Automating Finance & Accounting Process through

Robotic Process Automation (RPA)

Introduction to RPA Technology:

Thus, basic RPA is recommended in the case of the following processes:

RPA in Finance & Accounting Process:

McKinsey & Company has conducted an extensive analysis of finance and accounting processes, as well as automation intelligence software’s capability. The study revealed that automation technology available in 2018 was capable of automating 42% to 60% of finance activities.

To provide a comprehensive overview of the process areas and their likelihood of automation, the study combined the evaluated finance and accounting tasks with other common activities. Figure 1 presents the relative complexity of these process areas and their probability of being automated.

According to McKinsey’s research shown in Figure 1, entry-level finance and accounting tasks as well as those performed by shared service centers have the greatest potential for automation intelligence.

Additionally, there are other finance and accounting processes that are good candidates for Robotic Process Automation (RPA) but are not listed in Figure 1, including bookkeeping, payroll, data migration, and entry, daily profit and loss reporting, and control testing.

These processes are ideal for RPA because they are mostly rule-based and repetitive, with standardized input and output report formats, and have detailed documentation in place.

RPA Implementation

In a study conducted by Deloitte, which gathered responses from over 400 organizations worldwide, it was found that 53% of the respondents had already initiated their Robotic Process Automation (RPA) journey, while 19% planned to start within the next two years. However, the study also revealed that only 3% of these organizations had successfully scaled their digital workforce beyond 50 bots.

According to Gartner, the reason for this low scaling rate is that organizations often underestimate the complexity of RPA initiatives, despite the wide-reaching applicability of RPA technology, affordable licenses, and low barriers to entry for implementation.

The implementation of Robotic Process Automation (RPA) can be challenging, and some of the common obstacles that organizations face include:

• Misaligned RPA program goals with a company or department’s strategic goals.
• Underestimating the complexity or disparate nature of existing processes.
• Inadequate development and/or training partners.
• Insufficient financial or human resources.
• Fragmented process automation, which means automating individual components rather than end-to-end processes where applicable.
• Absence of documented governance for the RPA program.
• Engaging the wrong business stakeholders for process selection and solution design.
• Lack of IT buy-in needed to build appropriate infrastructure and application integration support.

Key RPA Implementation Risks:

There are five critical areas identified by Deloitte for RPA implementations:

• Operational
• Financial
• Regulatory
• Organizational
• Technology

A few examples mentioned below provide you with the objectives and process through which you can achieve your goals.

Pre-requisites for implementation of RPA:

When implementing Robotic Process Automation (RPA), one of the key drivers that shape the nature of the investment is the determination of the RPA operating model. There are three primary RPA operating models:

• Centralized model – has a robotics operations center that oversees and is responsible for RPA governance and infrastructure while leading process development for the entire company.
• Decentralized model – involves a central team focused primarily on governance and infrastructure, with hubs deployed within various business teams leading implementation for respective areas.
• Federated model –places the power of governance, infrastructure, and implementation in the hands of individual teams or departments.

Once the RPA operating model is finalized, it is important to make another key decision of automating the right processes. Choosing the right processes to automate is crucial as selecting the wrong candidates can result in:

• Wasted budget.
• Negative Return On Investment.
• Dissatisfied employees.
• Reputational harm to the RPA program etc.

While mature, well-defined, and well-documented processes are good candidates for RPA, it’s worth noting that processes that do not meet all these criteria may still be great candidates. They may require more preparation, such as documentation and standardization, before utilizing automation intelligence.

Organizations should first identify how they will source automation opportunities. Here are three common ways to source automation opportunities:

• Bottom-up – (Staff to Leadership) Ideation sessions can be held or access to a central repository can be provided to staff at the grassroots level to learn what manual processes are most important to staff to be automated.
• Top-down – Leadership identifies strategic initiatives for specific processes requiring automation solutions.
• Inspired by problems or audit & analytical findings – Problems like audit gaps, financial misstatements, or inaccurate government reporting can expose errors resulting from manual processes that might not exist if the process were automated.

Selecting & Prioritizing Automation Opportunities:

When selecting and prioritizing automation solutions, it’s important to answer two fundamental questions before moving forward with automating a process:

• Can we automate?
• Should we automate it?

Key Components of RPA:

Once the pre-requisites are met, governance documentation can be prepared. Seven Key components of RPA governance have been identified in “Govern Your Bots!” which appeared in the January 2020 issue of Strategic Finance, these key components are as follows:

RPA Governance Components:

1. Governing Bodies: Establishing a governing body to manage and oversee RPA initiatives.
2. Organizational Construct: Defining the organizational structure to ensure proper alignment of RPA initiatives with the overall business strategy.
3. Operational Life Cycle: Developing a framework to manage the RPA life cycle, from development to maintenance.
4. Internal Controls: Ensuring that proper controls are in place to mitigate risks associated with RPA.
5. Technology Governance: Defining the technology standards and policies to ensure the quality and reliability of RPA solutions.
6. Performance Management: Establishing performance metrics to measure the effectiveness of RPA and track progress.
7. Vendor Management: Establishing policies and procedures for managing relationships with RPA vendors.

Stages in RPA Adoption

1. Discovering – Understanding the capabilities of RPA and identifying potential use cases.
2. Evaluating — This Stage involves:
   1. Identifying business processes for RPA development and performing a cost-benefit analysis.
   2. Proof of Concept: Running a pilot project to validate the feasibility of RPA.
   3. Vendor Selection and Technology: Selecting the appropriate vendor and technology for RPA development.
   4. Developing Governance Policy: Developing a policy framework for managing RPA initiatives.
3. Implementing — Developing and deploying RPA solutions in pilot projects.
4. Operating — Establishing a governance team to manage RPA initiatives and monitor performance.

Benefits of RPA in Finance & Accounting processes:

• Risk Profile: The impact of automating compliance processes may result in greater effectiveness of the control and regulatory environment. However, it is important to ensure that the risks associated with RPA implementation are properly identified and managed to prevent any adverse impact on the business.
• Error rate – Automation of processes generally results in a reduction of errors and an increase in accuracy. However, proper testing and validation must be conducted to ensure that the RPA solution is error-free and reliable.
• Volume – RPA for finance can easily handle high volumes of transactional processes, resulting in improved efficiency and cost benefits. Additionally, automated processes are likely to be more effective and of higher quality, leading to improved business performance.
• Time – The use of Automation Technology in finance and accounting processes results in a significant reduction in the time required to complete each transaction. This results in increased productivity and faster delivery of services to customers.
• Value Creation – Automation Technology also helps generate financial value. This is achieved through cost savings, increased efficiency, and improved accuracy in financial processes.
• Improved Customer Satisfaction – Automation of finance and accounting processes can result in improved customer satisfaction. Faster processing times, increased accuracy, and improved quality of service all contribute to a better customer experience.

Primary triggers for investing in automation of Finance & Accounting processes:

As per Joint KPMG & ACCA survey, Automation in Finance & Accounting processes led to the below advantages:

Conclusion:

Automation intelligence is already integrated into finance and accounting tasks, and the capabilities of RPA are continuously improving with technology partnerships. The benefits of RPA in accounting include reducing costs, increasing efficiency, and transforming the finance and accounting function. CFOs are increasingly turning to RPA in finance as a solution that not only reduces costs but also introduces staff to digital tools and lays the groundwork for adopting other technologies.

Without adopting RPA, finance, and accounting teams risk becoming obsolete and unable to deliver agile analytics supporting real-time business decisions. To avoid falling behind, finance and accounting teams must embrace the power of automation intelligence and transform their processes.