18 Jun - Industry Focused // By Raheel Retiwalla

What is Robotic Process Automation (RPA) in Banking?

What is Robotic Process Automation (RPA) in Banking?

At its core, Robotic Process Automation (RPA) is used by banks and other financial institutions to automate manual business processes so the banks can remain competitive in today’s market. If implemented properly, banks can start to see a positive ROI from RPA in as little as 4 weeks.

We can define RPA in banking as the use of a combination of robots and Artificial Intelligence (AI) to replace and augment human operations in banking. According to Forrester, the RPA market is expected to surpass $2.9 billion by 2021.

The rise of digital banking solutions, cryptocurrency, mobile payments, and other new businesses have forced major banks to implement new technologies to offer better services to their customers and retain a competitive advantage. Digital transformation projects are a major priority for many banks and RPA is just one aspect of the digital transformation process.

Banks use RPA to perform repetitive tasks like data entry and to automate customer service and back-office workflows. Financial institutions that utilize RPA enable their staff to focus on more complex tasks, while the RPA bots take care of the mundane activities. RPA can also be supplemented with AI and Machine Learning (ML) to handle sophisticated processes with higher accuracy and efficiency.

Enhancing RPA with Intelligent Automation

RPA provides the basics needed to automate processes. To further enhance RPA, banks are starting to implement Intelligent Automation (IA). Intelligent Automation enhances RPA through Machine Learning and AI. By doing so, the Intelligent Automation industry has been able to massively expand business process automation within banks. To sum it up, here’s how Intelligent Automation works in banking:

  • IA enables banks to automate complex end-to-end processes.
  • These processes typically involve the use of structured and unstructured data.
  • Thanks to AI and Machine Learning (ML), IA systems are able to communicate using human languages, classifying, and recognizing ‘sentiment’.
  • This understanding of sentiment or language enables IA to operate in a completely automated fashion, even automating workflow steps that would have previously required human intervention.

Top 6 Benefits of Robotics in Banking

Banks that implement RPA can elevate their customer experience while improving quality and cutting costs. It’s not uncommon for a bank to begin seeing positive ROI in as little as four weeks. Here are just a few examples of how banks benefit from RPA:

No New IT Infrastructure

With traditional IT projects, new infrastructure is often needed before the project can begin. However, implementing RPA in banking requires almost no new infrastructure. Banks can leverage existing IT infrastructure to begin reaping the benefits. One unique feature of RPA is that it can take advantage of the native user interfaces of existing legacy systems to perform its automated tasks, which makes it a “minimally invasive” solution that builds nicely upon existing infrastructure.

Save Time and Money

Due to COVID-19, cost savings initiatives are a major focus for banks in order to be competitive and provide better services. How does the implementation of RPA enable banks to save time and money? Implementing RPA within various operations and departments makes banks execute processes faster. Research indicates banks can save up to 75% on certain operational processes while also improving productivity and quality. While some RPA projects lead to reduced headcount, many leading banks see an opportunity to use RPA to help their existing employees become more effective.

Improve Processes

The digitization of data has allowed banks to reduce paperwork. RPA can quickly scan through relevant information and glean strategic analytical data. There are various RPA tools that provide drag-and-drop technology to automate processes with little to no development. Likewise, bots continue working 24/7 to take care of data entry, payroll, and other mundane tasks, allowing humans to focus on more strategic or creative work.

Augment Human Workers with a Digital Workforce

The concept of a “digital workforce” is emerging these days due to the advancement of digital technologies. Robots take care of data entry, payroll, and other data processing tasks, while humans analyze reports for gathering useful insights. On top of that, the human workforce can have their banking robots help them gather information and process data quickly so humans can complete their work with higher efficiency.

Installing and updating banking processes can take as little as a week. Furthermore, robots can be tested in short cycle iterations, making it easy for banks to “test-and-learn” about how humans and robots can work together.

Better Regulatory Compliance

Banks and other financial institutions need to comply with many legal and financial regulations. According to a recent report, over 70% of compliance officers believe automation tools like RPA could significantly improve the use of compliance resources. RPA is available 24/7 and has demonstrated high accuracy for boosting the quality of compliance processes.

Staff can use RPA tools to collect information and analyze various transactions against specific validation rules through Natural Language Processing (NLP). If RPA bots find any suspicious transactions, they can quickly flag them and reach out to compliance officers to handle the case. This type of automated proactive vigilance can help prevent financial institutions from facing financial losses and legal problems.

Improve Customer Experience

RPA can help banks improve their customer experience. There is no longer a need for customers to reach out to staff for getting answers to many common problems. RPA robots can quickly analyze the challenges of customers and provide answers to their queries. Banking staff is then able to focus on handling the more complicated customer issues. Moreover, robots are available 24/7 to handle customer issues, which significantly improves customer satisfaction.

Likewise, other time-consuming processes can be expedited. For example, RPA can reduce loan processing times, leading to happier customers who want to conduct more business with the bank.

10 RPA Use Cases in Banking

Banks have hundreds of processes occurring daily. With the rise of RPA, many manual processes performed by humans can now be done by intelligent software robots. Here are some of the RPA use cases in Banking:

Customer Service

Banks deal with a plethora of customer queries, from account establishment to fraud to loan requests. When there are a large number of inbound inquiries, call centers can become inundated. The higher wait times can quickly lead to customer dissatisfaction. RPA can take care of the low priority tasks, allowing the customer service team to focus on tasks that require a higher level of intelligence.

Compliance

Banks need to deal with a lot of rules issued by central banks, government, and other parties. It becomes challenging for staff to comply with every single law. The implementation of RPA can assist faculty in complying better with rules and regulations. RPA works 24/7 and can quickly scan through transactions to identify compliance gaps or other inconsistencies.

Accounts Payable

Dealing with accounts payable is a time-intensive process. It demands staff to digitize vendors’ invoices and then validate the information in each field before processing it. The use of Intelligent Automation, which includes Optical Character Recognition (OCR), can automate these repetitive processes by automatically reading the invoices and crediting the payments after rectifying errors and validating data.

Credit Card Processing

In the past, it would have taken weeks for a bank to validate a credit card application. Slow processing times led to dissatisfied customers, many of whom even became frustrated enough to cancel their applications. Now, the use of RPA has enabled banks to go through credit card applications and dispatch cards quickly. It takes only a few hours for RPA software to scan through credit card applications, customer documents, customer history, etc. to determine whether a customer is eligible for a card. The credit card processing is now perfectly streamlined with the help of RPA software.

Mortgage Processing

Mortgage processing is labor-intensive for both customers and banks. Most US banks take around 50-55 days to originate and finish processing a mortgage loan. Banks need to go through numerous steps including credit checks, employment verification, and inspection before approving the loan. Even a small error by either the bank or the customer could dramatically slow down the processing of a mortgage loan.

But, RPA has now accelerated the process for banks. It goes through set rules and clears potential bottlenecks, which speeds up mortgage processing. For many banks, mortgage loan times can be reduced by as much as 80%.

Fraud Detection

The advancement of technology has resulted in an increase in fraud cases. It’s impossible now for banks to thoroughly check every transaction manually and identify the fraudulent patterns.

RPA uses algorithms to identify fraudulent transactions, flag them, and pass them on to the proper departments. In the meantime, the suspicious account can be automatically put on hold to prevent any further illegal activity.

Know Your Customer (KYC) Process

Banks are accountable for collecting “Know Your Customer” or KYC. Banks employ hundreds of FTEs to validate the accuracy of customer information. Now RPA allows banks to collect, screen, and validate customer information automatically. As a result, banks are able to complete this process faster and for less money, while also reducing the potential for human error.

General Ledger

Banks deal with large amounts of data every day, constantly collecting and updating essential information like revenue, liabilities, and expenses. Banks use these pieces of information to prepare financial statements. The public media and other stakeholders go through the resulting financial reports to determine whether the relevant organizations are operating as expected. It‘s a challenging task for banks to handle such voluminous data and compile it into financial statements without any errors. With the help of RPA, banks can collect, update, and validate large amounts of information from different systems faster and with less likelihood of errors.

Report Automation

Every player in the banking industry needs to prepare financial documents about different processes to present to the board and shareholders. Banks need to explain their performance and their challenges based on these reports. It’s a must for financial institutions to be error-free in their financial statements. Banks house vast volumes of data and RPA can make managing data an easier process. The use of RPA can help banks to prepare reports with accurate data. It can collect information from various sources and arrange them in an understandable format.

Account Closure Process

Every month, many customers send account closure requests to banks. Likewise, sometimes banks need to close customer accounts if they fail to present proof of funds. With the help of RPA, banks can send automated reminders if customers have not furnished the required proof. RPA is also capable of queuing and processing account closure requests based on specific rules.

Banking RPA Case Studies

What are real-world examples of banks using RPA? At Productive Edge, we’ve worked with leading banks and leading RPA vendors like UiPath, Workfusion, and Automation Anywhere to implement RPA. Here are a few examples of RPA case studies:

Reduced Account Opening from 23 Days to 5 Minutes

A leading bank with over 10 million customers wanted to transform the account creation experience to improve customer satisfaction and reduce operational costs.

The existing manual process for account creation was slow, highly manual, and frustrating for customers. For employees, the repetitive ‘copy-paste’ tasks limited productivity, leading to lower satisfaction and retention issues. Furthermore, interacting with the bank’s multiple legacy systems created high maintenance and integration costs.

The solution to automating account opening included:

  • Used RPA bots to extract application data across diverse document types, flag missing documents, and run the KYC process with higher accuracy and speed than the manual process
  • Created a unified automation platform that integrates with multiple legacy systems
  • Designed a single audit trail of the end to end account creation process
  • Created Human-in-the-Loop capability to route exceptions to bank employees, allowing them to focus on the more challenging situations

With this solution, the bank is now able to open an account immediately while the customer is online and interacting with the bank.

Automating the Mortgage Application Process

A bank was struggling to process the >3,000 mortgage applications it received per day. The multi-step process of verifying application information against supporting verification documents (credit history, driver licenses, pay stubs, etc.) was highly manual with many redundancies.

As a result, the bank was struggling with significant backlogs and slow fulfillment times. With RPA bots enhanced with Intelligent Automation, a solution was developed that:

  • Digitizes documents and learning bots to extract relevant data from application documents and move them across internal systems
  • Uses machine learning to validate that all required documents have been submitted and detect whether a signature is present on the Power of Attorney document
  • A unified platform incorporates automation with workflow and human-in-the-loop capabilities to route exceptions to analysts.

This solution reduced backlogs, improved turnaround times, and improved customer satisfaction.

  • Impact: 12.5 FTE equivalent savings
  • Time to value: 8 – 12 weeks

Transforming Data Operations in Financial Services

Financial institutions review legal documentation (Prospectus, Term Sheets, Pricing Sheets) related to new products available (known as new issues) to share with their customers.

Extracting data is time-intensive:

  • Unstructured documents up to 700 pages
  • A large quantity of information to be extracted (around 90 data points)
  • Not always easy to interpret the text
  • The huge financial impact of any error

This process was automated to focus on reducing the time extracting data from long documents like prospectuses. This solution leveraged capabilities such as:

  • Automated categorization of incoming emails and documents: Requests classified and sent to the appropriate flow
  • Learning bots to extra key data points: AI used to read the long legal documentation and extra key data points. Where the software is unsure, people fill the gaps and provide further learning
  • Validation and quality control: work is orchestrated so all data points are validated, and there is a clear link back from each field to the source documentation

The results consisted of:

  • 75% of workflow automated
  • 30+ FTE equivalent savings
  • 40 minutes reduction in process time

Reducing Commercial Loan Booking Time by Half and Improving Analyst Capacity

For years, a bank’s commercial loan booking team struggled to comply with US regulations established by the Sarbanes Oxley Act (e.g. SOX regulations). The process of booking loans and verifying SOX compliance was high in volume, repetitive, and highly manual, requiring analysts to key 80+ data fields into a system.

Despite rigorously coded quality controls, the process was slow and prone to error. With RPA and Intelligent Automation, the process was improved by:

  • Real-time learning bots: Bots, powered by machine learning, automatically extract key data fields from several types of unstructured loan documents.
  • Centralized governance: Automating each step also created an ongoing audit trail, which enabled the bank and regulators to trace how bots interpreted and actioned data.

Through automation, the bank’s analysts were able to shift their focus to higher-value activities, such as validating automated outcomes and to reviewing complex loans that are initially too complex to automate. This transformation increased the accuracy of the process, reduced the handling time per loan, and gave the bank more analyst capacity for customer service.

The results included:

  • 80% improved accuracy of data entry
  • 50% reduced manual handling times per loan
  • Time to value: 4 – 8 weeks

RPA Software + RPA Vendors

One of the reasons RPA has become commonplace in banks is due to the rapid pace of innovation brought to the market by various RPA software vendors. RPA software provides pre-built automation solutions that can be added to your workflows with minimal effort involved.
The three leading RPA vendors are UiPath, Automation Anywhere, and Workfusion. Their software provides the basic functionality needed to start RPA projects. To fully leverage their technology, many banks choose to work with these vendors’ system integration partners. Partners are certified to help with RPA and can make implementation projects a smoother process.

UiPath

UiPath is a popular RPA software, trusted by over 2,700 enterprise and government users. UiPath offers tools for businesses to deploy software robots rapidly. Software robots can accurately mimic and perform repetitive tasks, which boost the productivity of the company. UiPath enables organizations to automate simple office tasks. Employees can automate any processes via Document Understanding, Artificial Intelligence, and AI computer vision.

You can also manage your robots and engage with robot helpers. Finally, there is a feature allowing you to measure the performance of deployed robots.

WorkFusion

WorkFusion is a big player in the RPA marketplace. Major banks like Standard Bank, Scotiabank, and Carter Bank & Trust (CB&T) use Workfusion to save time and money. Workfusion allows companies to automate, optimize, and manage repetitive operations via its AI-powered Intelligent Automation Cloud.

Banking, Finance, Insurance, and other industries are using Workfusion for automating their organizations’ operations. It offers tailored solutions, as per the needs of your industry. You can use its automation solutions for account opening, KYC processing, Anti-Money Laundering (AML), and other tasks.

Automation Anywhere

Automation Anywhere is a simple and intuitive RPA solution, which is easy to deploy and modify. Companies like Accenture, Deloitte, Asus, and others are trusting Automation Anywhere for automating its companies’ tasks.

There are on-demand bots that you can use right away with a small modification as per your needs. There are three types of bots for customers. One is to discover bot, which uncovers processes for creating bots. Secondly, there is an IQ bot for transforming unstructured data, and these bots learn on their own. Lastly, it offers RPA analytics for measuring performance in different business levels.

How to Implement RPA for your Bank

Implementing RPA for a bank can be challenging. It requires the help of technical and professionals from different departments to work together for the implementation of RPA. Here are the three steps to begin implementing RPA for your bank:

Assessment

The first task is to conduct an evaluation and shortlist processes, suitable for RPA implementation. After making a list, analyze how they impact the organization and the potential benefits of automation.

Make Business Use Cases

Upon assessment, the next work is the calculation of cost and efficiency gains you can get via RPA implementation. Make a realistic expectation of the return on investment. Make sure you use various metrics like resource utilization, time, efficiency, and customer satisfaction.

Have a Comprehensive Execution Strategy

Finally, you should pick an appropriate operating model based on your organization’s requirements. You must identify the right partner for RPA implementation with the inclusion of planning, execution, and support.

Implement RPA for your Bank with Productive Edge

By embracing RPA, banks can improve the customer experience while reducing costs and improving efficiency. Increased automation combined with more efficient processes makes the day-to-day easier for employees as they’ll spend less time on tedious manual work, and more time on profitable projects.

Productive Edge is a leading organization specializing in RPA implementation for banks. We partner with our clients to enable consumer-focused, technology-powered RPA experiences that reimagine and transform the way people live and work.

By teaming up with other leaders in this field such as Workfusion, UiPath, and Automation Anywhere, we have been able to provide our clients with instant results, using tactics like data alignment, problem framing, road mapping, and piloting new RPA bots to help banks reach their RPA goals.

To learn more about how Productive Edge can help your business implement RPA, contact us to book a free consultation.

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What is Robotic Process Automation (RPA) in Banking?