How Audit Data Analytics Is Evolving the Way We Conduct Audits: Insights from Industry Experts 

Discover how audit data analytics is reshaping audit practices. Explore insights from industry experts on how ADAs and AI enhance risk assessment, efficiency, and audit quality.

As the world grapples with the transformative forces of Big Data and AI, the audit profession finds itself at a pivotal crossroads. The rise of audit data analytics (ADAs), which uses advanced technology and data tools to analyze large sets of financial and other business data, is helping auditors spot unusual patterns and outliers, allowing … Read more

AI-powered auditing in the digital age: precision planning for enhanced efficiency 

Discover how AI-powered audit planning enhances efficiency and precision in financial risk assessments. Learn how MindBridge AI transforms traditional audit methodologies.

In the complex world of audit and assurance, leveraging innovative technology to streamline processes is a necessity. MindBridge AI stands at the forefront of this revolution providing an AI-powered financial risk intelligence platform, designed by auditors for auditors, that transforms traditional audit methodologies into dynamic, precise, and efficient practices. By integrating AI, auditors can achieve … Read more

AI-driven audit automation: streamlining processes for scalable success 

Discover how AI-driven audit automation revolutionizes the audit process with enhanced risk detection, continuous monitoring, and real-time compliance for scalable success.

As financial data grows exponentially, traditional audit methods struggle to keep pace with the sheer volume and complexity. In today’s fast-evolving regulatory environment, relying on periodic, manual audits leaves organizations vulnerable to risk. AI-driven audit automation offers a solution by allowing finance professionals and auditors to continuously monitor transactions, detect anomalies, and ensure compliance in … Read more

Leading the future of audit

MindBridge CEO Stephen DeWitt at IIA GAM

A message from MindBridge CEO Stephen DeWitt I’ve been a perpetual entrepreneur my entire career. 40 years now. I have worked with brilliant technologists at moments of fundamental change. Now, just a few weeks into my tenure as CEO at MindBridge, I’m set to attend my first major event with the team: IIA GAM Conference, … Read more

How data-driven techniques can make a career in audit more rewarding

Auditor using MindBridge to perform data-driven analysis

For the past few years, there has been real anxiety and fear that AI will replace auditors and accountants. Much of this debate started with a now-famous Oxford study cited in The Economist, finding accountants and auditors as the second most likely job to be automated within the next two decades – second only to telemarketers! 

 However, with the adoption of AI accelerating, we are also seeing increased demand for auditors from our client base. As a result, stories of increased pay packets for auditors are abounding, while at the same time, firms’ total headcounts continue to grow. 

 

Future skills 

 It is no secret that audit firms have struggled to keep staff in the past. This is because audit has long been viewed as a training environment; one where staff picks up vital skills and understanding of business operations in order to take a step into the industry or some other professional service. The industry’s longstanding reliance on repetitive and manual audit techniques is part of this equation; no one enjoys the often endless ticking and tying.  

 As Artificial Intelligence, enabled by new standards, is creating new opportunities for evidence generation, there is also an opportunity to reframe the skills that auditors can learn on the job. As data-driven techniques become core to today’s audit, auditors can now claim to be picking up both critical business skills and AI skills.  

 Training audit staff on how to use these tools will help them future-proof their careers and potentially increase the profit margins of jobs. This fact is supported by a survey from PWC, which found that 74% of firms that invested in upskilling employees’ tech capabilities saw an improvement in their talent retention.  

 Adoption of new technology allows smaller firms to attract new joiners, who otherwise may have been tempted to join the Big Four. Employees using AI tools will learn new skills needed by CFOs of the future and master tech-led audit processes. Tomorrow’s finance leaders will need to become comfortable using technology to perform data analysis to identify areas of risk and provide insights related to financial performance, so that audit will continue to be a fantastic springboard to senior positions in the industry.  

 

The growing role of professional judgment 

 Such reliance on AI in place of traditional techniques creates a greater need for professional judgment. Auditors must now ask deep questions not just of the risk of material misstatement, but they must also pass judgment on the performance and applicability of data-driven techniques. When it comes to large-scale evidence generation, this is particularly important. 

 That’s not to say that auditors need to become full-blown data-scientists, just that they need sufficient skills to understand the strengths and weaknesses of any particular data-driven technique. In all honesty, this is not too far from the work auditors already do when designing testing; auditors have always been analysts. It’s just that they are quickly picking up techniques from the world of data science. 

 This creates an environment where auditors can sharpen their analytics skills to a much greater degree. Being able to ask great questions, both of the data and their clients (driven by the data), will lead to great auditors. Armed with the greater transparency that analytical techniques represent, conversations with customers become more conceptual, more targeted, and valuable for all those involved. All this means that audit is a great place to learn the skills of the future. 

 

Auditors are entering the market with expectations around the tools they use and ways of working

 Those joining the profession have also come to expect clear and uncluttered user interfaces; the antithesis of the tools that dominated the profession during the earlier days of computerized auditing. Firms that understand how the software user experience impacts employee satisfaction will also do better at attracting and keeping the best staff.  

 Additionally, the education system has recently evolved, with university courses in accounting teaching how to implement new technology, data analytics, and cyber security. Companies like MindBridge, with their MindBridge University Program initiative, are partnering with educators to get students ready for the labor market. By not providing the latest tech, audit firms are creating a risk that potential employees choose to go to competitors instead.  

 

Conclusion 

 While investing in new technology can be an effective strategy to help attract and retain staff, doing so also has commercial benefits for audit firms. This includes completing audits faster and more efficiently, alongside potentially reducing the cost of service delivery. 

 Expand your expertise, watch this short webinar from MindBridge here and learn how firms are adopting AI to drive growth. 

Building trust in artificial intelligence for audit

Blog post header; blue cubes moving on a conveyor belt towards a green gate.

With the advent and growth of artificial intelligence (AI) in audit, the topic of trust comes up repeatedly in discussions. Auditors have always relied on their credibility to build and maintain relationships with clients. Auditors must build their own confidence in AI technologies before convincing clients and regulators that they have achieved the same level of assurance, if not more, than traditional methods.

At MindBridge, we have been asking ourselves for some time: How can we build this confidence for our customers?

To support auditors in their assessment of AI as a viable option, we commissioned a third-party audit of the algorithms used in our risk discovery platform. This independent assessment by UCLC (University College London Consultants) is an industry first, providing a high level of transparency to any user of MindBridge technology and assurance that our AI algorithms operate as expected.

While the independent report is only available to customers, we’ll summarize the activities and results here.

Ethical AI and MindBridge

AI and machine learning (ML) are the most influential and transformative technologies of our time, leading to legitimate questions around the creation and application of these systems. Will AI-based algorithms influence potentially life-altering decisions? How are these systems secured? Are audit firms required to prove the credibility of their AI tools?

The ethics of AI sees continual press and social media coverage because the technology shapes how we interact with the world, and defines how aspects of the world interact with us.

“AI ethics is a set of values, principles, and techniques that employ widely accepted standards of right and wrong to guide moral conduct in the development and use of AI technologies.”

The biggest companies, from Amazon to Google to Microsoft, recognize the ethical issues that arise from the collection, analysis, and use of massive sets of data. The ICAEW, in its “Understanding the impact of technology in audit and finance” paper, says that it is “crucial for the regulators to develop their capabilities to be in a position to effectively regulate these sectors in the face of advances in technology.”

MindBridge has long realized that transparency and explainability are critical for the safe and effective adoption of AI, with a demonstrated commitment to the ethical development of our technology.

Why third-party validation matters

“80% of respondents say auditors should use bigger samples and more sophisticated technologies for data gathering and analysis in their day-to-day work. Nearly half say auditors should perform a deeper analysis in the areas they already cover.”

Audit 2025: The Future is Now, Forbes Insights/KPMG

The most significant difference between traditional audit approaches and an AI-based one is in the effectiveness of the auditors’ time. An AI audit analytics platform can search 100% of a client’s financial data such that auditors can avoid large samples in low risk areas, focusing their time instead on areas of high judgement and audit risk. 

Due to the increased effectiveness of AI-based tools, regulators, audit firms, and their clients now consider data analytics an essential part of the industry’s business operations. With such a widespread impact, no one should blindly trust technology that has the potential for misinterpretation or misuse.

Auditors are known for assessing risk and gaining reasonable assurance. AI is just another example where skilled, third-party technology validation must be performed.

How the audit of MindBridge algorithms was achieved

The third-party audit of MindBridge algorithms was performed by UCLC, a leading provider of academic consultancy services supported by the prestigious UCL (University College London). UCLC’s knowledge base draws from over 6,500 academic and research staff covering a broad range of disciplines, and includes clients from international organizations, multinational enterprises, and all levels of government. UCL’s reputation as a world leader in artificial intelligence meant they were the right partner for MindBridge in completing this audit.

The goal of the audit was to verify that the algorithms used by our automated risk discovery platform are sufficient in three areas:

  1. The algorithms work as designed
  2. What the algorithms do while operating
  3. Sufficiency of MindBridge processes with regards to algorithm performance review, the implementation of new algorithms, and algorithm test coverage

For auditors and the accounting industry, the importance of this type of report cannot be understated:

“Auditors have to document their approach to risk assessment in a way that meets the auditing standards. They are also required to clearly document conclusions they make over the populations of transactions considered through the course of audit. Where this analysis is being conducted through MindBridge, there is therefore a burden of proof to demonstrate that the software is acting within the parameters understood by the auditor.”

– 3rd Party Conformity Review (Algorithm Audit) for MindBridge, UCLC

The first step was for the UCLC auditors to identify potential risks in the MindBridge algorithms across four sets of criteria:

Robustness of the algorithm

Split into correctness and resilience, this set of criteria validates that the algorithms perform as expected, react well to change, and are documented well. Generally, these are rated against the ability of the algorithm to score risk properly and work properly across a range of inputs and situations.

For example, many of the techniques employed by MindBridge audit analytics are used to identify unusual financial patterns, such as those required by the ISA 240 standard. One set of these techniques falls under “outlier detection,” a form of ML that doesn’t require pre-labelled training data and as such, reduces the potential to bring bias into the analysis.

The limitation of this unsupervised ML is that it has no deep or specific knowledge of accounting practices. MindBridge adopts the concept of an ensemble, or augmenting with different techniques, to bring domain expertise into the analysis. Called Expert Score, this allows the analysis to identify the relative risk of unusual patterns by combining human expert understanding of business processes and financial monetary flows with the outlier detection.

AI explainability

Split into documentation and interface components, this set of criteria validates that the algorithms and their purposes are easy to understand for users. This is critical for financial auditors in providing clear and meaningful expectations and key to building confidence in their clients.

“When making use of third-party tools, audit trails are vital, and auditors should ensure that they are able to obtain from providers clear explanations of a tools function, including how it manipulates input data to generate insights, so that they are able to document an audit trail as robust as one that could be created with any internally developed tool.”

Response to Technological Resources: Using technology to enhance audit quality, Financial Reporting Council

Privacy

These criteria apply to the effectiveness of controls relevant to the security, availability, and processing integrity of the system used to process client information. Privacy is closely linked to the prevention of harm, whether financial or reputational. AI systems must guarantee privacy and data protection throughout the lifecycle and be measured against the potential for malicious attacks.

Bias and discrimination

This applies to the effectiveness of controls in place to prevent unfairness in AI-based decision making. As MindBridge algorithms don’t use or impact data from identifiable individuals, this category presents limited risk.

Methodology

The assessment was done by conducting numerous tests and research to grade performance along a scale from “faulty” to “working as intended or passed the tests” for the sets of criteria above. This included:

  • Using different settings and data as input into the AI algorithms and recording the results
  • Comparing the results of validation code against the results of the AI platform code
  • Conducting interviews with the CTO and key data science, software development, and infrastructure personnel to determine processes and controls for systems development, operationalization, security, and testing
  • Assessing the data science and software development expertise of the MindBridge team

The UCLC auditors were granted a level 7, or “Glass-box,” access to the algorithms. This is the most transparent level available to an assessment and allowed the audit to cover all details of the algorithms.

Graph showing 7 levels for information concealed versus feedback detail trade-off curve

All MindBridge algorithms passed the assessment and the auditor’s report is available upon request to customers, regulators, and others who must rely on our algorithms.

Conclusion

With completion of the independent, third-party audit of its algorithms, MindBridge demonstrates clear evidence for AI-based tools to support the financial audit process safely and effectively. Through this assessment, MindBridge further enables the audit of the future by helping firms build confidence with their clients on the value of making AI and audit analytics an essential part of business operations.

For auditors, this announcement makes it easier to place further reliance on the results of the MindBridge artificial intelligence, allowing auditors to sample fewer items and spend more time where it matters most. It’s a key stepping stone in building credibility for AI in audit, and we hope that such third-party algorithm audits become the standard across the sector.

To learn about MindBridge’s most recent verification journey with Holistic AI visit our blog.

For more information on how AI and automated risk discovery supports your firm, download this free eBook now:

Automated risk discovery: What is it, and how firms can achieve it

Audit standards don’t need to change. Our approach to innovation does.

Audit standards - Innovation in the approach

If there is one thing that COVID-19 taught us, the audit industry can implement wide-reaching change at scale. In a matter of weeks we witnessed audit partners driving the adoption of video calling software, new headsets appearing, and people’s home desks being upgraded. It wasn’t long before palm-tree laden beaches were appearing as backgrounds on Zoom calls, something I couldn’t have imagined a few years ago.

Following the onset of COVID-19, many of these tools became a lifeline for accounting firms, who had to quickly change the way they operate, shifting to remote digital practices.

Despite the fast pace of change for these operational parts of audit, little has changed for the core ways that auditors generate assurance. Whilst the impact and take-up of data analytics and artificial intelligence is accelerating, there are still some oft-quoted roadblocks to wide-spread reliance on these techniques. “As a profession and including our regulators, we must up the ante on making analytics a mandatory part of the audit process” recently noted Becky Shields, Head of Digital Transformation at Moore Kingston Smith. 

Often the finger is pointed at the audit standards or regulators as major blockers of innovation. “They do not allow or require new technologies” is a perspective I’ve heard a few times, and comes in a few guises. Either in pointing specifically to the audit standards, or in a general comment that such innovation isn’t required by the PPC, a checklist commonly used by audit firms in the US.

Is it true that the standards and regulations themselves are standing the way of innovation? Or do we as an industry struggle to see value from innovation and change the way we think about assurance?

 

The audit standards – fit for purpose

Let’s take a quick look at the audit standards. All the checklists and expectations for a good quality audit start with the standards, after all.

The Public Company Accounting Oversight Board (PCAOB), which regulates auditors of publicly traded companies in the United States, recently explored whether there is a need for changes to standards, guidance, or other regulatory actions in light of technological advancements like AI. 

In their report, the PCAOB stated that its “auditing standards are not precluding or detracting from firms’ ability to use technology-based tools in ways that could enhance audit quality (for example, to perform more thorough and better-informed risk assessments).” The PCAOB did, however, acknowledge that the current standards “do not explicitly encourage” the use of technology-based audit tools, which isn’t a surprising revelation. 

Encouragingly, the PCAOB praised the capabilities of technology-based audit tools, noting that they can “enhance the auditor’s ability to efficiently and effectively analyze larger volumes of data, and in more depth, than when using manual audit technologies alone.” The Board also stated that technology-based tools could assist auditors with addressing the requirements in PCAOB risk assessment standards, a view that we at MindBridge share.

The PCAOB is not alone in its assessments. Across the pond, the UK’s Financial Reporting Council (FRC) recently consulted stakeholders regarding the use of technology to enhance audit quality. In a December 2020 report outlining its findings, the FRC noted: “Respondents also agreed that whilst additional application material and guidance would be beneficial, the current assurance model and audit standards do not represent a significant impediment to the development and deployment of technology in audit.” The report also noted that nearly all the respondents agreed that technology use could “significantly improve audit quality.”

These are views that are largely shared by the international standards setters at the IAASB. In a June 2020 update from the Technology Working Group they stated “The ISAs are flexible in terms of how audit procedures may be performed – manually, involving the use of , or a combination of both.” Whilst there has been fewer statements of this kind from the AICPA, the convergence between the AICPA and the ISA’s will likely mean that those following the American Clarified Statements on Auditing Standards will be in a similar position.

Whilst not a look at the standards, Chartered Professional Accountants of Canada (CPA Canada) has issued publications which encourage their members to adopt new technologies into their practices to stay relevant: “Firms left behind during the ADA implementation are more likely to see their situation deteriorate further with each new wave of emerging technologies. Therefore, there is a pressing need for accounting firms to develop and implement a long-term ADA adoption and use strategy that will allow them to continue with the next generation of analytics using Big Data and prepare for the use of analytics related to the .”

It’s the opinion of the standards-setters, whether in the US or internationally, that audit standards are fit for purpose. Reading the standards themselves, this isn’t hugely surprising.The standards are principles based and lay out a framework under which firms are free to rely on data-driven techniques for evidence. Regulators, methodology providers, and firms must interpret these standards to create their own workflows.

If the standards are fine, perhaps it is the regulators that are standing in the way of innovation?

 

Speak softly and carry a big stick – the role of the regulator

Whilst often the standards setters and regulators are the same body, it’s worth making the distinction between these two roles. The standards are high level and principles based. The regulators, whether it is the PCAOB, the FRC, or any of the others, are entrusted with the interpretation and enforcement of the standards. The goal is to maintain a level of audit quality amongst audit firms, and to make sure the audit is delivering on its mission to society as a whole.

Largely, regulators focus on after-the-fact punitive measures to ensure audit quality. Whether through the reputational damage caused by releasing their public inspection results, fines or action taken against individual audit partners, regulators and the regulatory process focus their attention on completed audit files.

When looking at these audit files, auditors and regulators are applying a shared sense of what good looks like. There is a cultural norm for audit files. These expectations change from market to market, and from sector to sector. The audit file for a large bank will look nothing like the audit file for the small non-profit down the road. With new technologies changing the way that assurance is generated, the expectations of those that enforce quality have to keep pace with the rest of the market. How do regulators know what good looks like when assessing a revolutionary new technique?

As firms innovate, they change their audit file and assurances models. They may do in a way that does not fit with the regulator’s or peer’s expectations for what a good quality audit looks like. This dynamic makes firms rightly nervous about putting together an audit file that looks nothing like other files in the same sector. The fear of the regulator is a real deterrent to trying new things – why stick your head above the parapet when the checklist is accepted.

We often see auditors request for greater levels of guidance from the regulators. It’s a theme that was echoed in much of the recent research from the regulatory bodies, and would be surely welcome. But the regulators are in a difficult position, as innovation often requires an agile, experimental and iterative approach. How can the regulator’s possibly create guidance for techniques that are under drastic evolution from one year to the next?

 

Safe spaces and dialogue

Regulators across the US, Canada, and the UK have a major role to play in encouraging and fostering innovation. Dialogue with auditors is a good place to start, and in our experience regulators are open to speaking with firms innovating on their audit approach. Even better would be the establishment of safe spaces for firms and the regulators to collaborate on innovative techniques. It’s an approach that the UK financial regulator, the FCA, has implemented well with its Digital Sandbox and TechSprints

This kind of collaboration between firms and regulators would allow both to explore new ways of creating assurance, and to receive feedback in a low pressure environment. It’s a classic approach for exploring new ways of thinking. It also has the potential to enable firms to innovate on real data; another key requirement to truly exploring new ways to generate assurance. Given the opportunity for artificial intelligence to change the way that the industry works, now seems like as good a time as any.

There’s also an opportunity for firms to create their own safe-spaces for innovation. Asking a separate team to try a new technique or technology alongside the traditional checklist is one such approach. This allows a side by side comparison, and an opportunity to assess what level of assurance both are generating. It provides a place where auditors can ask ‘what do I actually learn about my client from doing it this way’, without the regulators breathing down their neck. The firm can always take these experimental working papers to their regulator if they want feedback.

 

Where’s the carrot? Firms need incentives to innovate

In the end, firms need to gain a competitive advantage in the market from innovation. If they didn’t, there is no point in them innovating. Often innovation drives improved audit quality, so the firm must translate this into bigger and better client wins, or eliminate work they were previously conducting. 

Publicly released inspection reports from the regulators are one key public facing measure of audit quality, but it is hard for everyone involved to tell whether their particular audit is one that is deficient in some way. The large delay between the audit work happening and the release of these public results also undermines the value that these inspections play. 

Whilst the regulators could consider ways to make the audit process and its outputs more transparent, firms also have the opportunity to talk about the results of their audit much more openly with their clients and prospective clients. Greater transparency into the audit process and its outputs make it more likely that innovative firms will reap the rewards from pushing the boundary. 

The capabilities that technology-based tools can bring to the audit process mean that clients expect more from their auditors than ever before. Rather than a hindsight perspective, clients want a “forward-looking view”, with deeper insights that add value. Clients no longer want a financial checklist, according to Audit 2025: The Future is Now, a report from Forbes Insights and KPMG. Firms that maintain the “if it’s not broken, don’t fix it” attitude about their methodology are increasingly losing ground in the market.

“Clients want their auditors to take things to the next level to weigh and prioritize risks and opportunities based on their in-depth knowledge of the organization, its controls and processes, so more-informed decisions can be made to guide the organizations forward,” the report stated. Openly presenting the findings, particularly aided by visualisations, cements the auditor’s position as a fountain of knowledge about a company.

That forward-looking expectation also means that more clients expect their auditor to stay current with technology and adapt as new tools become available. As a result, clients “rightly believe that technology has improved the quality of audit,” noted the KPMG/Forbes Insights report. 

So it’s no surprise that 78% of KPMG/Forbes Insights respondents believe auditors should use more sophisticated technologies for gathering data, and nearly 80% think auditors should analyze bigger samples.

 

A wider range of skills needed for tomorrow’s audit

The pace of change is accelerating in the audit market, and it seems clear that today’s innovations will define how we generate assurance in tomorrow’s audit.

The skill set of auditors has to expand in order to facilitate the audit process of tomorrow. That shift necessitates an adjustment in attitudes and mindsets to benefit the industry at large. In order for these changes to be successful, change needs to happen at every level of the industry, from the junior associates joining our firms, through the partners and regulators. 

Among the sought-after skills that clients want their auditor to have, the KPMG/Forbes Insights report found that 67% of clients are looking for increased technology skills, while 66% want better communication skills, 65% for critical thinking skills, and 59% for investigative financial skills. They are not looking for the old-school, number-crunching accountant any more. Considering they are obsessed with learning patterns and identifying anomalies in data, It is time for us to learn from what the data scientists are doing.

Given the massive skills and talent gap that the audit industry is facing, It’s also worth pointing out that teaching these skills is an opportunity for firms to keep their best staff around for longer.  Many like-minded organizations, including MindBridge, have also taken an interest in preparing tomorrow’s accountants and auditors with the tools and knowledge they need to succeed before they reach the workforce.

 

The data revolution is an opportunity for auditors

The audit sector is known for being stuck in its ways. We’re the number-crunching, adhering to regulations, checklist-oriented type. Sometimes, we follow those traits to a fault. As technology proliferates and data volumes grow, modern businesses are putting data front and center. This introduces both risk and complexity, but also an opportunity for data savvy auditors to provide leadership in the data driven world.

By encouraging more curiosity, creativity, and experimenting across the industry, we can hopefully adjust attitudes and mindsets regarding technology-based tools and audit standards. 

The future of audit is being reshaped by technology, there is no dismissing that. However, the industry must ensure it is keeping pace with the broader economy. Instead of looking for excuses to resist change, collectively, we need to find ways around any obstacles so that the accounting industry becomes a leader in innovation, resilience, and agility. We can’t wait to be told by regulators what tools to use ​​ it’s crucial to change attitudes and embrace the changes that are happening now. 

A study by the Harvard Business Review summed it up perfectly: “If more and more companies methodically dismantle blockers to innovation and encourage employees to experiment, perhaps we will finally see the gap close between leaders’ innovation goals and reality.”

PCAOB makes room for technology: What does it mean for auditors?

An abstract image of growth and development to symbolize the adoption of new technologies and processes by storied firms and businesses.

In the last decade, technology has altered the ways in which we work and live. This has become increasingly true in the auditing profession. 

According to Audit 2025: The future is now, a report released by KPMG and Forbes Insights that surveyed 200 CFOs, chief audit officers, chief tax officers and other financial executives, “the financial audit is poised for profound and rapid change.” That is, technology, combined with the expertise of today’s skilled auditor, allows audit professionals the opportunity to take a deeper look into an organization’s financial facets and provide more informed insights.   

The Public Company Accounting Oversight Board (PCAOB), which regulates audits of publicly listed companies in the United States, recently released their own report, the Data and Technology Research Spotlight, which provides timely and relevant observations for auditors and stakeholders on the current and future of audits and technology-based tools being implemented in the industry. 

It’s a mouthful, but essentially those responsible for regulating public audits in the United States are beginning to respond and acknowledge the transition we’ve been tracking  (and encouraging) for a few years now: audit approaches using technology-based tools.

In the KPMG-Forbes report, 80% of respondents said that auditors should use bigger samples and more sophisticated technologies for data gathering and analysis. As technology blazes a trail through the audit space, more firms, organizations, and boards are taking notice.

Back to PCAOB report, it included an interesting statement on standards:

“PCAOB auditing standards do not preclude audit firms’ use of technology-based tools during an audit but our current standards do not explicitly encourage the use of such tools.”

While far from an endorsement, the PCAOB is the most recent major organization in the audit space to recognize the value of technology to increase the quality and efficiency of risk assessment and discovery.

In the same KPMG-Forbes report, however, 66% of respondents noted that the regulatory environment as their biggest challenge to enhancing the role of the auditor:

A graph from Forbes and KPMG showing poll data from auditors on what is holding them back from integrating technology into their methodology, and from enhancing their roles.

Source: KPMG & Forbes, Audit 2025: The future is now

In light of this report, and the reality of auditors and accountants, we asked ourselves, what does this mean for not only public companies, but organizations everywhere that are still on the fence about integrating potentially groundbreaking technologies into their audit work?

What does this mean for the audit industry?

The use of technology in audits is not new. Currently, many of the firms governed by the AICPA’s regulations and standards  use technology in their audit approach to help augment their audits and enhance their judgement

In the PCAOB report, the board considered that “guidance or changes to the standard may be needed, given the increasing prevalence of technology-based tools and the increasing availability and use of information from sources external to the company, both in financial reporting and as audit evidence.” 

Beyond the admittance of such “technology-based tools” into public audit, this also speaks to the need to update standards and regulations that may inhibit their use. This is a major step for any regulator as, historically, audit standards have struggled to reconcile the advent of tools that may increase audit quality and efficiency with storied rules that attempt to define a “quality audit.”

A full meeting room discussing a presentation on the utility of technology to augment audits and enhance the judgement of auditors.

The AICPA and ICAEW (covering North America and England & Wales, respectively) are two major regulatory and oversight bodies that are both grappling with their relationship to new and upcoming technological advancements in accounting. AICPA, through CPA.com, are planning for the introduction of DAS (the Dynamic Audit Solution), a solution that looks to combine technology and traditional audit to bridge the gap between innovation and regulation. 

The PCAOB’s stance on technologically-augmented audits has given fintech innovators—and the firms that employ their technology—room to breathe, and to consider their relationship with the long-established audit industry.

So, where do we go from here?

The PCAOB’s Digital Technology Spotlight did more than open the door for technology in public audit, though: it outright listed the benefits of digitally-augmented risk assessment for auditors, firms, and businesses everywhere.

Reports conducted like the PCAOB and Audit 2025 show that technology-based audits reap huge benefits for firms and businesses. One potential benefit noted in the PCAOB report posits that these tools provide auditors with more persuasive evidence and confident findings in their risk assessments. This corresponds with a finding in the KPMG-Forbes report which showed that 62% of respondents want their auditor to articulate a clearer point of view on critical issues. 

“62% of respondents want their auditor to articulate a clearer point of view on critical issues.”

Other benefits mentioned include automating certain aspects of repetitive or less complex audit procedures like reconciling account balances to the general ledger, vouching sales transactions to subsequent cash receipts, or preparing confirmations to be sent to third parties. 

With the positives mounting, it’s understandable why organizations like the PCAOB felt it necessary to take a stand on this issue, and to formalize it into their standards (albeit off-handedly). However, it was also interesting to see the benefits specifically tied to public audit.

For example, in certain instances, the PCAOB Spotlight found that technology-based tools can aid auditors in analyzing data for indicators of management bias and the ability to provide auditors with information that could even suggest revisions to their planned audit response. 

Many more benefits weren’t mentioned in the PCAOB Spotlight, however. Like what automating recurring tasks can allow auditors to do, such as expanding their skill set, and allowing them more time to communicate with clients and stakeholders. Nor did it mention the marketing potential for firms utilizing AI and other hot-button technologies, from a branding perspective. 

Ultimately, this report is yet another example of the wider audit and accounting community recognizing the value of technology and embracing it. Given that, you may be wondering how you, your firm, or your business can begin to leverage technology for the betterment of your audits.

Thankfully, we have you covered.

How to integrate technology into your audits

With the addition of technology to your audit methodology also comes many changes to the way data is collected, analyzed and controlled in your firm, department, or business. This can seem daunting; the idea of implementing new policies and procedures and updating a methodology that has been so good to you for so long isn’t easy. 

But this change is good.

A man reviews financial data for a client's audit.

As mentioned, utilizing technology in your audit assessment has taken a long road to regulatory acceptance; technology moved too quickly to be tested and proven against the manual means of gathering and analyzing data — the person behind the calculator punching numbers worked, it seemed. However, now that both private and public regulatory boards are starting to recognize the power that using technology-based tools have in conducting audits, there is no reason not to accept the future of audit: technology.

The MindBridge Audit Approach works to empower auditors and finance teams with AI-enabled technology to automate tedious processes and provide deeper insight into financial data. 

From the planning, gathering, and analyzing stages, MindBridge’s technology allows users to analyze 100% of transactions to spot anomalies and potential risks faster. We appreciate the importance of understanding 100% of the process as well. 

It’s like cooking: you need a great recipe to make a great meal. If you go in blind, you may not like what comes out of the oven.

Audits should be treated with the same transparency, thoroughness, and detail. Which is why the MindBridge Audit Approach requires an understanding of your business and objectives, conducting preliminary risk assessments, evaluating internal controls, and building a plan for successful audit engagements.

Our Audit Approach Briefing Paper offers you a practical introduction to revamping your audit approach using MindBridge.

Tech-driven audit approach: What you need to know

Audit data going through technology

Deciding on the best audit approach isn’t a cookie-cutter process. While a long-standing relationship with a client or in-depth industry knowledge can give auditors a leg up, defining an effective audit approach requires careful consideration and planning for every engagement.

After all, your audit teams understand that every client is unique. So, deciding on the best ways to approach an audit will be too. Everything from the client’s objectives and business operations to known or unknown risks, internal controls, and much more will determine how you and your team go about any particular audit.

However, there’s something else you may need to think about that often goes unmentioned: the role of technology in your audit approach.

As this pandemic continues to propel widespread digital transformation and standards evolve to embrace new technologies, there is a growing need for auditors to consider updating their audit methodology too.

After all, a tech-driven audit approach can not only help auditors work more efficiently, but it may also allow them to deliver greater value to their clients. Whether it’s AI auditing software or other financial automation tools, technology serves to complement traditional auditing processes and lays a foundation for even better financial insights over time.

How does a tech-driven audit approach differ from a traditional audit?

A tech-driven audit approach considers the use of technology right from the get-go. It means there’s already some level of buy-in from management about auditing technologies, so your people are trained on the tech you’re using. You might even have data handling processes set up to fully leverage the capabilities of the new auditing solution.

While reaching this level of technological adoption might seem overwhelming, it shouldn’t have to be. With a little support on your side from the right vendor and a solid change management plan, you’ll be able to easily trial new technologies and reach higher levels of adoption at your own pace.

Then, as you go into new audit engagements over time, it’ll become second nature for you to think about the role of technology, how it will complement your existing methodologies, and how it may support your resources. From the planning stages right through to completion, you’ll consider how to automate manual tasks, get extra validation and assertion, and perhaps even uncover new insights that are buried in the mounds of client financial data.

In other words, implementing a tech-driven audit approach means you’re thinking ahead about how to best use the technology to deliver a quality audit. And you’re identifying the specific procedures or tasks where the auditing technology will be most beneficial.

What are the key factors to consider in a tech-driven audit approach?

Defining a tech-driven audit approach isn’t entirely different than a traditional one. It just requires another layer of consideration about how the technology fits into your methodologies. Below, we’ll explore what a tech-driven audit approach might look like and the areas where technological considerations can be made.

Understanding the client’s business and objectives

Whether you use technology in your audit or not, getting to know your client is a given. You’ll need to consider the industry they’re in, their business operations, their audit objectives, and other unique factors that pertain to the organization to achieve an effective assessment.

When defining objectives, it’s also important to consider those beyond the financial statement audits too. In fact, in a recent Deloitte report, 95% of the 351 c-suite, finance, and audit committee executives polled said that audits should provide additional value beyond an independent report on the historical financial information. Essentially, clients are looking for deeper insights, analysis, and recommendations.

When you implement a tech-driven audit approach, your audit team will be able to automate manual tasks and work more efficiently. That’ll allow you to assign extra resources to added-value services such as helping your client uncover new insights. Using technology, you’re essentially able to broaden your service offering and point your clients towards new opportunities that will positively impact their business.

At this stage, you’ll also need to understand what financial software your client is using and how you’re going to best access the information you need. With all this in mind, here are a few questions to ponder to map out your tech-driven audit:

Conducting the preliminary risk assessments

Identifying risks of material misstatement and their relative significance is an integral part of defining your audit approach. Because when you have a good understanding of the potential risks at play, you’re better able to plan for and execute a comprehensive and high-quality audit.

At this stage, auditors will look over balance sheets and income statements to spot any obvious inconsistencies. They might also dive into subledger data and run some preliminary testing on journal entries. The challenge here is that a traditional audit approach will leave so much data untouched and unexamined.

In a tech-driven audit approach, this is a key area where your audit technology can really make a difference. For instance, if you’re using an AI auditing platform, you’ll be able to test 100% of your client’s financial data and dive into accounts receivable and accounts payables subledgers  to see if any other anomalies stand out. This allows your team to conduct a deeper level of preliminary risk analysis and potentially uncover risks that weren’t on your radar.

Consider the following on risks assessment when building a tech-driven audit:

  • How can you use your auditing technology to get a clearer picture of the financial risks?
  • Does your technology allow you to filter results and dive into your client’s financial data to get a better understanding of those risks?
  • If you save time by automating risk assessment procedures, where else can you apply resources to offer your clients more value?

Evaluating the company’s internal controls

Evaluating the effectiveness of the company’s internal control over financial reporting is another critical component in your audit. Your auditors will likely perform a series of tests to validate how well internal controls are being upheld within the company.

In a tech-driven audit approach, the technology can either complement or replicate manual testing procedures to achieve higher levels of assurance. The technology might also point your team to riskier data that will then open up new conversations with your clients about potential weaknesses in internal controls.

For example, our AI auditing software automatically identifies control points to spot high-risk transaction data. The auditing team can also adjust these control points and use other capabilities within the platform to recreate traditional control testing models.

All of this will allow your team to move forward with greater confidence in the audit engagement while ensuring high levels of accuracy and diligence. Here’s more to think about:

  • Does your technology complement internal control testing or replicate manual processes?
  • What control testing models can you effectively carry out using your technology?
  • Can you adapt control points and testing to different clients and industries?

Building the plan for the audit engagement

Putting together the audit plan outlines why, how, and when you’re going to execute the audit procedures. These include everything from the planned nature, timing, and extent of risk assessment procedures, controls tests, substantive procedures, and any other relevant audit tasks.

When putting together the audit plan, an auditor will usually provide examples and reports that justify why certain procedures will be critical for the audit. In a tech-driven audit, it’s important to consider how your technology can back up your findings and assessments and help you build a more complete plan.

This could include exporting powerful visual graphs and data that support your audit plan and substantiate the details of specific procedures. Ultimately, this gives the client a snapshot view of where the auditors have identified risks and why certain procedures are warranted.

Here are some tech-focused questions to consider when creating your audit plan:

  • Does your technology allow you to easily export information to build a better audit plan?
  • Can you customize graphs or visuals to support the findings of your preliminary risk assessment?
  • Can you easily share information with your client to help steer conversations about the audit plan or other potential opportunities?

Are you ready to embrace a tech-driven audit approach?

The role of technology in audits is growing every day. More auditors are not only embracing new tools such as AI auditing software to support their audit strategies, but industry standards are also evolving to accommodate higher levels of automation in audit practices. Even the AICPA has announced the ‘Dynamic Audit Solution Initiative’, promising to create a new, innovative process for auditing using technology.

Auditors who stick with the traditional audit approach for fear of change are going to be left behind.

If you’re ready to implement a tech-driven audit approach using AI auditing software, know that the partner you choose can make all the difference. At MindBridge, we support our clients through the technology adoption process and offer value-add services that help you reach company-wide success.

Want to hear about what it’s like transitioning to a tech-driven audit approach? Read how Dixon Hughes Goodman LLP (DHG) embraces the power of AI to move their auditing practices forward.

Simplifying remote audit using AI auditing software

AI for remote auditing

The explosion of remote work is one of the biggest shifts to come out of the COVID-19 pandemic. Social distancing rules and concerns of employee safety have forced many to settle into working from home. But what does that mean for the future of remote audit, and for the auditing software that makes it possible?

For accounting firms specifically, the necessary distance created by COVID-19 has meant a major increase in remote auditsWhile the process of embracing remote audits hasn’t exactly been easy for accounting firms, many are now turning to artificial intelligence (AI) to automate data assessment and analytics to retain the quality of their audits, while making remote work simpler and more efficient. Below, we’re exploring some of the challenges of remote auditing and how using AI in remote audits can be a game-changer.

Accountants weren’t prepared for sharp increase in remote audits

In the world of COVID and social distancing restrictions, the typical site visits that take place during audits have been put on hold. What was once a routine process of going into the field to comb through financial data, speak with key employees, check internal controls, and handle other in-person tasks has all been diverted online. 

The problem is that many accountants weren’t prepared for this shift. A recent survey by IMA and Deloitte, which polled over 800 finance and accounting managers, showed that 75.7% of respondents said their company’s accounting processes are either largely manual or are still a considerable manual effort. 

Because of this, the majority of auditors working remotely are facing big challenges. For one, figuring out how to securely access a company’s financial data is not always straightforward. Companies today are acutely concerned about cybersecurity risks and adhering to data and privacy protection regulations. To successfully handle remote audit engagements, accountants must choose solutions and tools that are fully hardened and meet cybersecurity best practices. 

Fraud is on the rise during the COVID-19 pandemic

Even with secure access to general and sub-ledgers as well as other information, detecting risks across financial data has become harder. The fact is, fraud is on the rise as a result of this pandemic. Not only are companies under a lot of pressure to minimize loss and meet fiscal projections, but it’s extremely difficult to monitor internal controls when key employees are working from home. 

For instance, an article in Accounting Today titled ‘The craziest work-from-home expenses of 2020’ shows just how outlandish some fraudsters have been with expense claims during COVID-19. Everything from a $7,600 facelift which was listed under ‘Repairs and Maintenance’ to €200 worth of tea which was credited as an ongoing company perk is being flagged. For every instance of fraud that is caught, another illegitimate expense could easily slip through the cracks. 

To help counteract these new work-from-home challenges, 40% of respondents in the IMA and Deloitte report said that they’ll be implementing more automated tools in the future. Uniquely, just over 20% of those respondents are focusing on AI. That’s because whether in an office or at home, accountants can use AI auditing technology to strengthen remote audits and simplify everything from building an audit plan to identifying and assessing risks. 

5 ways AI auditing technology enhances a remote audit

Why AI auditing technology enhances a remote audit
  • Increase fraud and risk detection with AI-powered insights – With fraud on the rise, accountants must be hypervigilant when combing through all financial data. Truly AI-embedded auditing software helps auditors run multiple algorithms across all client transactions simultaneously and cross-correlate data using dozens of testing criteria. Auditors can then effectively identify all potential risks or fraud within the financial data and negate the weakening effects that work-at-home situations have had on internal controls. By taking this data-first approach, auditors can also detect anomalies such as rare monetary flows and unique account activity which can be difficult, if not near impossible to anticipate or test manually. Working remotely with AI auditing technology essentially enables auditors to get a better understanding of risks across a client’s financial data.They can then focus on delivering quality assessments and audits and offer their clients more data-driven value.  
  • Be better prepared to ask the right questions – With AI auditing software, accountants can become more effective at identifying real risks and anomalies versus a firm’s typical transactions. They can then direct resources to investigate those potential red flags and become better prepared when conducting interviews or gathering more information from clients. Honing in on riskier transactions and asking the right questions helps to enhance the accuracy of remote audits and ensures auditors deliver strong financial insights to their clients.
  • Build a more comprehensive audit plan An AI platform will rank transactions based on risk level. The MindBridge risk discovery platform also gives accountants an intuitive visualization dashboard that shows a holistic view of a client’s financial transactions from month to month. This makes it easier for auditors to spot risks during remote audits and dive deeper into the data that stands out based on their professional judgment. These risk-based AI rankings also help to confirm an auditor’s own risk assessments and build a more comprehensive plan for the remote audit engagement

Learn more about how MindBridge can help you sample less, and discover more.

  • Work with a secure cloud platform to access financial dataChoosing secure cloud-based AI auditing software can make all the difference in remote audits. Not only is it easy to upload and share financial data from various accounting software platforms, but leading AI auditing providers will offer solutions with built-in cybersecurity features and SOC 2 Type 2 compliance certifications. Sharing these details with customers before remote audit engagements can help ease cybersecurity concerns. 
  • Get hands-on support for data ingestion and analysisWorking with new technologies to facilitate remote audit engagements can be overwhelming to some firms. Having hands-on support from solution experts can help ease the transition. Both auditors and their clients will feel confident knowing they have support at the ready should they have questions or need guidance. This support also ensures they get the most value from the AI auditing software. 

Thinking long-term about AI for remote audit

As accounting firms everywhere navigate the challenges of remote audits,  groundbreaking auditing technologies  are just some of the tools helping them identify financial gaps and ensure quality assessments. And though work-at-home mandates may not last forever, the benefits of AI technology can. Accounting firms that choose to leverage AI technology for remote audits today will continue to see returns on this technological investment well after this pandemic subsides. 

Are you wondering how to work new technologies into your existing audit process or what other benefits they can offer? Check out our article, “Should you update your audit methodology?

Ready to embrace AI to strengthen your remote audit?

Contact our team to schedule a demo of the MindBridge risk discovery platform.