RPA in Banking: Experience the Unlimited Automation and Superior User Experience

Feb 8, 2022
5 min read

Introduction

RPA in the banking sector? What to expect? The banking sector is evolving. Rapid changes in the landscape have made it essential for banks to invest in new technologies to stay ahead of competitors. RPA can help achieve this goal by making your business more efficient, faster, and smarter - which will allow you to provide better services and make timely decisions for customers. There is a lot of potential benefits banking sectors can accumulate with RPA implementation. One of the essential benefits is it improves business efficiency. Let's take a look at the first thing that can be done by using RPA in terms of banking services. That would be customer service and handling operations of account holders. For example, RPA could handle account opening for young adults who may not know what an account is or how it works. This can be handled by the software, which is programmed to answer the user questions with legitimate answers based on what a human operator would have said in response to that question. Besides, automation increases customer satisfaction. With AI technology becoming more eminent across the industry, RPA has become a mandatory investment for the banking sector. With the trusted IT service provider, banks can consider revamping their legacy systems and make a quick decision about RPA implementation for greater success.

The digital Shift reshapes end-to-end operations

The need for automation across industries, digitization initiatives and process efficiency are only driving the need to employ RPA technology faster than ever before. RPA reshapes the way we look at automation and gives a new meaning to how humans interact with machines.  RPA is no longer limited to the banking sector's new opportunities, and it's efficient for complete business transformation. This means that RPA can enable customer service officers to deal with more people than they could carry out manually in banking. RPA is considered as a technology that can help bring about this change. Banks are required to undergo major transformation efforts, regulatory changes, and customer demands. While there will still be a requirement for human labour in certain areas, RPA can ease the burden on these departments and reduce manual errors while also speeding up processes and improving customer service overall.

How could RPA have an impact on the financial services industry?

The back-end of banking processes enables complete automation to be carried out by computers. The business benefits RPA could offer for banking are worth the investment, what the industry can expect in the future. RPA has been around for a while, so there have already been several offerings in this space. However, you probably already know that the use-case is not just another checkbox item. Still, it is a game-changer for financial service providers who are frustrated with their inability to scale their back-office operations at an industrial level without investing heavily or outsourcing work entirely.

In banking, businesses will want to keep their processes automated and move more work to the front-end desk. This could include account opening, online payments, ATM handling, customer relationship management (CRM), credit check processing, and so on. However, to reap the full advantages of RPA, companies should focus more on what they can expect from a provider they opt for.

Typical pain points of RPA implementation

All enterprises seek new ways to stay competitive without compromising on consistency, quality, and compliance. RPA can help with all three. However, implementing this technology is not always plain sailing.

A few challenges are:

1. RPA technology is new and has not been optimized for use with existing platforms and systems. Environmental factors such as security controls, compliance requirements, audit trails, and lengthy training must be worked around or overcome.

2. Resolution of conflicts between a business's policies and the automation framework can challenge the IT department's credibility.

3. RPA can be both an automating and a delegating technology, which means that business analysts need to get involved in the development process and manage the automated tasks.

4. There is no standard toolset for RPA, and many development environments and languages are used, so it is often difficult to identify all the moving parts.

5. Developers are reluctant to re-deploy manual processes due to their often lengthy training process, lack of autonomy, lack of motivation, and fear of data loss in case of error during automation, among other factors.

Best Practices to implement RPA

Organizations need to overcome the challenges of meeting an enterprise's IT and compliance governance requirements, ensure that security and regulatory gaps are addressed, and resolve issues around making developers feel empowered to re-deploy manual processes.

1.  Make sure your business policies are aligned with your automation framework.  Ensure that the automation framework knows all business policies related to your business processes.

2.  Ensure the infrastructure and development tools support automated deployment, i.e., ensure you have access to source code repositories and change management systems that support automated deployment when necessary.

3.  The language used for RPA deployment must be machine-readable, which means it should be interpreted and understood by the automation framework.  This can sometimes prove a challenge for legacy systems and platforms that are not compliant with industry standards. For example, legacy systems used in the financial industry often rely on text-based commands, which tend to create challenges with modern tools that may require XML or JSON inputs to work properly.

4.  Make sure your development team is comfortable working in your business domain to implement RPA.  Most of the time, IT teams have their domain expertise and skills to maintain or develop independently of the business.

RPA implementation methodology

To implement RPA, an organization may be required to update its IT system by accessing an expert third-party vendor who can provide the necessary RPA software. Implementation should not take too long. The developer will create a plan for RPA and recommend the best way for your company to implement it. This planning period can help ensure that you don’t run into any problems or problems with the software and all of its features. Once this is complete, it’s important to train staff on how their roles will change, making sure they’re comfortable with the new system in place.

RPA implementation can make your company more efficient and reduce costs. It’s relatively low in price and quick to implement, so there’s no reason not to do it. However, you should be aware of its potential problems and risks. If you run into trouble during RPA implementation of the project isn’t working out as expected, a company that specializes in business IT services can be a great resource.

Conclusion

RPA and AI are now part of the finance sector. Reporting says the use of these automation technologies will grow at an exponential rate over the next decade. Understanding what they are, their function, how they work, and how to implement them is key to not getting left behind by this trend.

The rise in RPA/AI has created even more jobs for humans. It frees employees from monotonous tasks that don't require human intelligence skills. However, the most significant impact of RPA/AI systems is cutting down on labor hours and financial costs. These savings translate into more profits, increases in revenue, and greater job security. That was the driving force behind companies adopting RPA/AI solutions. The BFSI sector is no exception to this.

The popularization of RPA and AI can only be unlocked by a few enterprises embracing the technology. The most common use-cases for AI include risk detection, fraud detection, regulatory reporting, compliance declaration, and KYC/AML. On the other hand, the RPA use cases are more diverse and inclusive work processes in financial service companies with repetitive tasks. As with other sectors, AI and RPA are also making their way into the BFSI sector and have already reached peak growth rates.