The banking industry is witnessing rapid turbulence caused by the global pandemic and economic instability. Amidst the COVID-19 situation, banks are looking for all the possible ways to cut costs, drive revenue growth and deliver superior customer experience. RPA in banking is proving to be a key enabler of digital transformation.
According to a recent report published by Fortune Business Insights, the global robotic process automation market size is projected to reach USD 6.81 billion by the end of 2026. Leading analysts also estimate a dramatic increase in the market size of RPA technology.
As per Gartner, the market size for RPA solutions is estimated to reach $2.4 billion by the year 2023-24.
98% of IT leaders say automating business processes is vital to driving business benefits.
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Robotic Process Automation in banking
RPA in banking is defined as the use of a powerful robotic process automation software to –
- Install desktop and other end-user device-level software robots
- Build an artificial intelligence workforce or virtual assistants
RPA serves as a useful tool to address the pressing demands of the banking sector and help them maximize efficiency by reducing costs.
McKinsey foresees a second wave of automation and AI in the next couple of years where machines and software bots will execute 10% to 25% of tasks across a myriad of bank functions, expanding the overall capacity and giving the workforce an opportunity to focus on higher-value tasks and projects.
The exponential growth of RPA in financial services can be estimated by the fact that the industry is going to be worth a whopping $2.9 billion by 2022, a sharp increase from $250 million in 2016, as per a recent report.
Power of automation in banking
Over the last decade, banks and financial institutions are reported to have spent more than $321 billion on compliance operations as well as fines. Banks are estimated to disburse nearly $270 billion yearly, just on compliance operations. Almost more than 10% of a bank’s operating cost is attributed to compliance costs.
Rising operating expenses, compounded by regulatory fines along with fierce regulatory requirements slow processes down as well as influence and result in a poor customer experience.
Robotic Process Automation can enable banks to reduce manual efforts, offer better compliance, mitigate risks, and enhance the overall consumer experience. Moreover, what makes automation most suitable for banks and financial institutions is that there are no additional infrastructure requirements coupled with its low-code approach.
10 most automated processes in the banking industry
Let’s look at the most automated processes in the banking industry that have undergone complete digitization with the touch of automation.
1. Loan processing
RPA can cut down months-long processes to a record time of 10-15 minutes. Automation allows extracting relevant information from the documents submitted by the customer to verify all details. Systems use machine learning, backed by more straightforward statistical approaches to making more decisive decisions based on data analytics. Intermediary bots derive business logic, asking the user to fix all incorrect entries, assuring safer loan decisions, backed by automated confirmation letter generation.
2. Account closure process
The monthly burden of account closure requests that banks struggle to manage is way too enormous. The biggest reason for such overburden is the clients’ non-compliance, leading to delayed submission of mandatory documents.
RPA enables banks to tackle this issue by seamlessly tracking all accounts and sending them continuous automated notifications and additional reminders for timely submissions. Automation allows the cancellation of standing orders and direct debits, change of interest charges, and fund transfers with accessible online forms.
3. Know Your Customer (KYC)
Know Your Customer (KYC) is not only a critical compliance process for every bank, but it is the most complicated one as well. This process involves a minimum of 150 to even thousands of FTEs to perform checks on the customer.
Thomson Reuters confirmed that few banks spend a minimum of US $500 million per year on their KYC compliance. Banks have now started leveraging RPA to collect customer information, screen it, and perfectly validate it to reduce the considerable cost and resources. This empowers banks to complete the KYC process in a comparatively shorter duration with limited staff and minimal errors.
4. Anti-Money Laundering (AML)
AML is one of the most data-intensive processes which can be simplified using a touch of RPA. Whether it is catching suspicious banking transactions or automating manual processes, RPA implementation proved helpful in saving both cost and time than labor-intensive traditional banking solutions.
5. Accounts payable
Accounts payable (AP) is confusing and highly monotonous as a process that requires invoices digitization from vendors based on Optical Character Recognition (OCR), extracting data from all the necessary fields in the invoice, and validating them quickly. Robotic Process Automation empowers businesses to automatically credit all payments to the vendor’s account after detailed validations and reconciliation of errors.
6. Credit card application processing
Credit card applications previously took weeks-long waiting periods, resulting in customer dissatisfaction, sometimes even pushing the customer to cancel the request. However, with the power of RPA, banks can speed up the process of dispatching credit cards promptly.
It now takes only a few hours for the RPA software to gather all customer documents, make credit checks with detailed background verifications, and take wise decisions based on pre-defined parameters to check customer eligibility. RPA has perfectly streamlined the entire process of credit card processing, making the lives of banking staff and customers easy.
7. Fraud Detection
With the banking fraud landscape expanding, banks are worried about strengthening their fraud detection mechanism. With the advent of the latest technology, banking frauds have only multiplied. Thus, it is next to impossible for banks to check every transaction to identify fraud patterns manually in real time.
RPA smartly deploys an ‘if-then method to identify any potential fraud and flag them for a quick resolution to the concerned department.
8. General ledger
Banks need to mandatorily keep their general ledger updated with crucial information like revenue, assets, liabilities, expenses, and revenue, which is necessary to prepare financial statements. With this vast amount of data from diverse systems, the manual management process is highly error-prone.
RPA comes to the rescue, in this case, integrating data from diverse legacy systems to collaboratively present them in the required format. This reduces the amount of data handling efforts and time.
9. Mortgage processing
Mortgage processing is highly labor-intensive and tedious for both banks and their customers. Banks take over a month to manage their mortgage process, including numerous worrisome steps, including employment verification, credit checks, and inspection before approving each loan request. Even the slightest error by either the customer or the bank could dramatically delay the mortgage loan processing.
But, RPA has accelerated this process for banks. Robotics goes through a defined set of rules to eliminate all potential bottlenecks, to speed up mortgage processing.
10. Bank Reconciliation
Enterprises waste arduous energy each year in manually validating and reviewing online transactions. Though the advent of various technologies and fragmented solutions have mitigated the painstaking process of managing journal entries, banks are still swimming upstream towards different challenges like muddled processes, transaction volumes, and eternal sources of data feed.
RPA allows enterprises to make quick cost reductions while improvising the back-office staff workload and enabling them to engage in more fulfilling activities. Leveraging RPA solutions would allow banks to build applications for reconciliations that offer automated journal entries, sophisticated data comparison, and long-term archiving.
Benefits of RPA in banking
There are several benefits of RPA in the banking industry. Let’s jump right into some of the prominent ones.
1. Scalability
The fact that robots are highly scalable allows you to manage high volumes during peak business hours by adding more robots and responding to any situation in record time.
Additionally, RPA implementation allows banks to put more focus on innovative strategies to grow their business by freeing employees from doing mundane tasks.
2. Increased operational efficiency
Once correctly set up, banks and financial institutions can make their processes much faster, more productive, and more efficient.
3. Cost-effectiveness
Similar to any other industry, cost-saving is critical to the banking industry as well. Banks and financial institutions can look at saving around 25-50% of processing time and cost.
4. Risk and compliance reporting
RPA in banking helps in generating full audit trails for each & every process, so as to reduce business risk as well as maintain high process compliance.
5. Availability
Whether you are looking to reduce manual errors or are achieving high accuracy at a low cost, robots work 24×7 to complete the tasks assigned to them. Thus, reiterating the ever-present availability.
6. Zero infrastructure cost
One of the benefits of RPA in financial services is that it does not require any significant changes in infrastructure, due to its UI automation capabilities. The hardware and maintenance costs, further reduce in the case of cloud-based RPA.
7. Faster implementation
With RPA tools providing a drag-and-drop technology to automate banking processes, it is very easy to implement & maintain automation workflows without any (or minimal) coding requirements.
8. Business growth with legacy data
With RPA implementation, banks and the financial services industry are using legacy as well as new data to bridge the gap that exists between processes. This kind of initiation and availability of essential data in one system allows banks to create faster and better reports for business growth.
Deploying RPA
Implementing the RPA solution in banking begins with the identification of accurate and feasible processes. It is important for banks to shortlist the right processes followed by assessing them based on overall impact.
1. Thorough Assessment
First, it is crucial to conduct a thorough assessment and detailed analysis to shortlist the processes that are suitable for RPA implementation. Make a list of the main operational issues that can be addressed and resolved through RPA, followed by assessing their impact & feasibility.
2. Make a business (use) case
In the next step, calculate the cost component and efficiency gains that will be delivered by RPA implementation in your organization. Additionally, conduct a quick comparison of RPA benefits based on various metrics such as time, efficiency, resource utilization, and efforts. Also, make sure to set achievable and realistic targets in terms of ROI (return on investment) and cost -savings to avoid disappointments due to misaligned expectations.
3. Prepare a comprehensive execution strategy
Based on your specific organizational needs, pick a suitable operating model, and workforce to manage the execution seamlessly. It is crucial at this stage to identify the right partner for end-to-end RPA implementation which would be inclusive of planning, execution, and support.
Remember that not all RPA vendors fit the specific requirements of an organization. Choosing the accurate RPA tool and implementation partner can be instrumental in impacting the final outcomes of the project.
A final note
Start small with concrete sub-processes/tasks.
Identify them on your process map, prioritize them based on the benefits their automation can yield, and develop and document a set of possible case scenarios of the selected workflow.
After the most tedious tasks are automated, you can move at your own pace toward full automation.
