RPA, RPA, RPA—this mantra is occupying every aspect of online financial operations these days. We’ve gotten so used to it as if it were Matthew McConaughey’s famous ‘All right, all right, all right.’ That’s because RPA in banking—robotic process automation—has become a magic wand for this extremely ruthless sector. The COVID-19 aftermath has forever changed the market rules for those willing to stay profitable.
The “Financial Services Technology 2020 and Beyond: Embracing disruption” report from PWC revealed that 81 percent of banking executives desperately try to keep up with the rapid pace of technological change. A constantly growing need for reimagining business processes in this industry puts CEOs under tremendous pressure. And that’s where RPA in finance can work its magic.
So, what makes it so complex? Well, business transformation requires special skills, domain insights, and a comprehensive approach. Unfortunately, only a few companies can satisfy all the requirements right at the beginning of their journey and most still act at their sole discretion. So, to help your business avoid common pitfalls and achieve resilience by leveraging RPA tools efficiently, we share our experience and best practices in this guide. Of course, there are pros and cons of automation in finance and banking, but this time we’ve focused on the benefits and areas where RPA works perfectly.
The basics of robotics and cognitive automation
Staying competitive in your niche is imperative at any time. However, the pandemic has particularly accelerated the adoption of automation, which has proven to be effective in eliminating repetitive tasks, optimizing the workforce, and reducing expenses. RPA in banking has helped institutions reach maximum growth and agility 24/7/365 without compromising the cost-efficiency of the operational department.
But how does RPA for financial routines work? Let us explain.
RPA for banking in simple words
Robotic process automation is a software technology (scripts) that mimics human actions using machine learning (ML) algorithms and various technologies like natural language processing (NLP), deep learning, and others. What is RPA in finance?—Well, acting basically as digital workers, these bots can take on rule-based, repetitive tasks. They scan and understand what’s happening on a screen, complete keystroke sequences, then process the collected data just like real people do.
Without going into much detail, RPA in banking enhances your human workforce by handling dozens of clerical tasks. Bots can interact with consumers, send emails, process and sort documents, schedule appointments, and much more. The biggest advantage is that one bot can handle multiple workflows at once.
Before financial organizations were introduced to bots, simple automation options, for instance, included macros for Microsoft Office. Furthermore, virtual robots, AI, and ML form the core of ATMs. Today RPA helps with cash demand forecasts, replenishment strategy creation, pattern and facial recognition, customer behavior analysis, ATM failure detection, and other tasks.
What part does cognitive play in RPA?
The cognitive automation meaning refers to pre-trained software tools that automate specific business processes and require less data for it. Cognitive functions take RPA to the next level by emulating human judgment and intelligence and adding analytical abilities to your digital workforce. These bots also operate based on ML, self-learning and correction, logical thinking, and more.
Hence, cognitive RPA analyzes the obtained data and decides on further actions without bias. Advanced robots even transform unstructured piles of information—letters, emails, pdfs, scanned documents, voice recordings—into structured data sets. They automate highly complex tasks by constantly learning from their environment and handle process exceptions with minimum or no human intervention.
Robotic process automation in finance enterprises: the top 6 areas of implementation
RPA in finance is projected to see significant growth of investments through 2024. As customers become more tech-savvy, robotic process automation in banking is an absolute must-have to stay ahead of the competition. Below, we’ll explore some use cases of robotics and cognitive automation in the banking, financial services, and insurance (BFSI) sector. There are dozens of options, so we cover the most promising ones.
1. Personalized customer service
Automation in banking empowers consultants to process more queries with turnaround time (TAT) reduced from hours to minutes. Leveraging OCR capabilities, bots accelerate customer verification and onboarding and eliminate manual errors. They analyze consumers’ data using ML algorithms, tailor services for each specific situation, and provide automated financial counseling, monitoring, tax processing, and investment advice.
Meanwhile, by integrating RPA into front office operations, banks cover more communication channels to reach consumers promptly and effectively. It results in fewer complaints and better loyalty rates thanks to superior customer experience (CX). Additionally, users can set up automatic bill payment and invoice processing.
2. KYC and AML compliance
The know your customer (KYC) and anti-money laundering (AML) are obligatory procedures that keep hundreds of workers busy performing all the necessary identity checking procedures daily. Thomson Reuters’ “Know Your Customer Survey” revealed that financial institutions all over the globe spend from $60 to $500 million on KYC compliance and customer due diligence annually.
These crucial processes depend heavily on manual and data-intensive tasks. Meanwhile, RPA in banking performs KYC and AML checks more accurately and much faster than people do. Bots process consumers’ information in seconds and detect money laundering transactions based on the provided ML algorithms. They can also predict criminal intent by learning from previously seen behavior patterns.
3. Governance and risk mitigation
Did you know that tier one banks spend over $1 billion a year on regulatory compliance and fines? And that’s, by the way, more than 10 percent of their overall operating costs. So, it’s somewhere around $270 billion annually for the entire sector. Meanwhile, the use of RPA in finance firms can prevent loss of profit due to compliance issues.
Bots scan, validate, and understand regulatory documents without human involvement. They can tell you whether the regulations are relevant to your company, what business areas will be affected, and who needs to review the collected information. So, mitigating risk through automation in banking means cooperating with digital workers to gain comprehensive audit trials and compliance checks 24/7.
4. General ledger management
This area is one of the most promising for robotic process automation in finance and accounting. Well-trained bots can prepare error-free financial statements, connect with multiple applications to retrieve both new and legacy data, and process it in seconds.
RPA software can automatically update all the reports on expenses, revenue, assets, and liabilities keeping the information in your general ledger accurate and verified. Finally, automation in finance reduces the need for human involvement in manual tasks like data entry, reconciliation, and reporting.
5. Fraud and cybercrime prevention
Cybersecurity Ventures predicts global cybercrime damage to reach $10.5 trillion annually by 2025. This means fraud detection is one of the major concerns for banks, as checking all the transactions is difficult if the process is manual. That’s why organizations look to AI-enabled robots to spot rogue transactions and trading market abuse.
RPA in banking protection analyzes behavior patterns using the ‘if-then’ method. It detects suspicious transactions in seconds and informs employees about fraud in real time. Such an approach saves companies hours or even days on manual tracking and enables them to stop crime by blocking payments and accounts immediately.
6. Investment management
Cognitive RPA will also boost investment banking automation in the future. These tools become a driving mechanism for fund management applications. Robo-advisors monitor dashboards, streamline hands-off investments, trading authorization and governance, and facilitate market analysis and predictions. RPA in finance systems develops comprehensive investment strategies for both passive and active funds based on consumers’ portfolios and spending habits. It ensures smarter risk mitigation and retirement plans and helps traders accelerate decision making and ROI.
Now, what about diving a bit deeper?
How the banking and finance sector can benefit from automation
Numbers speak louder than words, so we want to start with some representative stats that can help you make the right decision regarding RPA implementation.
At TEAM International we’ve worked on numerous RPA use cases in banking and our experience proves that it’s possible to automate over 50 percent of human performed jobs. But is it worth the trouble? Well, working with industry leaders globally, we can say for sure that business automation is an investment worth every penny. But let’s go into detail and see what specific advantages you can gain through the transformative power of automation:
Up to 70 percent cost savings
Cognitive bots enable us to do more with less human involvement, substantially reducing operating costs. RPA in banking boosts productivity and quality of previously manual operations, which is why enterprises aren’t afraid to invest in these types of tools. In the Deloitte Global RPA Survey, 61 percent of respondents said automation helped them meet and even exceed cost reduction expectations. Moreover, they reported overall payback time in less than a year as robots provided on average 20 percent of full-time employee (FTE) capacity.
Round the clock operational capacity
Bots work for you 24x7x365, either performing complex tasks from start to finish or contributing to a common cause. With that said, your business can process more customer queries with 99 percent accuracy and speed. RPA in finance workflows reduces TAT from days to minutes, increasing productivity by 90 percent. Finally, you can add as many bots as you need on-demand in a few clicks, as RPA offers limitless scalability and mitigates your business risks.
Inimitable customer support
Cognitive robots simplify data collection and processing and provide high-quality, human-like interactions with your customers at any time of day or night. And it’s always more appealing when online conversations are personalized and sound natural. RPA in finance platforms can do that for omnichannel communications, improving CX to a previously unreachable level. Your clients will be able to achieve goals without the help of actual company representatives. As a result, they take fewer actions but get more satisfaction, which improves customer retention.
Increased staff capacity
The digital workforce directly impacts people’s productivity and efficiency. Robots handle up to 80 percent of manual tasks, enabling your staff to perform better on higher-value projects and accomplish more critical goals. Your employees also deal with volumes of data in various areas daily, resulting in errors and eventual delays. Meanwhile, bots eliminate these risks almost completely and reduce information processing costs.
Another reason why the “go robotic” movement is becoming more popular is that RPA has proven to increase profitability. Bots transform chaotic, time-consuming operations into perfectly organized flows. Hence, your company can provide services to more clients and capture new market opportunities while getting more financial benefits in return. By 2022, RPA in banking institutions will automate approximately 90 percent of customer relations and save more than $8 billion annually.
If we’re to discuss actual RPA use cases in finance enterprises, the list is endless. A major Japanese bank that cut down 400,000 hours of FTE manual work through bots is an example of recent bank machine automation. Meanwhile, numerous other BFSI companies, from MasterCard and Bank of America to JPMorgan Chase and American Express, have also reaped the benefits of RPA in banking workflows.
Last but not least, how can you find the right tools for your business? You can select from a variety of ready-made desktop and device-specific solutions, end-user bots, and much more. Or you may decide to develop your own tailored virtual assistants from scratch. So, where to start?
When it comes to RPA in finance, the top three vendors of enterprise-ready solutions with enhanced finance controls and automation are UiPath, Automation Anywhere, and Blue Prism. Their solutions ensure regulatory compliance, effective risk prevention, rapid ROI, and more.
If you don’t know what kind of automation will work best, we recommend hiring a reputed RPA partner to save you from unnecessary expenses and wrong choices. But we hope now you’ll know the answer when you hear a question like ‘what is the cognitive part of Automation Anywhere, UiPath, or any other tool?’. After all, the ongoing revolution of RPA in banking is no longer a scene from a computer game or sci-fi movie. Robotic process automation in finance companies is a vital choice to remain competitive, agile, and ready for market challenges with medium upfront investments.
Can I integrate RPA into any software system?
Yes, bots are platform agnostic. You can add them to any existing application, dashboard, or server you have, whether on premise or in the cloud. RPA tools work even for complex but optimized legacy systems.
Is RPA a good choice for my organization?
Usually, there is no bad case for RPA in finance. Based on our experience of integrating bots for the BFSI sector, we’d like to encourage you to give it a try. For a more accurate answer, RPA experts should make a thorough analysis of your business processes.
What’s the primary reason to opt for automation?
The first and the most important reason would be to reduce operating costs. The Institute for Robotic Process Automation & AI states that RPA can cut up to 50 percent of expenses for one FTE employee’s work. Other goals include boosting productivity and efficiency, shortening TAT, mitigating risks, and enhancing regulatory compliance.
What technologies form the core of RPA platforms?
The modern RPA in banking approach is often coupled with cognitive AI capabilities such as ML, NLP, OCR, speech and image recognition. The most advanced solutions can even handle the entire business process automation cycle unattended by humans. But we recommend consulting with a trusted RPA partner before implementing such platforms.