robotic process automation in banking

Robotic Process Automation (RPA) in Banking

In this post, we explore how Robotic Process Automation is being deployed within the financial services industry and how this technology helps with banking.

With billions of financial transactions generated daily, as well as the need to manage significant stores of customer and market data, banks can no longer rely on manual processes to complete routine, recurring, back-office functions and tasks.  

Adoption of robotic process automation (RPA) is one clear way that banks and other financial institutions can increase efficiency and boost productivity, while also reducing errors and costs. In fact, a recent report [from KPMG] has revealed that RPA can reduce costs for financial services organizations by up to 75%.

In this post, we explore how RPA is being deployed within the financial services industry and how this emerging technology can help organizations streamline operations, enhance decision-making, improve compliance and strengthen the customer experience.

A series of buildings that belong to banks.

What is Robotic Process Automation (RPA)?

Robotic process automation (RPA) is a form of intelligent automation that uses computer coded software to automate manual, rule-based, and repetitive tasks and business processes.

The software – which in this context is considered a robot or bot – leverages artificial intelligence (AI) and machine learning (ML) to perform tasks that would otherwise be managed by people, such as document reviews, transaction analysis or data entry.

Many core functions within the banking industry fit the criteria for automation in that they are:  

  • High volume
  • Repetitive
  • Rule based
  • Susceptible to human error
  • Require urgent responses on a continuous basis
  • Marked by unpredictable surges and seasonal fluctuations

7 RPA use cases in banking

With an exponential growth of robotic automation in the financial sector and banking industry, many back-office tasks that were once performed by humans are now being completed by RPA bots. 

A banker hands documents to a client for signature.

Here are seven common RPA use cases within the finance industry:

1. Fraud detection

With rapid technological advancements and millions of financial transactions being completed daily, it is impossible for human auditors to accurately review and analyze all relevant data to identify potential instances of fraud.

With the help of RPA bots, fraudulent patterns can be identified earlier in the cycle and flagged to the bank’s fraud and risk management teams in real-time. In the meantime, any suspicious accounts can be placed on hold while the activity is investigated to prevent further damage.

2. Mortgage lending and loan processing

Processing mortgage loan or other lending applications is one of the most common ways banks leverage RPA. Various inspections and checks, such as verifying the applicant’s employment status and credit history, can be managed by a bot in a vast majority of cases. An RPA solution can also automate other rule-based tasks, such as processing financial statements, making financial comparisons and completing document checks.

3. Automated report generation

Banks are required to generate annual reports and other documentation for the board of directors and other stakeholders. This process requires compiling and analyzing copious amounts of data, which is a time-intensive and potentially error-prone process.

RPA software can enable banks, financial institutions and insurance companies to generate various reports automatically using the most up-to-date data within various tools and systems.

4. Compliance operations

As with report generation, RPA can also be used to support and strengthen regulatory compliance efforts. For example, compliance officers can use a combination of RPA software, optical character recognition (OCR) and natural language processing (NLP) capabilities to automatically extract the required information and generate filings with relevant bodies. The system can also flag potential instances of non-compliance, which can then be reviewed and resolved manually by a compliance officer.

5. Know Your Customer (KYC) and Anti-Money laundering (AML)

Know Your Customer (KYC) guidelines require banks and other financial institutions to verify the identity of their clients and assess their individual risk as it relates to fraud, money-laundering and other financial crimes.

RPA can help organizations streamline this process by automating core components, such as background checks, document reviews, data extraction and other steps needed to comply with KYC. The RPA tool can also be used to automate requests for additional information, e-signatures or other routine tasks, as needed.

6. Customer onboarding and account opening

Customer onboarding, especially due to KYC guidelines, can be a time-consuming process in that the user’s identity needs to be verified through substantial document reviews. RPA can not only dramatically decrease the time it takes to complete such checks, but also reduce human error within the process, since the solution can leverage advanced technologies to identify fraudulent or altered documents that are impossible to detect with the human eye.

7. Bank data reconciliation

RPA bots are now being used for bank reconciliations, which is the process of checking the integrity of the bank’s financial records. Rule-based automations compare the bank’s data with individual transactions and identify any discrepancies. If found, alerts are triggered for further investigation.

Benefits of RPA in banking

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RPA bots are designed to complete mundane tasks quickly and accurately. The application of RPA in banking unlocks a wide range of benefits, including:

1. Cost savings

RPA solutions allow organizations to reduce manual efforts, which not only accelerates timelines but frees staff to focus on other higher-value tasks. This can lead to significant cost savings, which can, in turn, boost profitability and improve margins for the business.

2. Higher levels of efficiency

RPA bots allow for the easy automation of various tasks, which helps drive efficiency in routine business practices. In some cases, bots can replace human workers completely, which allows the business to redeploy workers into other areas of the business. In other scenarios, existing roles may be supported by robotics, which could help expedite timelines, improve productivity and reduce errors.

3. Enhanced customer experience

Maintaining high quality customer service is one of the biggest contributors to a bank’s reputation. Therefore, it is hugely beneficial for banks to integrate RPA into their service channels to better meet customers’ needs and drive satisfaction. For example, customers can access RPA-enabled chatbots during out-of-office hours, which not only helps resolve their issue faster, but also helps reduce the volume of everyday customer queries managed by human staff during business hours. RPA solutions can also help speed up application processing times, resulting in a dramatic increase in customer satisfaction. 

4. Accuracy

The implementation of RPA eliminates or dramatically reduces the need for human involvement in repetitive and mundane tasks. This can greatly decrease the likelihood of errors, as well as reduce subjectivity and unconscious bias, the likes of which could contribute to skewed decision making or increase risk.

5. Enhanced regulatory compliance

Ensuring compliance with relevant government and industry regulations is imperative for banks and other financial institutions. RPA can strengthen compliance by automatically conducting audits and generating data logs for relevant processes. Doing so makes it possible for organizations to reduce the risk of fines, avoid investigations and inquiries, limit legal disputes and preserve their reputation.

6. Integration

RPA software can be integrated within the organization’s existing tech stack, which enables the company to pull data from various systems in order to define processes, inform decision-making, and identify opportunities for improvement.

7. Ease of use

Generally speaking, the RPA tool includes out-of-the-box capabilities and a simple and intuitive user interface (UI). This means that employees do not need to manually code or configure the solution. In addition, results are typically presented in a digestible and actionable form.  

8. Scalability

RPA bots are capable of being deployed at scale, meaning that they can meet the organization’s growing needs or respond to surges in demand without creating a backlog.

9. Employee satisfaction 

When RPA bots are deployed to complete mundane and repetitive processes, it allows human employees to focus on higher-value tasks. This can help drive employee engagement and workplace satisfaction as people are able to spend time on more interesting, high-level work.

Challenges and limitations of RPA in banking 

While the benefits associated with RPA in banking are clear, adopting these solutions within the banking environment is not without challenges. Here we review some key limitations and challenges associated with RPA:

RPA is not suited for complex tasks.  

RPA solutions are best suited for completing basic and routine tasks, such as application processing, customer service management, document checks and other clear, rule-based functions. Most tools cannot perform complex, variable tasks, which means that they will not be an effective solution for more advanced use cases which require higher levels of logic or complex reasoning.  

RPA may require upskilling within the IT department.

Although RPA solutions are relatively easy to implement and configure, the IT department will still need to formulate a deployment plan. This may include development, testing and production phases. In some cases, such tasks may require specialized skills which the internal team will need to develop or otherwise acquire to ensure the investment is optimized.

RPA deployment must be supported by a broader change management program.

Along the same lines, RPA bots are designed to automate back-office operations. As such, some employees may be resistant to change because they could perceive their job being replaced by machines. However, if the organization implements an effective change management strategy, it is possible to educate employees on the new opportunities afforded by RPA, including the ability to shift away from mundane functions and focus on more interesting and engaging tasks. 

RPA integration may not be possible with some legacy solutions and infrastructure.

Many financial institutions rely on legacy systems and tools, which may not be compatible with the RPA solution. Depending on the organization, the business may need to conduct significant modernization efforts to enable RPA in various downstream functions.

Best practices for implementing an RPA solution

A banker shakes hands with a new client.

For organizations that wish to begin to use RPA or expand its application throughout the enterprise, it may be helpful to consider the following steps:

  1. Identify and prioritize RPA use cases through an in-depth assessment.

RPA has many applications within the financial services sector. Organizations should conduct a comprehensive assessment of their existing processes and tech stack to: identify instances where manual processes can be automated; gauge the complexity of doing so; and determine the value of each use case. From there, the organization can determine which efforts to prioritize, as well as associated timeline and budget.

  1. Select an ideal RPA partner.

As the RPA vendor landscape becomes increasingly competitive and crowded, it can be difficult to identify the ideal partner. One of the most important aspects of this process is to evaluate vendors based on the actual use cases your business wishes to implement, as well as their ability to integrate with your organization’s existing infrastructure.

For relatively simple applications, it may not be necessary to choose a partner that offers advanced capabilities; on the other hand, if your organization’s transformation roadmap is progressive, it will be important to partner with an organization that can serve the entire journey. Finally, if your organization is focused on one niche application, such as customer service or document processing, it may be beneficial to select a vendor that specializes in that area.

  1. Embrace a multi-faceted RPA transformation plan.

Implementation of RPA technology is but one component of a successful transformation program. The organization must also take steps to support a broader change management strategy that focuses on tangential technologies, underlying processes and the people who will ultimately use the solution. Ensuring each of these areas is carefully considered and planned is essential to both the success of the implementation of the RPA tool, as well as the organization’s broader business goals and objectives.  

RPA in banking with Inscribe 

At Inscribe, we help banks and other organizations within the banking sector embrace the power of robotic process automation to more efficiently process customer documents, streamline account openings, expedite underwriting processes, enhance compliance and so much more. Our platform enables:

  • AI-powered fraud detection
  • Intelligent document automation
  • Painless document collection
  • Actionable insights and analysis

To learn more about how Inscribe can help your organization automate processes, improve accuracy, and increase productivity with our cutting-edge platform, please reach out to schedule a personalized demo.

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