RPA and Finance Industry: Automation Benefits and Use Cases
Financial processes are always stressful and have zero tolerance for mistakes. Constant document flow and pressure requires financial officers to be knowledgeable and mentally strong. So it may be a challenge to find employees that match your expectations. However, technologies can offer an alternative.
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According to Gartner’s insights, a finance automation solution can work 20 hours a day and cost one-fifth of the amount of an in-house employee. Moreover, you don’t have to spend your time on reviewing and hiring people. Keep up with this post to know more about robotic process automation in finance, its benefits, and use cases.
What Is RPA in Finance?
Robotic process automation in finance is software that automates routine tasks and reduces the employees' workload. Usually, it’s applied to already existing, well-established financial processes. Automation includes data processing and communication between systems.
Here are some reasons why robots are better at performing routine tasks:
- Robots can’t forget anything.
- Unlike people, robots can work 24/7.
- Robots manage low-level tasks, like typing or transcribing texts way faster than people.
- Robots can’t be distracted. Staff members are frequently distracted by phone calls, chats, and other tasks. But RPA in the finance sector is all about single-tasking, so robots can’t do anything else while they have an unfinished task.
Advantage of RPA solutions over ordinary employees
The list goes on, but the examples are more powerful than facts. The Royal Bank of Canada is one of the successful RPA use cases in finance. It performs money transfers, bill payments, and processes bank statements via the web-based chatbot.
Keybank is another example of RPA in finance. This bank has automated the invoice delivery and invoice processing services. These solutions help banks to automate a number of processes and reduce the physical presence of clients in banks.
Benefits of RPA in Finance
Now that we’re clear with the idea of RPA in the finance industry, it’s time to review the benefits of this concept. Let’s single out each of them.
4 main advantages of RPA in finance sector
The transition from manual to automated processes increases the performance. Robots can perform the same actions as humans much faster. The execution speed no longer depends on the mood and condition of your employee. Now it’s all about the code optimization and hardware capabilities.
Robots are very effective when it comes to processing of unstructured data. Invoices, for example, require employees to spend a lot of time gathering data from different sources. A human factor can also lead to mistakes during the manual data entry. But well-developed algorithms extract data in a blink of an eye and provide precise data input.
It’s obvious that the main goal of RPA in the finance industry is to reduce time and money expenses. Robots can reduce the workload on your employees or even completely replace them. Thus, you cut two expenses at once. If you have an open position, you don’t have to spend time hiring a new specialist. Instead, you can replace your employee with a robot and reassign the officer to a vacant position. In the end, you will get an automated process and an experienced employee in a new position.
Another benefit of RPA in finance is a rapid ROI. It’s hard to say the exact pay off term because the RPA price varies according to users’ needs. Still, the amount of money you pay to your employees for performing routine tasks outweighs the cost of development. Let’s imagine that an employee with all the data at disposal will spend an hour making an invoice. A robot can perform this task in a few minutes.
Improved Customer Experience
The integration of the RPA finance system brings benefits to customers. RPA can speed up user data processing, provide information about interest rates for investors, and assist in opening bank accounts. For example, customer onboarding is a long process that requires a lot of manual data entry. In smaller bank branches, customers have to stand in lines because of the small number of bank managers. RPA finance solutions can automate registration, reduce the number of clients in physical branches, and save time for your clients.
Know your client (KYC) is one of the most important guidelines in financial services. These regulations prevent money-laundering and detect suspicious transactions.To comply with these guidelines, financial entities have to fulfill three main points:
Top 3 pitfalls of "know your client"
RPA solutions allow businesses to collect customer information by accessing databases, gathering data from documents, and social media. Besides, it can help to speed up the risk assessment process. Analysts spend a lot of time searching for information on complex government resources, FBI, Interpol, and more. RPA in the finance industry can deal with these tasks and give analytics more time for other tasks. Robots guarantee the maintenance of the audit trail, which is a major requirement in KYC.
RPA Use Cases in Finance
It’s hard to ignore the benefits of RPA in finance, but benefits worth nothing without the implementation. In this section, we’re going to talk about robotic process automation finance use cases.
Accounting is a major field that can benefit from RPA in the finance industry. Robotic solutions can automate the process of transcribing invoices from PDF into SAP-compatible formats, and CSV spreadsheets. Besides, RPA software places the finale file version on the server automatically. That’s how it ensures the compliance with the SOX act.
Drafting monthly payrolls is a routine task that isn’t tolerant of any mistakes. However, payroll processes are usually rule-based, require to put large amounts of data, and are highly repetitive. These factors make it a great RPA use case in finance. Automation solutions can check the correctness of employees’ payrolls by comparing the data with ERP software. Besides, RPA software can perform gross-to-net processing and supply procurement systems with relevant data.
3 examples of finance RPA in accounting
Preventing Money Laundering
Today, each bank has a department to deal with money laundering. Their task is to monitor the transactions on high-risk accounts and detect suspicious activity. Investigators have to manually check every domestic and international transaction made with this account. It’s a time-consuming process because employees retrieve checks on transactions manually from a database.
What are the benefits of RPA in finance in this field? Robotic software simplifies the process of retrieving checks. When the software notices suspicious activity, it automatically downloads checks for a predefined period of time. This results in an increased number of solved fraud cases and increases the productivity of investigators. Moreover, this system works round the clock so that auditors can work on new cases right from the start of a new working day.
With the help of AI, RPA software could solve even more problems, like comparing transactions and identifying suspicious payments. However, AI-powered RPA software development can cost you a fortune, so it’s crucial to calculate expenses wisely.
Trying to figure out the difference between AI, data science, and machine learning? We got you covered!
Quick Bank Account Opening
The bank account opening process requires a manual data entry or even a client’s physical presence at the bank branch. If clients make a mistake during data entry, the client support specialists have to reach back to them to clear things up. This action takes time from your employees and slows down the overall process of registration. RPA automation in finance offers an alternative that can eliminate the chances of a mistake.
To open a bank account, clients have to upload a photo of their driver’s license or ID. Then, finance automation RPA software digitizes the documents provided with the client and matches the ID with the government registry's information. If there’s any information missing (like a date of birth) the bank’s employee has to solve this issue with a client. Finally, the verified data is transferred to the bank system, and clients receive their banking details. A well-built ID transcribing system grants the data accuracy, so client support employees will have less work to be done.
Danske bank is a great example of how to automate the customer onboarding procedure. The bank has developed a robot that transfers the data collected during an onboarding meeting by a bank adviser from the client. The adviser has to enter data into the onboarding platform and then into the customer portal platform. Initially, it took around 20-30 minutes during each meeting. With the help of the RPA solution this time was reduced to mere seconds.
Updating Customer Data
Banks keep a lot of information about their clients, and this information should always stay relevant. Unstable data, like the phone number or a client’s address, require a recurrent verification. Obviously, you can’t call your customers once a month to ask about their current address. However, robotic process automation in finance has some other useful options.
RPA software can make queries to a government registry database to update the data on its own. Updating the client’s information is an essential procedure, especially when you’re dealing with loan processing. The government registry keeps all the information you have to know about the client. The only issue is to find the client’s phone number. Today, SIM cards are easy to purchase, and in some countries, cellular providers don’t even ask for the ID during the mobile number registration. You can still develop RPA software that can extract the information from your clients’ social media. Users often display their numbers on their social pages.
Accordingly, this use case lets you stay informed about the changes in your clients’ personal data without disturbing them personally.
Detailed Information About Bank Services
Banks provide many services. Each of them has some pitfalls and unclear details. If we’re talking about the lending process, banks should take into account the client’s credit history, income level, the number of transactions made, and more. Credit and deposit calculators are another robotic process automation finance use cases that shed light on the lending process for customers.
A plain calculator simply displays the overall payment based on the maximal credit term, an initial payment, and product price. However, clients don't know the chances of getting a loan using this calculator. RPA based calculators can analyze the client’s capacity to pay and output the real periodic payment and a preliminary bank’s decision.
The same thing with deposit calculators. An RPA-based calculator can calculate the bonuses for regular customers, deposit fees, and produce the final interest rate for the deposit. This RPA use case in finance brings transparency to loan and depositing systems and inspires trust among your potential clients.
We can take a look at Bancolombo’s use case of RPA for investors. The largest bank in Colombia, uses RPA finance solutions to provide their clients with market insights, analysis of their portfolio performance, and make suggestions on further investments. This feature is available to any client with an investments portfolio of more than $7,000.
RPA Preparation Steps for Businesses
Understanding of use cases isn’t enough to implement RPA automation in finance. To create an efficient and cost-effective system, you have to come up with a plan and stick to it. In this section, we’ll have a closer look at four main preparation steps before the development of robotic process automation in finance.
4 steps to take before automating financial processes
The estimate is an initial stage of any project. At first, you have to choose a process that you’re going to automate. Usually, that should be an operation that involves manual transferring of large amounts of data. A successful automation of such processes leads to a faster return on your investments (ROI).
Then, you have to build a feature list and describe an idea of how this RPA finance software is going to work. Don’t overload your software with useless features. Each hour of developers' work costs you money, so treat the feature list with all the responsibility. After the feature list is made, contact a software development company to estimate your project.
Steps to estimate your software project
Compare the Expenses and Possible Profits
When you know the cost of software development, it’s time to compare it with the possible earnings. Calculate how much working hours per month this software can reduce and how long it’d take to pay off.
Take a look at a client support automation use case, for example. Let’s assume that your software can reduce the workload of your employees for 20 hours/month. With an average salary of a customer support officer of $18/hour, the software saves you $360/month per each employee.
However, if the development process costs you $100,000, and you have only two client support employees, it will take almost twelve years to pay off. That’s an unacceptable return of investment term. Therefore, you have to weigh a possible profit and make a decision carefully.
Standardize Related Processes
RPA finance software can work only with standardized processes. Like any other computer program, this one needs a strict sequence of actions that should be performed one by one. Before the integration, your employees have to build a clear and straightforward system for the task you’re going to automate. Whether it’s a bank account opening or credit issuing, make the process follow a routine and rule-based order with only one expected result.
Hire a Reliable Vendor
The last step of your preparation is to find a reliable software development team. If you own a large company, you probably have an IT department, so you can come up with technical requirements and organize the development process. However, if you're in charge of a small company, you still have options for the development finance automation RPA.
Instead of a costly in-house team, you can hire an outsourced software development company. They usually deliver the same product quality for a lower price. Outsourcing companies have experienced development teams and meet all the deadlines. By the way, Clutch rates vendors based on clients’ reviews. You can use it to find a company that meets your needs.
Thinking over the outsourcing destination? This article shows all the benefits of outsourcing the project to Ukraine!
In the first case, we’ve developed software for Invoicing and Acceptance/Delivery Certificate. Our accountants load .xls file to the platform. This file contains a list of employees and their personal data. The service processes the data and automatically generates two .pdf files — Invoices and Acceptance/Delivery Certificates for all employees. The service has a web version. Out .Net team used the following technologies to make it work:
- .Net Core 3.1
- AWS EC2
- AWS RDS
As for financial CRM, it was taking too much time to load tables and hop between data-filled pages. That’s why we’ve built a database solution that’s capable of storing over 1 million records and fast-loading them during page-to-page views. You can test it here. As we couldn't find any appropriate framework for this task, we had to build it from scratch. We’ve used the following technologies to make it work:
- .Net Core 3.1 for the back end
- Angular for front end
- AWS EC2
- AWS RDS