyperautomation" where bots can handle unstructured data and complex decisions.

Key examples in fintech include:

  • AI reading handwritten or complex documents with natural language processing
  • Chatbots handling customer service with natural conversations
  • Predictive algorithms for credit decisions or investment recommendations
  • Intelligent character recognition (ICR) for extracting meaning from forms

One leading hyperautomation platform is UiPath. Their AI tools let bots learn new workflows by watching humans. Then the bots continuously self-improve through machine learning.

RPA was just the first wave of automation in fintech. But with APIs and AI, the future of productivity and innovation through automation is unlimited.

Let‘s talk about automating your fintech workflows

I hope this guide gave you a helpful overview of RPA‘s benefits and use cases for fintechs and financial institutions. Automation is critical to stay efficient and competitive nowadays.

My team at Apify has years of experience building RPA bots and automation solutions for the world‘s leading banks and fintechs. If you‘re looking to streamline your processes with robotic automation, please reach out. I‘d be happy to discuss your needs and see how we can help you innovate!

You can also browse our Apify Store for pre-built tools to automate common scraping, crawling, and data integration workflows – no coding required.

Thanks for reading! Please drop me a note if you have any other questions.

Join the conversation

Your email address will not be published. Required fields are marked *