In the recent past, big names in the banking sector like Axis Bank and Deutsche Bank have made it to the news for incorporating RPA in their processes. However, even Japan’s biggest banks, like Mitsubishi UFJ Financial Group Inc.(MUFG), Sumitomo Mitsui Financial Inc. (SMFG), and Mizuho Financial Group Inc. (MHFG), made headlines for integrating banking automation through Robotics Process Automation to save operational and labor costs.
Therefore, it’s right to say – “Adopting technologies helped banks provide the best customer experience while staying competitive in the saturated banking market.”
Especially considering RPA, it has evolved into a dynamic and effective technology to maximize security and efficiency and minimize cost. According to Gartner, 80% of finance leaders have integrated or are planning to implement RPA. Also, as per Gartner analysis, if RPA is implemented completely, it can save upto 25,000 hours and $878,000 every year.
Furthermore, because of the RPA low-code approach, it’s an ideal choice for banking and financial institutions. Let’s have a look at a handful of RPA use cases in Finance industry:
Areas For Automation in Banking and Financial Sector
Some tasks rely greatly on robots in the financial domain, whereas a handful of the functions are complex to automate with the available technologies. So let’s look into which operations have the highest potential for RPA integration.
RPA Use Cases in Banking and Financial Industry
Now that I have outlined some compelling areas where financial services organizations can implement RPA technologies, let’s look at most rewarding examples.
There’s no denying improving client experience is a quick fix to organizational success. But, RPA bots can significantly relieve the banking industry of inbound queries and concerns. Besides, it can lend a hand in managing voluminous amounts of daily traffic and improve customer support.
Financial Trading Operations
Banks can use RPA technologies to expand their financial operations and strengthen their position in the financial supply chain. For instance, RPA has the potential to automate activities related to issuing, managing and closing letters of credit – most often used trade financing instruments.
Customer onboarding is among the most challenging operations in the banking domain.
For instance, manually validating each customer’s identity documents takes too much time and effort. Also, the Know Your Customer (KYC) process makes this process a little more complicated and tiring. If this is the scenario with you, RPA is the answer!
RPA bots can easily automated the customer onboarding process saving time and increasing work efficiency.
Loan Application Processing
The process of loan application is an amazing option for RPA to show its potential. A handful of manual activities like data extraction from applications, verification against different identity documents, and creditworthiness evaluation.
Automatic Report Generation
The automated report-generation process includes optimizing data extraction from internal and external systems, building reporting templates, and reviewing and reconciling reports.
Several banks and financial service providers have adopted RPA to automate these report-generating processes.
Anti-Money Laundering (AML) Prevention
Automating the complete anti-money laundering process is among the best examples of RPA in the banking sector. So often, the investigation of a single case takes approximately 30 to 40 minutes. But, with RPA, repetitive and rule-based tasks can be easily automated, resulting in a remarkable reduction in process turnaround time.
Bank Guarantees Closure
For several financial institutions, this is among highly relevant RPA use cases.
A staff team manually transcribes data in this banking process and identifies bank guarantees due for termination/closure/discharge. The creation/distribution of notifications, and the execution of closures or reversals, are all done manually, eventually resulting in reduced productivity.
In a nutshell, RPA has the potential to automate complete processes successfully.
Processing Account Closure
There is no denying end-to-end account closure sheaths several manual duties like validating the bank’s records, sending emails to clients and branch managers, and changing data in the system. However, RPA has the potential to automate these processes, allowing employees to focus on more complex tasks.
Bank Reconciliation Process
Bank reconciliation is a time-consuming process that needs a manual search for a bigger piece of transactional data that involves several banks and the balance of the final numbers.
Here, RPA comes into the picture that automates numerous manual tasks, like validating each payment entry against bank data and several other records. further, the records are reconciled if the entries match.
Credit Card Applications Processing
Last but not least use case of RPA in the banking sector is that it enables credit card application processing. RPA bots can easily traverse numerous systems, verify data, carry multiple rules-based background checks, and decide whether to approve or reject an application.
Presently, customers receive credit cards within hours, thanks to RPA.
Finally, with the untold benefits of RPA, banks should integrate RPA in their other operational areas to improve customer experience and gain a competitive edge.
After all, Robotic Process Automation in the banking and financial domain is a continuous process. You can’t automate everything at once; it makes a better choice to choose your starting point wisely.