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Robotic process automation (RPA) is a hot topic in business. And for a good reason, RPA has the potential to completely change the way we do things. But what about auditors? Can RPA help us audit … better?

The global audit market is a huge business with the financial audit market projected to grow to US $2.23 trillion by 2023.

Well, as the scale of work increases, so do the documentation processes. Using automation for data entry and document processes can help organizations save a lot of money. How much? Here’s an estimate

45% of workforce tasks can be automated, which could save an estimated $2 trillion in global workforce costs.

Here, we're going to explore how RPA can be used in auditing and what benefits it can bring to the table. Stick around because you might just be surprised at what RPA can do!


What Is RPA (Robotic Process Automation)?

RPA is a software technology that lets you build, deploy, and manage software robots that emulate human actions interacting with digital systems and software.

As with people, software robots can perform tasks like understanding what's onscreen, completing the right keystrokes, navigating systems, identifying and extracting data, and more.

However, software robots can do it faster and more consistently than people without the need to stretch or take a break.

Robotic accounting is different from traditional automation in that it doesn't require any custom coding or integration with legacy systems. This means that it can be up and running relatively quickly and with little cost.

How does RPA in Audit work?

Robotic Process Automation is the creation of bots that can interact with data similar to humans but with several advantages. As bots are software, they can run continuously without making mistakes like humans.

Consider these steps if you are considering automation with RPA:

Gathering Requirements

Understanding the process you want to automate is the first step to RPA automation. In best practices, a process should be mapped in its current state so that the bot designers know where the data is coming from, what systems are involved, and what the desired outcome will be.

Assessment Of Readiness

In the readiness phase, we assess whether or not your organization is ready to automate and determine whether employees possess the necessary skills to build Robotic Process Automation tasks.

If the necessary skills are not available, the decision will be made to either outsource the project or continue with the current process.

Planning A Project

If the group that is requesting automation with RPA and the bot developer decide to move forward with the project, the project plan should be drawn up. Consider how this project fits into the broader field of Robotic Process Automation.

Almost every organization is pushing for more automation, so your project is unlikely to be the first of its kind.

Conceptual Proof

It's time for the developers to work on the proof of concept (POC). They will test the theory based on the information you have provided so far. A minimal amount of data is usually used for this.

The goal is to determine if the robotic process automation tasks can be achieved and if the bot's learning logic can produce more accurate results over time or not.

Pilot Tests

If the POC shows that the automation with RPA is viable, the next stage is to try the RPA in the real world. Pilot tests are run in a monitored development environment. This test aims to mimic real-world usage as closely as possible.

The RPA is usually run parallel to the current process so that results can be compared. We measure accuracy, completeness, reliability, and speed during this phase. The bot is sent back to the developers if there are any issues with the results. This may require repeated testing.


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Implementation Of Production

When the results of pilot testing match the desired outcome, the bot is ready for deployment into production.

The POC and pilot testing completed by the team should have prepared them for real-world implementation.

Monitoring

In Robotic Process Automation in audit, repetitive tasks are performed by a bot so that your team can be more productive, but this does not mean ignoring the bots. A regular check of the outputs is advisable.

While some bots are designed to post the output files to a shared location, others are intended to alert individuals if a problem occurs. Check for blank output as well. In the event of a system update, the automated process can break, and the developers will have to revise it.

Maintaining

For updating, the process is the same as for initial development. Developers will code the bot, a pilot test will be conducted in a development environment, and then the Robotic Process Automation will be deployed into production.


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What are the benefits of using RPA in Audit and compliance processes?

RPA in audit and compliance can bring a number of benefits to the auditing process:

Faster And More Accurate Data Collection

One of the main pain points in auditing is data collection. This can be time-consuming and error-prone, mainly if data is spread across multiple systems. If your information is wrong, your whole audit could be thrown off.

RPA can automate data collection from various sources and consolidate it into a single system for further analysis. This not only saves time but also reduces the chances of errors.

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Improved Efficiency

RPA in audit can automate repetitive and manual tasks in the audit process, freeing up time for auditors to focus on higher-value activities.

For example, RPA can generate standard reports, update records, prepare documents, send emails, and more. This not only makes auditors' jobs easier but also reduces the risk of human error.

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Increased Quality

RPA in audits can help improve the quality of audits by providing a consistent and repeatable process. By automating critical tasks, auditors can be sure that steps are not missed, and that data is collected accurately.

In addition, robotic process automation in audits can provide real-time feedback on the progress of an audit, which can help identify potential problems early on.

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Higher Customer Satisfaction

Audits can be a pain point for both auditors and those being audited. There are a lot of rules and compliance requirements during the process of audit, which has to be completed carefully. Using manual processes to complete this requirement takes up a lot of time. And therefore, it is beneficial to automate the processes using an RPA in audit software like Nanonets.

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RPA in audit and compliance can help streamline the process and make it more efficient, leading to improved satisfaction from all parties involved.

Elevated Client Service

Auditors often need to collect information from clients in order to complete an audit. RPA in audit can automate this process by sending emails, setting up meetings, and sending reminders. This can help to improve client service and make the audit process smoother for all involved.

RPA can also help improve client service by providing faster turnaround times on reports and other deliverables.

Fraud Detection

RPA can help detect fraud by identifying patterns in data that may indicate fraudulent activity.

For example, robotic process automation in audit and compliance can compare data across multiple systems to look for discrepancies. This can help to flag the instances of fraud so that they can be investigated further.


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What audit processes are relevant to robotic process automation?

Even if your company isn't currently using robotic process automation (RPA), there's a good chance it will be in the near future. And when that time comes, you'll need to know which audit processes are relevant to RPA and which ones aren't.
Let's look at some of the most critical audit processes for RPA and explore how they can help ensure your implementation goes smoothly.

Process Mapping

The first step in any RPA implementation is process mapping. This is the process of identifying which tasks in a process can be automated and which ones can't.

This process is important because it will help you determine which audit processes are relevant to RPA and which ones aren't. It will also help you identify any potential bottlenecks that could impact the performance of your bots.

Process Documentation

Once you've identified which processes can be automated, the next step is to document them. This documentation will be used to build your bots, so it's important that it is accurate and up-to-date.

Your documentation should include a description of the process and any input and output data. It should also identify any possible exceptions and how they should be handled.

Process Testing

After your bots have been built, testing them to ensure they are functioning correctly is essential. Before being deployed to production, this testing should be done in a controlled environment, such as a test server.

Your tests should include both functional and non-functional testing. Functional testing will ensure that your bots can complete the task they are designed to do.

Non-functional testing will ensure that your bots can handle different types of data and deal with exceptions in a way that doesn't impact the overall process.

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Process Monitoring

Once your bots are up and running, you'll need to monitor them to ensure they perform as expected. This monitoring can be done manually or through an RPA platform.

Your monitoring should include a review of bot logs, as well as performance data. This data will help you identify any issues that need to be addressed, such as bottlenecks or errors.

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Process Improvement

As your RPA implementation matures, you should continue reviewing and improving your processes. This can be done through process mining or other process improvement techniques.

Process mining is a technique that allows you to visualize and analyze your process data. This data can be used to identify areas of improvement, such as bottlenecks or inefficient steps.


The 5 Biggest Opportunities For Robotic Process Automation To Assist Internal Audit

Internal audits can assist organizations in identifying opportunities for embedding audit automation control activities within business processes and functions. Listed below are the areas where RPA can have the greatest impact.

Gathering And Cleansing Of Data For Analytics

The RPA can create and standardize data to produce custom analytics, including automation checks for completeness, duplicates, and validation. As a result, internal audit is freed from the time spent coordinating and gathering data.

Robotic process automation in audits can also help ensure data accuracy by providing a higher level of control and oversight during the data entry process. For example, RPA can be used to validate inputted data against pre-determined rules and standards (i.e., company policy, regulatory requirements, etc.), and flag errors for correction before moving forward with analysis.

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Risk Assessment

When considering new opportunities or business processes, an internal audit can use the audit RPA to help perform initial risk assessments. RPA can quickly collect and analyze data related to the process under review, providing a comprehensive understanding of the potential risks involved.

Then it can then be used to support decision-making around whether or not to pursue the opportunity or implement the new process. This saves time and provides a more accurate picture of control effectiveness.

Controls Automation

RPA in audit can automate controls within business processes, providing a higher level of assurance around compliance and reducing the risk of human error.

This is especially beneficial in instances where controls require real-time monitoring or are repetitive (i.e., data entry).

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Population Gathering

Using bots to process data populations more efficiently and accurately than humans during the sampling and initial proof-gathering phase is possible.

This is very advantageous when it comes to large populations that require heavy computational resources to process, such as analyzing thousands of statement documents.

By offloading this work to an RPA bot, an internal audit can focus its attention on other aspects of the audit.


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Project Management Office (PMO) Areas For Internal Auditing

The PMO can use RPA in audit for a wide variety of activities, from scheduling and managing audit projects to analyzing project data and creating reports. This is beneficial as it allows the PMO to focus on more strategic tasks while RPA handles mundane, repetitive tasks.

As you can see, RPA provides many opportunities for internal audit departments to automate manual processes and improve efficiency.

If you're considering implementing RPA for audit and compliance in your organization, be sure to partner with a reputable RPA in audit provider who has experience in the internal audit space. This will ensure that your RPA implementation is successful and delivers the promised benefits.

RPA's Impact On Driving Value In Internal Audit

As organizations look to internal audits for more strategic guidance, RPA can help drive value by providing otherwise unavailable insights.

RPA can also help optimize efficiency and effectiveness within the internal audit function, freeing up time and resources to focus on more strategic initiatives.

Some of how RPA can help drive value in the internal audit include:

In-depth Analytics And Insights

RPA can help provide insights that would otherwise be unavailable, such as identifying trends, outliers, and risks.

This information can then improve decision-making and drive value for the organization. RPA can also be used to automate the generation of reports, saving time and resources that would otherwise be spent on manual tasks.

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Improved Efficiency And Effectiveness

RPA improves the efficiency and effectiveness of the internal audit function by automating repetitive tasks, such as data entry and analysis.

This frees up time and resources that can be redirected to more strategic initiatives. In addition, RPA can help improve information accuracy by providing a higher level of control and oversight during the data entry process.

Better Quality

RPA can help to improve the quality of information by providing a higher level of control and oversight during the data entry process.

This can help to reduce errors and improve decision-making.

In addition, RPA can help to automate the generation of reports, ensuring that they are accurate and up-to-date.

Enhanced Communication

RPA can help improve communication between the internal audit function and other parts of the organization by automating the generation of reports and distributing them to relevant stakeholders.

This can also support ensuring that everyone is on the same page and that information is being shared promptly.


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RPA Use Cases For Audit And Compliance

There are several ways in which RPA can be used to improve audit and compliance.

Some of the most common use cases include:

Executing And Tracking Internal Audits

RPA can be used to automate the execution and tracking of internal audits. This can include tasks such as scheduling audit activities, sending reminders to auditors, and generating reports.

In addition, RPA can be used to track KPIs and ensure that auditor independence is maintained.

Maintaining Compliance With Regulations

RPA can be used to help organizations maintain compliance with regulations. This can include tasks such as monitoring compliance risks, generating reports on compliance status, and updating compliance records.

In addition, RPA can be used to automate the distribution of compliance-related information to relevant stakeholders.

Optimizing The Audit Process

RPA can optimize the audit process in different ways, including tasks such as automating the generation of audit reports, the distribution of audit findings, and maintaining an audit trail.

In addition, RPA can be used to improve communication between the internal audit function and other parts of the organization.

Driving Continuous Improvement In Audit And Compliance

RPA can be used to help organizations drive continuous improvement in audit and compliance, like generating reports on advances and updating records.

In addition, RPA can be used to automate the distribution of information to relevant stakeholders.

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Managing Data Quality Of Audits

Automation of master data to manage evidence and have a platform to validate it to reduce the risk of fraud and improve data quality for audits.

This is a two-fold solution that benefits the auditor in automating processes and provides controls for the organization.

The goal is to get real-time alerts for any changes in the data that could indicate a compliance or control issue. This would allow the auditor to investigate and take corrective action before it becomes a material issue.

Anomalies That May Occur In The Data During Audits

Many types of anomalies can occur during the audit process. Some of the most common include:

● Inconsistencies in data

● Changes in data that are not explained

● Missing data

● Errors in data

RPA can help identify these anomalies and provide alerts to the auditor so they can investigate and take corrective action.


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Methodology To Implement RPA In Internal Audit

A few different approaches can be taken when implementing RPA in internal audits.

1. Define Clearly The Vision And Strategy For Automation

The first step is to define the vision and strategy for automation. This should be done in collaboration with all stakeholder groups.

Some of the questions that should be considered when doing this include:

  • What are the goals of automation?
  • What processes will be automated?
  • Who will be responsible for overseeing the automation initiative?
  • How will the automation initiative be funded?
  • What risks and challenges are associated with automation?

2. Implement A Foundational Infrastructure To Enable Automation

This is necessary for effective implementation, maintenance, and risk mitigation. Operational and governance frameworks should not be designed in a vacuum but aligned with enterprise standards and best practices within the organization.

This infrastructure should include:

Governance Enhancement

The first step is defining roles, responsibilities, and structures to identify which tests and processes are most promising for automation. Governance frameworks should also cover procedures for approving designs and deployment methods and standardizing documentation.

Managing Change

Things will inevitably change. Because of this, there must be protocols to monitor and address changes to automated tests and processes themselves, as well as the downstream effects of such changes.

Continual Testing And Monitoring

As business processes are dynamic, periodic quality assurance testing is imperative. Testing and monitoring should be done frequently to keep up with the changing environment.

Processing And Handling Of Exceptions

It is necessary to develop a framework and process for triaging issues, identifying operational and technical exceptions, and routing them appropriately.

3. Create A Target-State Operating Model To Support And Sustain Automation

It should be a natural extension of the existing IA operating model, yet it will have some critical differences concerning the interaction of people, processes, and technology.

Conclusion

Robotic process automation can help automate multiple rule-based processes that are the backbone of the audit process. With an error-free, faster and more efficient process, RPA can enhance audit compliance, mitigate risks and enhance the productivity of audit organizations.

Implementing RPA can help in cost savings, and FTE efforts and improve efficiency but it is important to find the correct software to see the real benefit. Getting it right is better than implementing a solution that is cheap. Nanonets is an intelligent document processing software that enhances the efficiency of organizations by automation end-to-end document processes with a no-code and workflow-based system.

Nanonets provide>95% accuracy in processing audit documents and can process documents 10x faster than manual FTEs. Interested? Try Nanonets for free. Or set up a call with our automation experts to see how you can improve your processes.


September 2022 Update: The blog was originally published in May 2022 and has been updated in September 2022.


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