RPA In Banking Compliance: Benefits, Use cases, Best practices and Tools
Kavya Ravichandran is a skilled content writer with a flair for crafting narratives that educate and engage. Driven by a love for words and an innate curiosity, she explores various topics in the digital space, focusing on application development and modernization, UI/UX design, and emerging technologies like DevOps, AI, and more. She is adept at tailoring her narratives to suit different audiences and platforms, ensuring her work is both relevant and insightful.
Imagine this. You want to start a new account in a bank. The bank wants to vet your application through the KYC (Know Your Customer) process. They ask you to provide a range of information to authenticate your identity and address details. The KYC process includes ID card verification, document verification, face verification, biometric verification, utility bill verification, etc. It used to take 1,200 minutes to conduct a KYC. It puts a strain on the bank. There are hundreds of processes like this. All of them require thousands of person-hours. This is where Robotic Process Automation (RPA) comes in. An RPA-driven KYC process takes less than one-tenth of the time to complete. RPA has shaken up the banking status quo like no other technology.
The year 2008 changed the banking industry (and the world) forever. The Great Recession resulted in regulatory changes that would make the banking regulatory requirements more complex than any industry. The laws and regulations kept changing almost monthly, and they still do. Financial institutions were finding ways to control compliance costs while thwarting cyber attacks from hackers.
Banks have to face severe financial and reputational damage for non-compliance. In fact, they spend 5% on compliance costs. In the past decade, banking institutions have spent in excess of $321 billion on compliance operations and fines. Banks can tackle this by building a culture of compliance. Outline, refine, educate, communicate, and document compliance standards and policies with every stakeholder. Thanks to its basic rule-driven sensibilities coupled with artificial intelligence technologies, RPA is a force to reckon with.
RPA understands complex processes, and human conversations, recognize sentiments and respond in real-time. It has a systematic way of handling its tasks and makes no errors unless a human who operates it falters. From generating reports to processing mortgage applications, the use cases are endless.
This article looks at RPA, its benefits in banking compliance, use cases, best practices, popular RPA tools, challenges, and limitations in implementing them in your banking institution.
Benefits of RPA in banking compliance:
Automation in banking saves 25,000 person-hours, according to Gartner. This number summarises what RPA bots mean for banking institutions. The typical use case of RPA in banking is adhering to pre-defined validation rules. Simple as it may sound, in the banking industry, several rule-based checks make up most of its day-to-day operations. This is where RPA makes a world of difference by being excruciatingly accurate without compromising on quality and taking less time.
Let’s look at some of the benefits of RPA.
1. Increased efficiency in compliance processes:
Regulatory compliance wants you to align business practices to align them with regulations and be prepared to be audited with impeccable record-keeping. The banking industry has stringent regulations that they need to adhere to. RPA takes care of several auditing and compliance issues.
2. Cost savings:
Deloitte estimates that RPA deployment in finance results in a 30% cost reduction. Accenture suggests that there is an 80% cost decrease for certain tasks in finance. These are all promising numbers whose impact will be heard throughout the organization.
When you eliminate redundant activities and reduce the dependency on manual inputs, you end up saving a lot of money. Otherwise, banking institutions would have to spend indiscriminately on personnel, tools, and resources. Scheduling manual processes and repeatable tasks with an RPA results in cost savings.
3. Scalability:
Bots can handle any number of tasks at the same time. Human agents can concentrate on complex customer issues instead of handling repetitive and monotonous tasks. It helps provide a better customer experience.
4. Improved accuracy and data integrity:
No matter how well-rested and cognitively sharp a human is, there will be slip-ups. Unfortunately, the margin for error in financial institutions is too less. A simple misstep can result in losses of millions. This is where RPA saves the day by managing processes efficiently. It will function like clockwork and will be unaffected by data outages. The data is also backed up efficiently and automatically.
5. Enhanced regulatory compliance:
RPA generates full audit trails for every process and maintains the high process compliance that is expected of banking institutions. Banking institutions need to work on revenue-generating tasks instead of spending hours conducting compliance audit activities.
RPA bots extract the latest regulation updates to stay on top of compliance requirements. Policymakers keep updating the regulation details, and if you don’t employ RPAs for this, you will end up shelling out $4 million.
6. Zero infrastructure cost:
No significant changes are necessary for implementing RPA in financial services, thanks to its UI automation capabilities. Since RPA is cloud-based, there are no hardware or maintenance charges either.
Use Cases of RPA in Banking Compliance:
There are multiple situations where RPA bots can enhance your customer experience, handle repetitive tasks, cut costs, and reduce reliance on human agents. Let’s look at some of the most popular use cases of RPA in banking compliance.
1. Know Your Customer (KYC) verification:
Banks have to perform Know Your Customer verification for every customer. Dealing with these KYC verifications takes up the time of two or three full-time employees (FTI). Banks spend more than $60 million per year on KYC process compliance. RPA ably replaces these manual processes to verify customer data.
2. Anti-Money Laundering (AML) compliance:
AML analysts spend most of their time collecting data and organizing them. For investigating a simple money laundering case, it takes a minimum of 40 minutes to investigate a simple money laundering case since it is manual. Depending on the complexity of the case and the information available, it could take more time. RPA bots can easily take care of the data collection process and save time.
3. Process of Bank Reconciliation:
Bank reconciliation is important because it helps identify unusual transactions caused by fraud or accounting errors. It is done by comparing your internal financial records against the records provided by your bank. Several transaction data involve many banks. RPA bots to complete the process with ease. The RPA bots can validate each payment entry against bank data with several other records. The records get reconciled when the entries match.
4. Fraud detection and prevention:
Fraud instances have exponentially increased over the years, making it difficult to identify potential frauds. RPA uses a simple “if-then” method to flag anomalous transactions. For example, if multiple transactions exist in an account from a new country, the account is flagged for a potentially fraudulent transaction. The bank can investigate for fraud.
5. Automatic Report Generation:
Banks have compliance officers who are tasked with going through compliance reports. It is mandatory for brands to generate compliance reports when they spot any fraudulent or suspicious activity. These suspicious activity reports (SARs) should be thoroughly read, and the officers should fill in the appropriate details. Thanks to its natural language generation abilities, RPA reads these compliance documents, extracts the information, and fills the SAR.
6. Account Closure:
Closing a customer’s bank account based on their request is a time-consuming process. RPA systems manage to process it without any manual intervention. If not for RPA, banks would have had to manually cancel direct debits, transfer of interest charges, and funds from one account to another. With RPAs, the customer service agent can do this by completing an electronic form over the phone.
7. Loan Processing and Validation:
Processing loans for customers is no easy affair. RPA does the verification in a significantly less TAT. It auto-extracts relevant information from customers’ documents. Prepares a due diligence report by combining the above information with internal and external records. It uses advanced machine learning algorithms to make the final decision.
8. Mortgage Loan:
It takes an average of forty-five days to process a mortgage loan in the United States. RPA reduces the processing time to a few minutes. Even a simple error during the various checks, such as credit checks, repayment history, employment verification, inspection, etc., can drastically affect the process. Since the verification requires following a set of rules and checks, RPA does the job with ease. RPA cuts loan processing time by 80%, and that’s a win-win for the banking institution and the customers.
9. Card Management:
Replacement of stolen cards, billing processes, charge reversals, card blocking requests, and so on are tasks that can be automated. The best part about automating them is that it betters customer experience and reduces employees’ workload. RPA handles all of this with ease.
10. Processing credit card applications:
RPA-enabled credit card application processing is an excellent example of RPA shining in the banking industry. To process a credit card application, numerous systems have to be traversed. Data needs to be vetted, and rule-based background checks are necessary. RPA makes all of this possible within a few hours.
Case studies of successful RPA implementation in these areas:
A Las Vegas-based Credit Union saved 80% of employee time with RPA bots. They implemented end-to-end RPA back-office processes. Five bots were deployed in two months to perform tasks that were carried out by employees. The financial institution estimates that more than 200 person-hours per week were saved since the RPA implementation.
By automating file processing, customer onboarding, application processing, and a few other tasks, a tech-driven financial infrastructure, and services provider managed to reduce 75% of efforts, which is equivalent to the work done by 100 full-time employees.
BNY Mellon’s RPA journey began as early as 2016. They use robots to handle their trade settlement processes, among many others. It takes an employee five to ten minutes to reconcile a failed trade, while RPA can complete it within 0.25 seconds. The clearing house subsidiary of the bank, BNY Mellon Pershing, aims to improve its operational efficiency with 90% straight-through processing.
Best Practices for Implementing RPA in Banking Compliance:
The use of RPA technology in the banking sector is growing. Here are the best practices to consider if your bank is implementing RPA:
1. Carefully choose the robotic process automation platform:
When looking for an RPA vendor, you must consider the type of automation you want in your bank. Do you want a barebones solution or an advanced one with machine-learning capabilities? You must identify the operational issues which RPA can help with. Asses its impact and whether it is possible. Once you have clarity on this, you will find one that suits your needs. UiPath, Workfusion, Blue Prism, and Automation Anywhere are some of the popular RPA platforms.
2. Find a reliable RPA partner:
In addition to familiarity with RPA in the banking industry, you must verify their experience and preferred technology stack. Your RPA partner should be able to recommend processes that can be automated to give you the most ROI. Ensure that your partner is also well-versed with various RPA tools. They should be able to develop a roadmap to achieve your goals with RPA.
3. Automation is a continuous process:
If your RPA bots encounter cases which it hasn’t seen before, it will require human intervention. It is not possible to automate everything. The careful eyes of your team is always going to be pivotal. One must also understand that automation is a continuous process and there will come instances when you will have to look at upgrading your existing RPA setup.
4. Ongoing maintenance and monitoring:
Even after integrating RPA in your bank, it is imperative that your employees keep monitoring the results. Their efforts are required only when the RPA encounters something beyond its control. Employees must be prepared to take over in areas where automation is impossible. Make sure there are backup servers and are ready to switch automation architectures in real time as automated solutions should be available 24*7 and fool-proof.
Tools for RPA in Banking Compliance:
RPA tools help companies automate monotonous and repetitive tasks to save time and cut costs. These tools can be used to create custom scripts that would automate these tasks. Let’s look at some of the best RPA tools available.
1. Uipath:
One of the most popular and easy-to-use tools, Uipath comes with a drag-and-drop interface that helps automate a wide range of processes. It is great for web scraping, email marketing, data entry, and other routine duties such as scheduled follow-up contacts, notifications, and documentation.
Features:
- It allows for data mining and extraction.
- Enterprise-level governance for APIs.
- You can use APIs, UI, and AI, in any combination you deem fit.
- It has a growing library of API connectors.
| Advantages of using Uipath | Disadvantages of using Uipath |
|---|---|
| It has an active and helpful community of users. | It cannot read non-electronic data with unstructured input. |
| You can use the tool with minimal technical knowledge. | The number of robots operating in the Orchestrator community edition is limited. |
| Uipath is optimized for faster development and designed to give you ROI quicker. | Uipath is not a cognitive computing solution. |
| It provides many activities that can be reused by changing the parameters and properties. |
2. Microsoft Power Automate:
It automates a wide range of processes and helps create automated workflows between apps and services. Power Automate streamlines everyday tasks, uses predefined templates to create a flow, automates tasks across business systems, and so on.
Features:
- Get push notifications to your mobile to respond in real time.
- Power Automate offers the ability to link to various data sources- SQL, SharePoint, PowerBI, MS Access, and Excel.
- Comes with hundreds of prebuilt connectors.
- Cloud-based data loss prevention, identity, and access management capabilities increase security.
| Advantages of using Microsoft Power Automate | Disadvantages of using Microsoft Power Automate |
|---|---|
| Even though it is easy for beginners, it can get difficult for complex tasks. | It allows you to use only 250 actions per workflow. |
| Power Automate is targeted at Citizen Developers. They are employees without any technical background. | Workflow instances are backed up and saved only for 30 days. |
| The Microsoft community for Power Automate is pretty active. You can also find tutorials and learning materials and even ask questions in forums. | Once you run a workflow, it cannot be changed. |
| Since certain functions are missing, complex business scenarios might not be possible to handle. |
3. Automation Anywhere:
It is one of the market leaders in RPA, and it offers a comprehensive enterprise RPA platform. Automation Anywhere has built-in artificial intelligence technologies and predictive analytics that hikes its value. It offers different products such as Enterprise RPA, IQBots, Bot Insights, BotFarm, and Bot Store.
Features:
- The Task Editor comes with 380 plus actions.
- The Workflow Designer feature lets you create a graphical representation of the business processes.
- The user can generate reports based on the execution history of certain tasks.
- Automation Lifecycle Management empowers RPA bots to go through the entire stages of the software lifecycle process.
| Advantages of Automation Anywhere | Disadvantages of Automation Anywhere |
|---|---|
| They have a 256-bit credential vault, which adds a layer of security. | Setting up Automation Anywhere can be a bit complex. |
| You can extract both structured and unstructured data spread across several web pages. | There are several complaints that only an expert coder can assure stability in the bot development. |
| Its enterprise RPA can be installed and deployed both on-premise and on the cloud. Workflows or tasks can be executed based on external events. | The interface can be a bit complicated, and it will take some time before someone becomes familiar with it. |
| AI and ML-based predefined packages could be better. |
Challenges and limitations of RPA in banking compliance:
A 2020 PwC report said that 81% of banking executives were overwhelmed by the speed at which technology was impacting their operational style. The same fear grips them when they integrate automation into their systems, which is why not all banks have RPA-proofed themselves.
Let’s look at some of the challenges and limitations of RPA in banking compliance.
1. The complexity of compliance processes:
Even though RPA was developed in the early 2000s, it didn’t become a phenomenon until 2015. That’s precisely why the legal regulations haven’t been enforced properly, as it is still a relatively new technology in the eyes of the government and regulators. The compliance process will be more streamlined over time.
2. Process standardization:
RPA is extremely good at performing repetitive and mundane tasks. If the process is complicated, it becomes too difficult to implement RPA. Larger banks with branches worldwide might be heavily different across different countries. Therefore, RPA adoption requires standardization across the enterprise.
3. Integration with existing systems:
One of the biggest impediments to implementing RPA in the banking industry is its slow technological development pace. Not all banks can say they have a reliable IT infrastructure. The workload added by RPA requires more processing power and storage capacity. 43% of US banks use COBOL, a programming language that is almost seven decades old. COBOL might not be compatible with all the new-age technologies. Replacing legacy systems isn’t easy, as they are complicated and expensive.
4. Ensuring data security and privacy:
There should be robust security measures in place since RPA systems contain sensitive customer data. Banks should take stringent measures in governance, software security, data access, and credentials management.
5. IT buy-in:
RPA execution poses several challenges to the IT department. System maintenance, cloud migration, enforcing new ERPs, testing of the RPA systems, etc., can be taxing on top of taking care of existing IT systems. Getting support from the IT team is pivotal to a successful RPA implementation.
6. Estimating ROI:
25,000 hours of avoidable rework caused by human errors can be saved by deploying RPA in the financial reporting process, according to Gartner. Employing a typical cost-centric ROI doesn’t help with prioritizing RPA. Go beyond mere metrics and view it as a boon that helps banking staff work on strategic tasks instead of mundane ones.
Solutions to overcome a few of these challenges:
One of the biggest challenges when adding disruptive technologies to your repertoire is employee resistance. When people are familiar with a particular method of working, they would be hesitant to change, even if it were to make them more efficient. There is also the added fear that these bots will completely replace their jobs.
The first step in including your employees in your RPA program is to reassure them of their place at the banking organization. Get them on your side. Let them know how it will improve their jobs. If it directly affects their jobs, walk them through the transition program you have planned. The rest can be taken care of with the help of an RPA vendor with experience in the banking industry.
Conclusion:
RPA in the banking sector is expected to reach $1.12 billion by 2025. Apart from being efficient and keeping costs low, RPA in banking has the additional goal of maintaining high levels of security. Ever since RPA was introduced, it has successfully managed to eliminate human intervention to a huge extent.
Banking institutions looking to implement RPA in their technology stack should do so with alacrity. You will only regret not having bots take care of tedious tasks. Get the leadership buy-in and involve all the stakeholders to get started with RPA. Partner with a technology firm with vast experience in implementing RPA for banks.
Frequently Asked Questions:
1. What is RPA used for in banking?
RPA in finance replaces human efforts as it automates manual and repetitive tasks. It thrives in performing rule-based tasks at scale and in a significantly short period. Freeing resources can help banks to concentrate on strategic tasks. It is used in several areas- customer onboarding, commercial banking, retail banking, lending, loan application processing, account closure, etc.
2. What is compliance in RPA?
Compliance refers to conforming to policies and guidelines. It helps maintain data integrity and data security and safeguards the privacy of employees and customers. RPA increases the efficiency of a compliance program by reducing legal issues, saving time and money, and strengthening operations.
3. How does RPA improve compliance?
The compliance process keeps changing frequently. Staying on top of compliance requirements manually is extremely difficult. RPA bots scrape details from regulatory compliance documents. It can repeat the process with 100 percent accuracy every single time. It leaves an audit trail when issues arise.
4. Which banks are using RPA?
Many major banks have adopted RPA. ICICI bank adopted RPA way back in 2016. It is said to handle approximately 1,500 RPA projects. Axis bank, Deutsche bank, Kotak Mahindra bank, Suntrust bank, BB&T Corporation, BNY Mellon, and Yes bank are a few of the other banks that have adopted RPA.
5. What are the three types of RPA?
The three main types of RPA are:
Attended Automation- It is invoked by the user, and it is perfect for tasks that are triggered at points that are difficult to detect programmatically.
Unattended Automation- It reduces the work of back-office employees. These bots can be triggered like this- bot startup, specified location and intervals, and orchestrator startup.
Hybrid RPA- It is a combination of attended and unattended RPA that enables end-to-end process automation.
6. What are three RPA tools?
Below are three RPA tools:
Macros- They perform calculations, organize data, and so on. When you want to automate a process that requires only one tool, macros should be your go-to choice.
IT Process Automation (IT PA)- They automate complex processes. IT PA handles complex tasks like prioritizing action plans, taking care of alerts from multiple sources, and implementing action plans.
Cognitive Automation Tools: They have screen scraping abilities and perform tasks that require several systems. It employs a simple drag-and-drop programming interface and uses natural language processing.
7. What are the seven pillars of compliance?
The seven pillars of compliance are as follows:
- Implementing written policies and procedures from a code of conduct guide.
- Assigning a compliance officer and compliance committee.
- Conducting effective training and education.
- Developing effective lines of communication.
- Conducting internal monitoring, auditing, reviews, and inspection.
- Enforcing discipline standards with the help of disciplinary action.
- Responding to problems and taking corrective action.
8. How do you automate compliance?
The best way to automate compliance by constantly checking systems for it is by using RPA. RPA automates compliance decisions, workflows, and reporting. By using RPA, you can eliminate manual and administrative work from compliance activities.
9. What are some best practices for compliance?
- Compliance management is challenging since regulatory bodies and governments keep imposing more regulations, each more complex than the previous one. Below are the best practices to be compliant with regulatory requirements:
- Determine your end goals concerning compliance.
- Understand the regulations that affect your industry.
- Create policies and procedures that reflect your organizational values.
- Your employees are your frontline warriors in your defense against non-compliance. Track what the employees receive and acknowledge to reduce your risk.
- Conduct a thorough review of all the regulatory compliance tasks that your organization needs to address.
- Build a repository of critical documents that includes compliance information.
Looking to automate your banking processes? Transform your financial institution with Zuci Systems: the trusted RPA implementation partner for banks and credit unions. Our comprehensive Banking RPA Services will help you modernize and automate your processes for increased efficiency and productivity.
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