How Is Robotic Process Automation Disrupting The Banking And Finance Industry

The innovative technology of Robotic Process Automation (RPA) is one of the most powerful tools for optimizing business processes today. The course of all exhausting, routine processes in any business area can be significantly improved thanks to it, and the costs of their maintenance are significantly reduced.

However, is the banking sector one of those where it is possible to use robotization technology? After all, Robotic Process Automation in banking sector and automation in general is perhaps one of the most vulnerable in terms of risks, given banking specifics. In addition, the rather restrained attitude of banking IT departments to all kinds of technological innovations that could interfere with the smooth operation of banking systems and already integrated corporate applications is well known.

Also, what about security issues? Indeed, in the banking sector, they are relevant, like in no other: it is information security, the security of saving personal data, the security of operations, etc. The slightest mistake can be very expensive here – both in monetary terms and in matters of reputation bank and clients’ confidence in it.

Due to such a high degree of financial and non-financial risks, doubts may even creep in whether it is advisable to “let robots into the bank” at all. But, despite the quite fair questions and warnings, the technology of robotization of business processes is not only suitable for implementation in the banking sector – it already has successfully established itself in this field and showed the first results that are encouraging for all skeptics.

Such world-famous banks as HSBC, Credit Suisse, Citi, Deutsche Bank, and international groups Raiffeisen Bank International and BNP Paribas are already leveraging RPA and intelligent automation.

Many other institutions around the world are already on the verge of implementing Robotic Process Automation in banking and see it as a powerful and truly revolutionary tool for positive changes in the banking business.

The banking and finance industry has experienced exponential growth over the past few years, thanks to the implementation of technological advances that lead to faster, safer, and more reliable services. To stay competitive in an increasingly crowded market – especially with the increasing adoption of virtual banking – banking firms had to find a way to provide their customers with the best possible user experience.

Almost 81% of banking executives are more concerned about the speed of technological change than any other sector in the industry, according to PwC. Within the company, the challenge has also grown to maximize efficiency and minimize costs while maintaining the highest level of security. To meet these needs, Robotic Process Automation (RPA) has become a powerful and effective tool.

RPA has been widely adopted in this sector to make labor-intensive banking transactions more organized and automated. According to reports, the largest share of revenue in 2019 came from the BFSI segment in terms of RPA application.

Robotic Process Automation in banking has also greatly simplified a wide range of back-office processes that once bored bank workers. By shifting much of these tedious manual tasks from person to machine, banks have been able to significantly reduce the need for human participation, which has had a direct impact on everything from productivity and efficiency to personnel issues and costs.

Recently, Japan’s largest banks announced the introduction of Robotic Process Automation to reduce labor costs and improve operational efficiency. Large banks such as Axis Bank and Deutsche bank also announced the implementation of RPA to automate business processes.

A bank employee deals with voluminous data from customers, and manual processes are prone to error. Banks around the world are considering using RPA to minimize manual processing of this huge data to avoid errors. Handling data manually is also a laborious task. Simple checking of client information from two systems can take seconds instead of minutes with bots. Implementing bots for these manual processes can reduce processing costs by 30% to 70%. Some processes in banks can be automated to free up staff to work on more important tasks.

Over the years, companies have tried to find ways to improve these departments through corporate systems, reporting tools, and interim measures to eliminate repetitive manual actions.

According to Jeremy Dean, the head of RPA at the accounting company Mazars in the USA, this phenomenon has a bright future:

“Unfortunately, these methods solved many other problems but did not help in any way to eliminate two main ones that exist in finance and accounting. The first is how to load data into the systems, and the second is how to carry out the “closing of the month.” Many people now realize that automation solves these two problems.”

To reduce errors and perform repetitive workloads, RPA also leverages the power of artificial intelligence. The advantage of RPA is that you do not need to automate the entire process, but only certain parts of a multi-step process.

Dennis Gannon, vice president of consulting at Gartner, says rule-based processes are best suited for automation. This is where RPA delivers fast results and acts like digital adhesive tape.

“RPA is good at handling bottlenecks that arise in time-consuming processes that require many hours of manual labor,” Gannon revealed.

He says RPA is likely to gain widespread acceptance as a means of automating the buy-to-pay process. By starting with these transactions, finance teams can capture early results and get feedback on what is working well, and then move on to other tasks that are also easy to automate.

When it comes to fears of being unemployed due to automation, it’s important to involve finance staff on RPA projects to reduce their fears and allow them to discover new perspectives.

To begin with, project managers will involve employees in automation processes for a couple of days a month so that they can practice introducing new robots into the production environment. For the remainder of the time, they will observe how the robot is working and identify any limitations and problems in using it. This will open up other areas for them to automate their work.

RPA consists of software robots, which are patterns of repetitive actions. The robot mimics normal human functions: reading text in an application, copying information, and transferring it to another application. IT departments use RPA platforms to create, monitor, manage, reuse, and save robots and the actions they perform.

The simplest robots capture the mechanical actions of a person and copy them. This is a kind of sample. Based on it, the developer will create a stronger robot that will not break if the application screen is slightly changed. Other artificial intelligence technologies often complement robots. For example, optical character recognition (OCR) is used to transfer text from a paper document, and machine learning is used to match fields in an invoice with fields in an application. This combination is sometimes referred to as intelligent process automation.

Robotic Process Automation in banking also complements a number of other technologies. Sometimes IT departments use low-code / no-code frameworks to create lightweight automation that is implemented as code, API management frameworks, or platform-as-a-service, which enables direct communication that is much faster than RPA. However, RPA has access to any application available to humans, and this is its advantage over other technologies.

Studying the market of implemented RPA solutions in the international IT segments, we can conclude that the use of RPA does not actually depend on the industry, and this technology works in any market segment.

However, this article is devoted primarily to Robotic Process Automation in banking and finance.

Here are the most important points. Look through all of them to see the main benefits of using Robotic Process Automation in finance.

How and what is automated in finance? According to a poll by The Economist Intelligence Unit, more than half of all financial transactions last year were carried out with robots’ participation. Analysts at McKinsey say that in the financial sector, automation can, on average, free up 43% of employee time. This figure may vary depending on the specific specialization. For example, a mortgage broker spends 90% of the time processing applications in manual mode, but if it uses more modern methods of determining the authenticity of documents or applications for a loan, then 60%. As a result, they can devote the saved time to communicating with clients – to consult more and delve deeper into their needs.

Companies trust robots to solve specific problems in large processes. They can:

• get access to applications;
• make decisions based on the if / then rule;
• navigate through applications;
• write and send emails;
• read structured data from documents;
• open files and attachments;
• copy and paste information.

As practice shows, a wide variety of banking functions and processes are successfully amenable to robotization:

• lending,
• servicing accounts and payments,
• audit reporting,
• mortgage payments,
• reconciliation of account balances,
• etc.

Here are examples of the most common tasks that robots take on in the financial sector.

1. Collection and processing of data. Finance and insurance workers in the United States spend half of their time on these processes. According to McKinsey, RPA solutions are capable of handling 60% of these tasks. Robots successfully process completed customer forms according to the specified parameters, extract and check data from invoices, confirm payments, send error notifications, monitor duplicate payments, etc. The robot copes with data entry faster than a human. This saves companies the time and money needed to rework the task. The program works around the clock without a break for lunch and sleep, does not get tired and does not make mistakes, and provides reports simultaneously. Thus, customers of banks and insurance companies are less likely to face situations such as delays in payments.
2. Confirmation of data accuracy. Employees of many financial institutions spend a lot of time on tasks such as determining a credit score. Robots with access to databases are able to verify the authenticity of the information provided by clients by order of magnitude faster. They easily track money transactions and identify suspicious activity. In the long term, this means that a person with a clean credit history will get access to necessary services faster.
3. Prepare material for analysts. Organizing data for analysts takes a huge amount of time, and this task can also be safely given to a robot. The specialist will work with a ready-made table. Its task is reduced to familiarization with the document and making decisions.
4. Customer support. Most executives across industries, including finance, believe that customer support automation is essential to a company’s competitiveness. This implies both a more convenient search and storage of user information and the implementation of RPA solutions integrated with chatbots. So, bots are happy to communicate with any client, regardless of the time of day. They are ready to answer basic questions, leaving complex counseling to the people.

With such a wide range of potentially robotic processes, one has only to remember about choosing the “correct” ones among them, the effect of which will be the best.

The decision on this should be made on an individualized basis – taking into account the specific banking infrastructure and current business processes efficiency.

Let alone RPA in the banking industry, the robot can do the following:

• opening/closing applications and systems Web clients, Email (including attachments);
• navigation within applications (ERP, CRM, etc.);
• creating and moving files and folders;
• following links and emulating button presses;
• automatic switching between applications;
• filling out forms, copying;
• loading data from external sources into the program interface and directly into the database;
• comparison and validation of data, mathematical calculations;
• work on complex logic with conditions and cycles;
• OCR (PDF / DOC / XLS);
• multilevel automated verification of data entered by other employees;
• messengers – communication using intelligent chatbots;
• using predictive analytics to drive statistics-based robot decisions and data mining.

Below are ten examples of implementing Robotic Process Automation in banking, accounting, and finance.

Financial companies planning to automate their processes can learn from the following examples. These companies have pioneered Robotic Process Automation innovations beyond simple operational efficiencies.

Insurance is one of the main beneficiaries of Robotic Process Automation. Kryon Systems, a provider of RPA solutions, helped a global insurance company reduce payment processing times.

RPA has proven to be a game-changer in claims technology. Their client, a global insurance company, had to go through 26 different banking websites and use a smart search to check if payments were made. This happens on 4 different days each month and takes 4 business days each month.

Once RPA was implemented, it took only 2 hours to complete. In the past, employees made mistakes and searches were wrong, but robots provided a mechanism that increased accuracy. As a result, thousands of working hours are saved every year, and human error is eliminated.

Bancolombia, the largest bank in Colombia, has implemented RPA solutions to help people better manage their investment portfolios.

Their RPA tool, Invesbot, is available to anyone with investments over $7,000. It provides real-time market information and portfolio performance and offers advice on making changes in line with current market conditions.

Another innovation is a robot advisor who advises Colombian investors on stock marketing and helps them experiment with it. This allowed Bancolombia to teach how to invest in the stock market digitally.

“The idea is that the client does not have a higher cost for advisory services. We see this more as a highway for growth rather than something that allows us to cut back on financial advisors.”

– Juan Felipe Giraldo, President of Valores Bancolombia

The results are clear: Bancolombia has won the Digital Transformation Award at Colombia’s Best Biggest Company from PwC and CINTEL.

Keybank is the leading commercial bank in the United States to partner with Billtrust and implement RPA technology to improve its efficiency.

Bank automated invoice delivery and receivables processing with RPA solution powered by Billtrust. It includes the creation of electronic invoices with Quantum Payment Cycle Management Billtrust. Keybank has optimized accounts receivable through an end-to-end implementation of RPA.

“Banks have traditionally focused on payment execution. We think that’s important. But in consulting with our clients, we hear a lot of pain upstream and downstream of payment processing. Partnering with innovators like Billtrust enables us to optimize clients’ processes from beginning to end.”

– Matt Miller, Head of KeyBank product and innovation for commercial enterprise payments

The bank has automated repetitive manual tasks. They hope that the entire implementation of machine learning will improve processes over time. It expands its RPA capabilities for better digital transformation.

For now, most industry leaders have no doubt that RPA will increase their companies’ competitiveness over the next two years. The reason for this will be, among other things, an increase in the level of service and greater customer satisfaction.

So, let’s say a positive decision on robotization in the bank has been made. It will be equally important to correctly build further steps for its implementation and determine what basic rules should be followed in order to make a banking RPA project successful.

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