Financial services companies can save more than 25,000 hours at one-fifth of the currently applied cost by implementing Robotic Process Automation (RPA) for repetitive tasks. This applies well to effort-intensive undertakings like financial reporting that are otherwise grounds for errors and omissions.

Dennis Gannon, research VC at Gartner Finance, claims that “the departments that have experimented with RPA…report a series of additional benefits, from less staff time fixing mistakes and more time allocated to higher-value work.” He also highlights the considerably increased “employee engagement” and relatively downsized “turnover.”

Indeed, the viability of RPA for financial services is as clear as the technology itself. In its most valid form, RPA can be used to automate an entire assembly line, from the point of initial data entry to order and transaction processing to even some elements of customer service. This can form the foundation for a wider automation strategy that drives enterprise digital transformation.

The best approach is often to start small with a handful of RPA use cases to see where it offers the most value and then expand organically outwards.

That being said, let’s dig into some of the most pertinent benefits of RPA for banking and financial services companies.

Automates Financial Reporting

Financial reporting is recurring, time-consuming, and tedious in large financial institutions. It’s a by-product of complex regulatory requirements that require ongoing adaption to best practices and the constant need to produce different reports for stakeholders.

By bringing RPA to bear on this onerous process, overworked employees can be freed to focus more on creating and extracting valuable insights from the reports. It also frees up time-strapped administrators to spend less time manually processing rote data and make more of an effort to tackle new challenges. Such adoption further complements the hybrid nature of work brought to life in the COVID-stricken world.

Cuts OPEX and CAPEX Big Time

According to KPMG’s analysis, RPA can reduce the overall expenditure of banking and financial firms on specific processes by as much as 75%. That’s massive considering the inherently high costs of IT outsourcing, let alone hiring new employees to handle the ongoing demand for such tasks.

RPA’s inclusion means companies can drastically reduce operational costs while retaining their top-tier workforce. The crucial thing to remember here is that technology can also minimize employee turnover by narrowing the skill gap. Companies can democratize IT across the board by providing an avenue for greater employee advancement.

Helps Establish Smart Control of Offshoring

It’s easy to be engaged in offshoring in the New Normal, and understandably so. Gad Levanon, on Forbes, writes that “remote work” across operations is the “biggest legacy of COVID-19.” Naturally, outsourcing and offshoring could appear viable options; however, when too many routine and effort-intensive tasks get shipped out, the total cost of engagement (TCE) could always become higher than one presumes.

RPA, on the other hand, can help companies keep in touch with spending targets by optimizing the tasks that get moved out and minimizing the effort required to execute those tasks. Simply put, RPA helps companies maintain the integrity of their processes while still staying within their budget constraints.

Eases Customer Onboarding

The drawn-out process of onboarding customers is often too cumbersome and time-consuming to handle at scale. RPA’s natural data entry and extraction propensity helps resolve the issue by automating various processes, from verification to validation. Such capabilities also make it easier for front-end staff to address customer inquiries. Faster and easier onboarding also contributes to a superior customer experience.

Significantly Reduces Errors and Eliminates Irregularities

Considering the myriad challenges financial institutions face and the enormous amount of data at their disposal, it’s no surprise that human error is a concern. Beyond being costly for the company, such mistakes can even hurt customers in the form of fees and interest.

RPA, on the other hand, is an effective way to eliminate the possibility of such errors in manual, repetitive, and ubiquitous processes. The technology can also reduce the risk of human errors from repetitive tasks such as manual reporting associated with check and access control.

And remember that RPA can take on more complicated tasks like credit card processing. The technology can streamline repetitive tasks that, in turn, ensure higher levels of accuracy, especially with the growing influx of digital payments.

The Future of Financial Services Automation is Bright

By 2030, the worldwide RPA market would constitute a value of $13.39 billion (4 times the projected value in 2022). From what’s depicted above, the technology is more than capable of delivering great value. As more financial services companies look to kick-start automation in their processes and see the real benefits, it’s natural for them to look at more ambitious goals for the future. This is the right way to look at digital transformation. Check-in with us for stories of how companies have fared this route!

Emergys Blog

Recent Articles

  • Maximizing Customer Engagement with Salesforce

    Maximizing Customer Engagement with Salesforce

    Maximizing Customer Engagement with Salesforce

    Forget about closing deals – in today's business world, customer [...]

    Forget about closing deals – in today's business world, customer engagement is all about building bridges, [...]

  • Bridging the Gap Between Humans and Machines with Generative AI

    Bridging the Gap Between Humans and Machines with Generative AI

    Bridging the Gap Between Humans and Machines with Generative AI

    Nowadays, customers expect quick and thorough help whenever they reach [...]

    Nowadays, customers expect quick and thorough help whenever they reach out, whether it’s to order something, [...]

  • Exploring Generative AI for Manufacturing Demand Forecasting

    Exploring Generative AI for Manufacturing Demand Forecasting

    Recent disruptions in global supply chains have shown that [...]

    Recent disruptions in global supply chains have shown that traditional ways of predicting customer demand [...]