Pre Loader

Automating Finance & Accounting Process via Robotic Process Automation (RPA)

Introduction to RPA Technology:

RPA is a technology that enables a robot—the digital worker or a ‘bot’—to execute processes by emulating human interaction with computer applications through the User Interface.

In 1959, Arthur Samuel developed Machine Learning (ML), which is one of the most important technologies that eventually led to the creation of RPA. ML allowed computers to perform several critical tasks, such as translation & text summarization, etc.

RPA was first coined in the year 2000, however, the foundational technologies on which RPA was built have been around for decades. The foundational technology on which RPA is based are:

  • Screen Scraping;
  • Workflow Automation;
  • Artificial Intelligence.

The capability of RPA Technology:

RPA has the ability to:

  • Interact with other systems via Screen scraping or API Integration or OCI;
  • Ability to determine actions based on inputs it gathered from other systems;
  • Ability to Report.

What macros can do for Microsoft Excel; RPA can do for any application accessible by an end-user.

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

RPA in Finance & Accounting Process:

Mckinsey & Company conducted a detailed analysis of finance & accounting processes & automation software capability, it found that the capability of automation tools that existed in 2018 could “fully automate 42% of finance activities & mostly automate a further 19%”.

A summary of finance and accounting tasks evaluated in this study is combined with other common finance & accounting activities to present the relative complexity of the process areas & their relative likelihood of being automated in Figure 1.

Mckinsey’s findings as per Figure 1, of the greatest impact, are tasks performed by entry-level finance & accounting staff & finance & accounting shared service centers. Other examples of finance & accounting processes not listed in Figure 1 that typically make good RPA candidates include:

  • Bookkeeping.
  • Payroll.
  • Data Migration & data entry.
  • Daily profit & loss reporting.
  • Control testing.

Since these processes are mainly rule-based & repetitive in nature with standard input & output report formats & detailed documentation in place.

RPA Implementation

Deloitte conducted a study on RPA, attracting responses from more than 400 organizations globally. 53% of respondents had already begun their RPA journeys & 19% intended to begin within the next two years. Yet only 3% of these organizations had scaled their digital workforce beyond 50 bots.

Gartner found that this low scaling rate in spite of wide-reaching applicability of RPA technology, affordability of licenses, and low barrier to entry for implementation was mainly due to, “organizations found underestimate the complexity of RPA initiatives”.

Challenges in RPA Implementation:

  • Misalignment of RPA program goals to company or department strategic goals.
  • Underestimating the complexity or disparate nature of existing processes.
  • Inadequate development and/or training partners.
  • Insufficient financial or human resources.
  • Automating fragmented processes (automating individual components rather than end-to-end process where applicable).
  • No documented governance for the RPA program.
  • Wrong business stakeholders engaged for process selection and solution design.
  • Absence of IT buy-in needed to build appropriate infrastructure and application integration support.

Key RPA Implementation Risks:

Five Key risk areas for RPA implementations were identified by Deloitte:

  • Operational
  • Financial
  • Regulatory
  • Organizational
  • Technology

Examples of risks in each of these areas can be found below:

Pre-requisites for implementation of RPA:

Out of pre-requisites for implementation of RPA, the determination of the RPA Operating model is one of the key drivers that shapes the nature of the investment. There are three primary RPA operating models:

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

Once RPA operating model is finalized, another key decision would be to Automate the right processes. Choosing the right process to automate is one of the key decisions, since choosing the wrong candidates can result in:

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

While good RPA candidates should be mature, well-defined, & well-documented, it is worth noting that processes that do not check all of these boxes may still be great candidates; that may simply require more preparation such as documentation & standardization prior to automation.

Organizations should first identify how they will source automation opportunities; these 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.
  • Inspired by problems or audit & analytical findings – Problemslike auditgaps, 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:

Two fundamental questions should be answered prior to moving forward with automating a process:

  • Question 1 – Can we automate?
  • Question 2 – Should be automate?

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:

  1. Governing bodies.
  2. Organizational construct.
  3. Operational life cycle.
  4. Internal controls.
  5. Technology governance.
  6. Performance management.
  7. Vendor management.

Stages in RPA Adoption

  1. Discovering — Understand the capabilities of RPA
  2. Evaluating — This Stage involves:
    1. Identify a business process for RPA development key metrics being # Number of hours displaced, # Amount of output achieved by BOT compared to humans etc.,
    2. Identify the requirement for RPA automation i.e., the Input, Process flow for designing the Decision making & Output i.e., Reporting requirement.
    3. Proof Run of the Concept.
    4. Vendor Selection & Selection of Technology used to develop RPA.
    5. Cost to Benefit Analysis.
    6. Develop Governance Policy.
  3. Implementing — Involves development of RPA includes running the process in Pilot projects.
  4. Operating — This Stage involves:
    1. Build Governance Team & Processes
    2. Monitor Performance etc.,

Benefits of RPA in Finance & Accounting processes:

  • Risk Profile – Impact of automating compliance processes may result in the greater effectiveness of the control & regulatory environment.
  • Error rate – Automation of processes generally results in susceptibility of manual processes to errors.
  • Volume – High volume of processes transactions can be easily automated using RPA resulted in efficiency & cost benefits & also leads to a more effectiveness & higher quality of the environment.
  • Time – Automation of finance & accounting processes results in reduction of time required to complete each transaction.
  • Value Creation – Automation ofFinance & AccountingProcesses results in generation of financial value.
  • Improved Customer Satisfaction – Automation ofFinance & AccountingProcesses results in improved customer satisfaction.

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 is here to stay. Although widespread democratization of RPA, the concept of a bot for every employee, may still be far off, digital teammates are already on the payroll & leadership is assigning them finance & accounting tasks. As RPA vendors strengthen their native offerings & progress with integrating technology partnerships, the complexity of the processes digital teammates can perform with intelligent RPA will undoubtedly increase.

To become more efficient, eliminate mundane tasks, and holistically transform the finance and accounting function, many CFOs are already looking to RPA as a solution that also exposes staff to digital tools, reduces cost, and paves the way for other technologies.

As businesses demand more, CFOs who do not act will find themselves leading overpriced, overworked teams without the bandwidth or skill set to operate in an agile manner or deliver elevated analytics supporting real-time business decisions.

Thus, finance & accounting teams who have not yet embraced RPA risk of becoming obsolete or uncompetitive, thus the finance & accounting teams across the country should embark to brace itself the power of the transformation in order to unleash the power of automation in Finance & Accounting processes.

No comments yet.

Leave a comment

Your email address will not be published.