Where to Start with RPA in Banking and Financial Services

Automated processes and decision-making must be "part and parcel" in today's (and tomorrow's) banking delivery model, to secure and deliver frictionless digital customer experiences. Keys to this include establishing Robotic Process Automation (RPA) on legacy solutions / processes. With a 40 per cent -100 per cent ROI potential within 3 to 8 months, RPA offers banks and customers a tremendous win-win opportunity.

It's time to get to work and open our toolboxes.Increasingly, customers and prospects want to know their bank has resolved to be an always-on digital bank that meets their needs. Banks using process automation are able to provide customers with digital ease and transparency that seamlessly spans the entire network of the bank and all its channels, from branch to back office, mobile to digital, etc.

Digital Banking Is Important only second to always-on digital banking

By the end of 2017, 11 percent of financial services institutions considered themselves to have adopted RPA widely across their organizations.[1] Process automation is transforming banks, with some incremental changes (some transformational) for customers — such as real-time support and the ability to save unnecessary steps when opening a new account. In 2020, RPA adoption is expected to hit 2.5B and grow at a CAGR of 70-85% between 2018 and 2020.

Process Automation Has Matured and is now combined with AI and Machine learning.Process automation has reached a point to whereby it is key enabler of digital banking experience. Process automation provides for an expedited and tangible ROI. Banks may not be able to solve every

legacy system or organization process problem at once, but process automation allows modern banks to become more competitive and differentiated by an abundance of new opportunities.

Process automation technology can easily access systems via API gateways, immediately reducing reliance on manual interventions and the costs and risks. Machine learning is now integrated into technology platforms and easily implemented with a built-in add-on. Solutions by companies like Impact Tactics that have embed AI and Machine Learning into Robotic Process Automation to deliver a powerful combination to digital banking operations. This means for banks the ability to finally effectively harness external and internal data, so that they can be applied to solve real business challenges. Process automation can significantly reduce compliance costs, process waste, and allow banks to better run accurate fraud prevention programs, accelerate onboarding, and make customized and personalized customer offers.

Banks and financial institutions need to adopt a strategic, not a tactical strategy to take advantage of this opportunity. McKinsey anticipates a second automation and AI phase in the following years, when machines and software bots can perform 10 to 25 per cent of tasks in several bank functions, increase the overall capacity and give workers an opportunity to concentrate on high-value tasks and projects.

In the past decade, more than $321 billion has been spent by banks and financial institutions on compliance and fines. Banks are expected to spend almost $270 billion annually on enforcement operations only. About 10% of the operating costs of a bank are due to enforcement costs.

Integrating existing systems is expensive and labour-intensive; however by implementing RPA, financial institutions boost operations dramatically and reduce errors.

The Banking Industry

Robotics are a modern and largely underused way of raising efficiency in the banking industry while eliminating repetitive, manually-intensive conventional processes. The RPA in banking threatens to disrupt models of business outsourcing by providing a cheaper, higher-productivity model that supports and drives progress in banking processes.

Robotics helps the banking sector to incorporate the last mile into business units as before. In banking applications, RPAs refers to a wide variety of processes such as retail sector procedures, business lending, customer lending, loan processing, underwriting and anti-money-laundering, to name but a few.

Banking and finance robotics are characterized primarily as the use of powerful robotic process automation software for the deployment of designers and other robotic end-user device-level software. Creating a workforce of virtual assistants, the RPA system in the banking sector is a valuable tool for addressing and optimizing the productivity of the pressing demands of the banking industry.

That said, there are many repetitive processes in the banking sector in functions such as fraud, audit, and risk management. For example, employees may need to copy information from an internal document into conformity forms during compliance operations. When detecting fraud, employees can need to sort vast quantities of data in tablets, extract those data points and produce an incident report. RPA will automate parts of these processes.

RPA Banking Use Cases

From credit assessment to accounts payable and account reconciliation to fraud prevention, RPA solutions are being used in the BFSI industry through several processes. We will currently focus on some of the most popular RPA applications in the BFSI market.

Since RPA can be applied to a wide variety of automation projects for business processes, including the interaction with a loan processing system, many existing applications are present here. In this section, we examine in greater depth some of these cases with examples:

Customer Service Use Case

Each day, Customer Service Banks answer numerous questions, from account details to transaction status to balance details. Banks find it difficult to respond to requests with low turnaround times. RPA helps to address demands for low priority, free up the customer support team and create an improved customer experience.

Optical Character Recognition Use Case

When using an RPA platform, an employee may scan a KYC paper form and transmit the digital image to a robot. AI-enhanced RPA program can read and replicate every character in digital form automatically.

The program improves over time through the feedback from customer service providers during the testing process when any character not properly recognized is corrected and the accuracy of the character recognition gradually increases. The overall business benefit is savings for banks in costs and time.

Automatic Report Generation Use Case

Banks are expected to produce enforcement reports in the form of suspicious activity reports for fraud and cybersecurity incidents. Compliance officers read the entire manually

Investigation reports and fill up the report form with the required information.

The form is well-structured, and the information required for each incident is usually very similar. Nonetheless, the job is extremely repetitive and takes up a lot of manual and time.

RPA platforms with the capacity to create natural language can read and extract the relevant sections from each document to create the report through long compliance documents.

The software can usually be trained by the compliance officers' inputs which are best adapted to each section of the report. The market advantages are a substantial reduction in the time required to achieve this mission, which also decreases operating costs.

Customer Account Onboarding and Account Closing Use Case

Banks can deploy RPA platforms to allow software robots to automatically collect and submit the information gathered during an onboard meeting between a bank employee and a customer. First, during the call the consultant fills out an onboard form and then updates the same information on the customer portal.

The use of RPA systems for this task will potentially result in cost savings and reduce errors in the transmission of this information. This is a repetitive and time-consuming process.

For example , if a customer tries to close (supported by the bank account closure process) his credit account, RPA software bots can be used to verify whether credit was fully refunded and processes followed for the closure of the account. This ensures that the proper account closing process is always followed.

The other benefits reported by the bank include an 88% increase in transaction and loan system processing times and the confirmation of account closures on five separate systems at an impeccable 100 % accuracy rate.