How the banking sector is using RPA software

The finance sector is leading with RPA deployment. Here's how banks are putting the software to use.
6 September 2019 | 25 Shares

RPA software is transforming the banking sector. Source: Shutterstock

Robotic Process Automation (RPA) is big business. It has been now for some time and is continuing to grow at a rapid rate.  

According to Gartner, RPA software revenue grew 63.1 percent in 2018 to hit US$846 million, making it the fastest-growing enterprise software market. Last year North America held a 51 percent share of the RPA market. 

This year, it’s forecast to reach a worth of US$1.3 billion in 2019. “Competition is intense,” said the firm’s Research VP Fabrizio Biscotti— nine of the top 10 RPA vendors changed market share position last year. 

The market includes the likes of UiPath, Blue Prism, NICE, Kofax and Pegasystems, which offer programs to automate (usually pretty mundane) rules-based business processes. 

Reflected in the figures above, the draw of this technology makes it an attractive investment in any industry. It essentially frees staff up from menial, spreadsheet related work, while making certain business processes more efficient and free of human-error.

Further advancements in RPA autonomy with AI and machine learning are only drawing further interest, as software becomes increasingly ‘intelligent’. 

RPA and banking

But, while RPA likely factors into the transformation considerations of most large businesses, it is the finance sector— particularly insurance and banks— that is one of the most eager of adopters.

In these industries, legacy technology systems remain ingrained, and RPA solutions can help ensure successful integration, while still peeling value from earlier investments. 

Other sectors, such as insurance, utilities, and telecoms, are also big investors, but banks with a turnover in excess of US$1 billion can claim the lion’s share of investments. 

As well as catering for integration, banks have typically relied on large-scale manual workforces. 

RPA software has allowed costs, time and effort to be saved, for example, by automatically correcting formatting and data mistakes in transfer requests or by retrieving information from external auditors, or automating loan processing and credit checks.  

Other uses include fraud detection, with RPA software able to comb through vast volumes of data in spreadsheets, pull specific data points, and generate an incident report. Or in the role of compliance, tools can help copy information from a document internally to compliance forms. 

The following are some of the most common uses of RPA currently in the banking sector. 

# 1 | Optical character recognition

RPA platforms don’t just deal with numbers and plain text. Solutions are now in the market with optical character recognition (OCR), which can interpret information from handwritten forms. Editing and verification can be carried out automatically, and the information transferred and replicated into electronic forms.  

This type of software improves over the training process, where inaccurate interpretations are corrected by human customer service operators. 

# 2 | Generating reports

Incidents of fraud and cybersecurity require banks to create compliance reports, namely Suspicious Activity Reports (SAR). Previously, individuals in the compliance function would manually read investigation reports and input the required information into SARs. 

This is a repetitive task, and the information required is largely similar for each incident. Equipped with natural language generation, RPA can read through lengthy compliance documents, taking the relevant information to form these reports. 

In this role, RPA alleviates the manual burden from the compliance department, particularly as incidents of fraud are on the rise. 

# 3 | Customer onboarding

The process of onboarding new customers often requires a face-to-face or phone meeting, with a member of a bank collecting information from a customer and entering into the internal system. 

Once again, RPA can be deployed to make this data entry process more efficient and error-free.

In the same way, it can also be used in account closures; it could verify outstanding payments or loans have been paid, and all the bank’s routines have been followed before closure. 

Streamlining operations

As TechHQ reported previously, insurance company AXA was able to save 18,000 people hours— amounting to roughly £140K (US$182K)— thanks to 13 software bots deployed over the course of six months.

The UK arm of the company rolled out the RPA software to help employees with tasks such as filing correspondence with customers around insurance claims. As a result of working hours saved, the firm claimed to have seen gains in productivity among its staff as a result.