Simplifying remote audit using AI auditing software

September 21, 2024March 26, 2021 by Solon Angel

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 audits. While 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

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 data – Choosing 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 analysis – Working 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.

Should you update your audit methodology?

May 26, 2022March 23, 2021 by John Colthart

Does your audit methodology need a facelift?

When most people think of an auditor, they picture someone working away on a calculator with a gigantic stack of paper beside them. Invoices, transactional documents, payroll documents, let your imagination run wild. The point is, there’s always a stack of paper, albeit some have started to become digital in form. But, what if an updated audit methodology and audit process could change that?

But just because something was popular once, definitely doesn’t mean that it’s the best way to go about things. Take Pet Rocks for example. Tell me with a straight face that Pet Rocks were a good idea.

Audit best practices and compliance are constantly evolving, especially as data sets increase, remote audits become more prevalent and regulators/standard setters look for more analytically driven procedures. This also means that maintaining SALY (Same as Last Year) will challenge firms in staying relevant to their clients, risk of client acquisition or retention, and have peer reviews/inspections/audits scrutinized more thoroughly. To continue to offer clients top quality audits and risk assessments, add new value to their clients and win more business, auditors should routinely evaluate their audit methodology and process.

Here are just a few points to keep in mind if you’re on the fence about updating your audit process.

Audit evidence standards are modernized

Now is the best time to work on new engagement models, modernization and change. Sure it can be hard, we hear you, but the reality is that the industry has moved, and it’s to be expected that firms and individual auditors will need to keep up.

The American Institute of CPAs (AICPA) recognized that fact when it released the Statement on Auditing Standards (SAS) No. 142 Audit Evidence in July 2020. The new audit evidence standard, which takes effect for financial periods ending on or after December 15, 2022, modernizes private company auditing standards and includes significant updates around how technology and automation can be leveraged throughout the audit process.

“Our substantially revised standard addresses the evaluation of audit evidence and has been modernized to reflect our current business environment,” explained Bob Dohrer, CPA, CGMA, AICPA Chief Auditor, in a press release. “It recognizes the use of automated tools and techniques such as audit data analytics, AI, and remote observation tools to obtain audit evidence.”

With so much of the audit process tightly wrapped up in regulation, this new standard represents a huge step toward the future of the audit industry and acknowledges the ever-evolving nature of business.

For more detailed information on this new standard and what it means for your business, check out our blog, “How the new SAS-142 audit evidence standard embraces technology and automation.”

AI won’t replace auditors

When it comes to implementing new technology into your audit methodology, you might be thinking, ‘But what about my team?’

Since the dawn of technology, there has been apprehension about robots and machines replacing jobs done by humans. But here’s the thing: artificial intelligence will not replace auditors, but auditors using AI will replace those who are not using it. In fact, data science can augment an auditor’s experience and judgement.

Now, there is reasonable concern around AI’s ability to conduct an effective audit, and whether or not regulators are going to embrace these technologies as sources of high quality risk assessment and evaluation. But, as the revised ISA 315 audit standard shows, regulators are inching closer to the adoption of industry-changing technological changes, such as integrating data analytics into the formal audit process.

It’s safe to say that accounting and audit firms that embrace new technologies will dominate the market. The bottom line is that AI is about task replacement, not human replacement.

Want to learn more about how auditors are using AI?

The continuing implications of COVID-19

Before the global COVID-19 crisis, technology and automation were already on their way to becoming the future audit process norm.

However, the global pandemic underscored the need for the audit industry to more readily utilize new technologies. COVID-19 made change unavoidable and advanced the future of auditing and disrupted a long-standing complacency that had settled over the audit industry

While the pandemic may be temporary, many of the changes it has brought will be permanent.

There’s no question that COVID-19 has transformed how many firms will work and collaborate going forward. Since more teams are working remotely, a cloud-based AI auditing platform can simplify data sharing and ensure cybersecurity best practices are in place for the new norm of remote audits.

With AI-embedded auditing tools like MindBridge, customers can experience a more streamlined and integrated audit and risk discovery process.

It’s also important to keep in mind that just as your team is working remotely nowadays, so too are your clients’ teams. Providing a remote-friendly audit approach means your firm will be more relevant to current and potential clients, which, in turn, gives your firm a competitive advantage.

An updated audit methodology can add value for clients

Businesses have traditionally seen audits as simply a compliance exercise, and that auditors merely verify if financial statements comply with standards, and find out whether or not their transactions look risky.

However, that perception is changing, and clients are now expecting more services than a calculator and Excel spreadsheet can offer.

Financial technology and automation have given rise to a component that’s changing the audit field: insights. AI-embedded audit tools allow for detailed risk assessments and insights, which provide added value to a client and result in higher quality audits altogether.

The future of auditing will have a heightened emphasis on exploring data trends, studying risk characteristics, and real-time transaction analysis. With these capabilities, auditors can gain a deeper understanding of their clients’ financials. At the same time, clients have greater confidence in the audit process.

When it comes to audits, clients now want more than a rear-view mirror perspective. They want to know what to keep an eye out for.

That’s why diversifying your firm’s offerings will be fundamental to longevity and growth in the future world of audit. Adopting an AI-embedded risk discovery and audit procedures not only makes audits more effective and efficient, but also allows for expansion into advisory and transaction services. Modifying and diversifying services adds incredible value for clients and can lead to a more regular income stream for firms, not to mention smoothing your delivery timing and ridding teams of rote and menial tasks.

Embracing change in your audit methodology

Let’s be honest, not everyone embraces change. It can be intimidating; it’s new and unknown. It can take a lot of effort and planning to put something new into action. But more often than not, change is beneficial.

Evolving and implementing new practices is an essential part of doing business today. It’s safe to say that a retail business that doesn’t utilize technology to have an online presence would most likely fail in the marketplace today (let alone tomorrow).

Of course, updating your audit methodology doesn’t happen overnight. It can be a long and tedious process that may even require some research on change management best practices. An important aspect of changing your audit methodology is finding an approach that’s right for your team.

At MindBridge, we can help you develop your new audit process that meets both your needs and the needs of our clients. While there are many unknowns about the future of audit, one thing is for certain: AI will be a part of it.

Want to learn more about how AI is reshaping the audit industry? Register for our on-demand webinar “Demystifying artificial intelligence and the impact on auditing.”

Financial automation: The good, the bad, and the future

September 22, 2024March 18, 2021 by Benjamin Wyrick

Well, it’s finally here. According to an article from Forbes Magazine, we have reached the age of automation. From AI and machine learning to financial automation and robotics, we’re officially an automatic civilization. Please, be kind to our new robot co-workers.

Okay seriously, this is important stuff, even if we did all see it coming. Especially when it comes to the ever-expanding world of finance.

In every industry, every business, and every firm, finances and how they are managed are vital to the growth and development of a company. Whether you’re a business owner, CFO, or part of the finance department, the role of automation in the future of finance is vital to your role, growth, and the evolution of your organization.

Financial automation doesn’t just mean automating payroll, although it doesn’t hurt to do that as well. Automating financial processes incorporates much more, including risk assessment, audit, and compliance among many other aspects.

An article from DigitalistMag outlines the capabilities of today’s financial automation services, describing the ability to “gain new insights from existing data to optimize credit decisions and improve financial risk management, automating business processes that previously required manual human intervention, and improving the customer experience.”

Financial management has evolved rapidly since the advent of computational technology. As this technology evolved, financial experts and professionals soon recognized that process standardization and centralization are absolutely necessary to increase the efficiency and effectiveness of modern organizations. As efficiency grew into a central tenant of management processes, financial automation became the next logical step for businesses and organizations.

In 2016, McKinsey estimated that 60% of all occupations have approximately 30% or more capabilities that can be automated with existing technology. Moreover, there has been a significant change in the understanding of what can be automated and what should be automated, which has become increasingly evident due to the unprecedented effect the COVID-19 pandemic has had on work.

For businesses looking to hire and outsource their financial processes or professionals who want to simplify and streamline internal processes, it may be time to look at automating them instead. For many, this has already begun, as “CFOs around the world heavily invest in financial automation software as a next step in the evolution to enable enterprise transformation.”

In this way, financial automation could lead to a complex or fundamental shift in how an organization’s core business is conducted.

Taking the first step toward financial automation can seem daunting. However, with more businesses adopting automation into their day-to-day financial practices, it’s clear to see the power this technology holds.

So, what exactly is financial automation?

What is financial automation?

For us mere mortals, financial automation can be as simple as automatically depositing your paycheck, paying bills, or saving a portion of your income per month. The concept is similar for businesses and corporations, but at a much larger scale, and with a lot more moving parts.

Financial automation is the process of utilizing technology options to complete tasks with minimal human intervention. These tasks would normally be accomplished by employees, which, in theory, frees up time for them to perform more complex tasks.

According to another automation study from the McKinsey Global Institute’s automation research, current in-use technologies can fully automate 42 percent of finance activities and mostly automate a further 19 percent.

While many still consider financial automation and intelligent software to be on the horizon, organizations have already started to utilize cutting-edge tools and technologies such as advanced analytics, process automation, robo-advisors, and self-learning programs. A lot more is still yet to come as technologies evolve, become more widely available, and are put to innovative uses.

Levels of automation

The initial forms of automation were (and still are) macros and scripts: simple rules-based automation that repeated simple work with highly structured data – things like general accounting operations, revenue management, and cash disbursement have an over 75% fully automatable ability with already existing technologies.

Robotic process automation (RPA)

RPA is the basis (above macros and scripts) to understand the capabilities of automation. An example of an RPA would be simple software that can perform repetitive tasks quickly with minimal effort, like some of the rote tasks mentioned earlier.

According to the 2017 McKinsey research (also mentioned earlier), about a third of the opportunity in finance can be captured using basic task-automation technologies such as these.

Artificial intelligence (AI) and intelligent automation (IA)

On the other end of the spectrum is artificial intelligence. Artificial intelligence is theoretically achieved when software is able to make intelligent decisions while still complying with controls using algorithms or machine learning.

Machine learning algorithms demonstrate the ability for computers to take in a constant stream of data, analyze that data for patterns and recommend solutions to problems humans can’t even see, proving vastly positive results in improving a company’s financial proficiency.

Once a dream for financial professionals and business owners, this form of financial automation software is becoming a reality, shaking up the way that tasks are performed, and even introducing other aspects such as forecasting into the mix.

Improvements with financial process automation

The umbrella of finance – from payroll to predictive forecasts can involve menial and repetitive tasks which leave limited time and resources to focus on value-adding activities to grow your organization. When financial process automation is added, it serves as a pivotal support to free up needed resources and time.

As these technologies can cover more ground and more deeply analyze company financials, many organizations are finding that AI and automation technologies are actively improving their bottom line. According to a survey from the Association of Certified Fraud Examiners via the Harvard Business Review, “organizations lose 5% of their revenue every year due to fraud. The typical fraud case causes a loss of $8,300 per month and lasts a full 14 months before detection. And lack of internal controls contributed to nearly one-third of all fraud cases.”

Risk discovery is just one aspect of financial automation, but a growing one.

As AI, RPA and IA continue to use machine learning to do more and perform more intricate tasks, offering insight into finances, we are seeing how this can be incorporated into an organization’s long-term organizational strategy. MindBridge, for example, has developed AI technology for risk discovery, a complex financial task that incorporates not only transactional analysis, but offers broader insights into financial health and integrity.

Want to learn more about how auditors are using AI?

By automating certain financial processes, “finance professionals can not only provide real-time insights into the current status of the business but, with advanced predictive algorithms, they can look into the future and proactively steer the business.”

Financial automation and its capabilities are excelling at a fast rate. With the help of AI, RPA, and IA, standard automation practices can be enriched beyond simple pre-programmed controls and scripts. From McKinsey & Company once again, AI algorithms can learn from historical datasets and the interactions of the financial professional with the system, thereby improving the matching rates tremendously. In this context, matching rates refer to the ability at which an AI system is able to tag users to certain data sets based on their profile of demonstrated usage. Furthermore, the AI technology allows automatic extraction of unstructured information from documents, such as emails.

Of course, return on investment is always a concern. It can take a lot of time and effort to implement new technologies, and savvy business leaders need to know that the tools and processes they put their money behind will work.

According to Gartner, “AI augmentation will create $2.9 trillion of business value and 6.2 billion hours of worker productivity globally.” Basically, they define this term as the combined work of humans and technology, with the people at the center of the operation.

Source: Gartner.

If these forecasts are correct, executives should be clamouring for AI and automation investment. Even a small piece of this pie can level up your office, department, or organization writ large.

What financial process automation could mean for work structure

One of the biggest concerns associated with exploring financial automation and therefore implementing financial automation software is what happens to the employees and the roles formerly associated with those finance objectives.

There’s no doubt that introducing financial automation will change the roles of many employees and even the manner to which employees are trained or progress toward career objectives. One thing is for sure though, automation will replace low-value, simple, and time-consuming tasks, thereby giving staff the flexibility to expand their roles, and spend more time on value-adding activities to help drive a company’s competitive advantage.

In an article from PWC on change management, they outline five steps that can help firms adopting financial automation make the transition as smooth as possible:

Prepare for human capital risks like you’d prepare for any other risks
Help people find their way
Create organizational support for success
Expect changes to jobs, compensations, and structure
Learn new ways to develop your team

To unlock financial automation’s full potential, managers must be willing to re-engineer processes, and redeploy resources to optimize efficiency and output.

Another consideration for anyone looking to adopt automation and AI technology is assurance and verification. This verification work ensures that the technology in place is doing what it’s supposed to do, at the level of work required to meet compliance requirements and quality assurance standards.

Internal teams can “test” automations by utilizing what are known as “Test Frameworks” for applications. Some examples of framework tools come from SmartBear and Selenium. However, it’s a lot of work, and unless you have dedicated developers that can help your team test automation tools, you’re sort of stuck. For many businesses, it’s much easier to work with platforms and tools that have done this testing themselves by utilizing a third party.

A future with financial automation

Although IA and machine-learning algorithms are still considered in their infancy, that doesn’t mean finance leaders should wait for them to mature fully. According to McKinsey, many automation platforms and providers that struggled a decade ago to survive the scrutiny of IT security reviews, are now well established, with the infrastructure, security, and governance to support enterprise programs. “Where a manager once had to wait for an overtasked IT team to configure a bot, today a finance person can often be trained to develop much of the RPA workflow.” The exponential growth in structured data fueled by enterprise resource planning (ERP) systems, combined with the declining cost of computing power, is unlocking new opportunities every day.

MindBridge is a great example of a pioneer in unlocking the expanded capabilities of AI and RPA within the finance sector. With AI-embedded risk discovery, MindBrige can risk-rate 100% of the transactions in general ledger and sub-ledgers to produce an aggregated risk profile of the data that makes up the business’ financial statements, facilitating laser-like focus on the areas that matter.

The future of financial automation seems bright, already beginning to reshape the way in which financial services are performed in organizations large and small. Incorporating AI, RPA, and other forms of automation can seem daunting at first, as there are many tasks and organizational changes that go into implementing new technologies and processes.

By empowering your finance team with AI co-workers, they reduce the time spent on mundane tasks, enabling your team’s human intelligence to shine operationally. Financial efficiency and accuracy means happy stakeholders, and a growing business. What’s not to love?

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Will DAS (the Dynamic Audit Solution) change the audit industry?

September 21, 2024February 5, 2021 by John Colthart

A paper boat on paper water, symbolizing whether or not programs like the AICPA Dynamic Audit Solution will hold water.

The audit industry has seen a bit of a shakeup in the past few years. New technologies, regulator crackdowns, big firms acquiring and merging, and a general push for improved processes and a review of age-old standards are all signs of new things on the horizon for our industry. But while there was a lot of talking, we didn’t see much walking.

But, all that changed, at least for auditors, with an announcement from the AICPA in 2018.

Nearly three years ago, the “Dynamic Audit Solution Initiative” was announced. Projected to release in 2021, the Dynamic Audit Solution, or “DAS,” as many in the industry affectionately call it, is a “multiyear initiative to create a new, innovative process for auditing using technology.”

As the beta release approaches, we wanted to take a look at the Dynamic Audit Solution in more detail. As a pioneer in AI-powered risk assessment, MindBridge is highly invested and interested in any and all innovations in our space. When it comes to DAS, we want to know what it is and what it means for us and our industry.

In this article, we’ll answer those questions and consider what the impact of a Dynamic Audit Solution might be, for better or for worse.

What is DAS (the Dynamic Audit Solution)?

We don’t know a lot about the Dynamic Audit Solution, but what we do know is exciting. The AICPA sees DAS as the next step toward the future of audit and assessment by leveraging technologies never before seen on a large scale. That, obviously, has a lot of people excited.

There aren’t a ton of details on what exactly the AICPA’s DAS will look like. We haven’t seen any product screenshots, and the core functionality hasn’t been mentioned in any major press coverage.

But, there are a few key aspects of the technology that have been announced, as well as some information on what the team behind the product are considering as they are building it.

AI, automation, data, and AICPA

At its core, the Dynamic Audit Solution will be an AI-powered product. In an interview with AccountingToday, Matt Dodds, CEO of CaseWare, one of the organizations involved in the project, made a point to note that “the solution is driven by data analytics and AI.” The idea here is that artificial intelligence capabilities will allow auditors to process more data more efficiently, allowing them to create higher quality audits in a fraction of the time.

It isn’t quite clear what areas of the audit solution will include artificial intelligence, or how the AICPA auditing standards will regulate and legitimize control points, risk assessments, and other key factors to a quality audit. But, the need for AI to process increasingly complex and large data sets is clearly at the top of the priority list for the AICPA. As are data analytics.

According to the AICPA, the Dynamic Audit Solution will require “audit professionals become conversant in data science, data integration and analytics.” Essentially, artificial intelligence and automation will allow auditors to become experts in the data that they spend so much time analyzing. Once that data has been processed, though, auditors will be able to better understand and communicate the results of an audit to clients.

As the traditionally manual tasks of an audit are automated, audit professionals will be afforded more time to converse with clients. This will allow auditors to offer clients a true assessment of the audit findings, while also expanding into a more continuous audit through advisory and consulting services, avoiding independence issues wherever possible.

All of that being said, what does the Dynamic Audit Solution mean for auditors themselves, and for the industry largely?

What does the release of DAS mean for the industry?

The Dynamic Audit Solution is going to mean different things to different people. For auditors, it means a potentially new technology to help them create more efficient and quality audits. In theory, that is. As well the automation of certain audit tasks will allow auditors to become data science professionals, consultants, and any range of financial experts to help their clients better understand their data and assist them in their endeavors.

But, such a large scale release of an AI-powered solution has industry-wide effects as well, which the AICPA have outlined.

Technology is considered to be one of the four “key drivers” of the DAS project, according to the AICPA. The other three are Methodology, Standards, and New Skills. Artificial intelligence is at the heart of the Technology driver, but is also the reason that the three other drivers are mentioned at all.

As the AICPA introductory document to DAS notes, audit methodologies, standards, and skills will need to be reevaluated and evolved to meet the demands of artificial intelligence. This means that, as an industry, we are potentially looking at a large-scale overhaul of the AICPA auditing standards, regulations, and methodologies that we’ve come to know over the past 100 years. In fact, some of these revisions are already in motion.

While it might be scary to some, this evolution was all but inevitable, hence the push by the AICPA to introduce DAS in the first place. In fact, in many parts of the world, organizations like the AICPA are being pressured to revise regulations and standards to meet the needs of today and tomorrow’s audit professionals.

While many have feared the advent of new technologies in the face of storied regulations and standards, large organizations like the AICPA are helping to fix that by entering a new age of tech-driven audits and accounting services.

The question is, can it be made to work?

The Dynamic Audit Solution: A new hope?

Everyone seems to have a different opinion on the Dynamic Audit Solution. Whether or not you think it will work depends on your perspective, and what outcomes you want to see from it. But, as the development process continues and feedback is given, ultimately, the Dynamic Audit Solution can be made to work, even if some of our fears come to fruition.

We’ve outlined what the AICPA and their collaborators hope to achieve with DAS, including automation of rote tasks, expansion of service offerings from auditors and firms, and a revision of AICPA auditing standards and methodologies. What these achievements mean for various auditors and firms will surely vary, so it’s hard to say whether or not the DAS will “work” for everyone, so let’s talk about whether or not it can achieve what the AICPA hopes it will.

The AICPA is an important and storied institution in our industry. It has been a stalwart of standards, regulations, and a representative for CPAs everywhere since its founding in 1887. But, that might be exactly the problem.

Old dog, new tricks?

While the Dynamic Audit Solution is a great sign of evolution in our industry, it’s a little late to the party.

MindBridge, along with many other innovators in the audit and accounting industry, have worked on this for a long time. We know the market, we know the challenges, and we know what it takes to create a robust product that services not only the auditors on the front lines, but the larger firms, businesses, and stakeholders that invest in technology.

We had a running start, while DAS is still at the starting line. We understand that agility and flexibility are necessary to address user needs, and delight our evolving industry with a tight feedback loop, among other considerations that come with time, practice, and experience.

Companies like MindBridge are ultimately closer to the needs of enterprises and stakeholders in the audit industry. These are the people pushing firms to do more with less, and produce more effective and high quality work with less resources. We understand the struggle in the market in a way that the AICPA and other organizations may not.

Part of the challenge will be to establish systems of review in order to meet the needs of an ever-evolving industry. The AICPA is a storied organization that may find it challenging to balance procedure with market need.

Even still, it may be even more difficult than that.

As a standard setter in the audit industry, the AICPA may find themselves in an awkward position with regulators and other standards enforcement agencies.

Audit Standards vs. Innovation

Comparatively, standards setters have been historically less agile than innovative and tech-forward firms. Large organizations have enough hurdles to jump over as is, without being the literal standard setter pushing back on these technological developments.

The AICPA’s involvement with regulators and imposing audit standards poses a unique challenge to the development, release, and review of a Dynamic Audit Solution. As they mention in their own Introductory Document for DAS, the AICPA anticipates an upheaval of standards and regulations that have inhibited the use of AI-powered technologies for audit in the past.

It will be interesting to see how a standard setter like the AICPA can build a tool and roll out their procedural recommendations at the same time. This brings to light questions around feedback and updates, and whether or not large organizations are flexible enough to meet the needs of our ever-evolving industry in a timely manner.

At the heart of this is the ability for tech firms to move quickly, update and adjust to new risk factors, changes to normal business processes, and therefore stay ahead of the standards curve.

Can the standard setter balance that need for speed and agility to enhance client satisfaction while also delivering on software changes needed for a dynamic business environment?

DAS will bring us a long way with standards that embrace technology. However, we will want to make sure that the AICPA focuses more on standards agility to help their members impact and delight the outcomes for the entities they audit.

We will have to wait and see what becomes of DAS in light of current or amended standards, but it’s more than valid to suspect that the industry-wide perspective shift may take some time.

DAS, and the future of audit

Ultimately, the AICPA’s investment in AI and data analytics, and the development of the Dynamic Audit Solution as a result, is exactly the type of thing our industry needs. Big players like the AICPA need to step up and embrace technology, and look to the future of audit and accounting more generally.

At MindBridge, innovations like these make us hopeful for the future of our industry, and have convinced us that we, and our peers in the industry, are having a marked impact on the present and future of audit and accounting.

As our Founder, Solon Angel, notes in his own article on the Dynamic Audit Solution:

“The bottom line is that artificial intelligence is being considered by all players, and this is something that I welcome with open arms. No matter how small or large the investment, every hour or dollar spent works to improve our industry. In light of recent fraud cases around the world, there is a clear need for as many initiatives as the Dynamic Audit Solution as possible, using different AI approaches is better than the status quo.”

We couldn’t agree more. We’re looking forward to the release of the Dynamic Audit Solution to make us better and challenge us to continually improve, evolve, and engage with our expanding client base. For more articles on the audit and accounting industry, visit our blog here.

MindBridge is performing tomorrow’s audits, today.

Find out how AI empowers the financial leaders of the future.

ISA 315 revised: What it means for risk assessment procedures, and data analytics

May 26, 2022January 19, 2021 by Rachel Kirkham

Two characters discuss the benefits of data analytics in light of ISA 315 revisions.

ISA 315 (revised) and Data Analytics: Risk assessment procedures reimagined

The revised standard has been published as of December 2020, and you might be wondering what impact it has on your firm’s risk assessment procedures and how you can address the requirements. There are many useful sources of information on the changes, notably the IAASB’s Introduction to ISA 315. IFAC also published a helpful flowchart for ISA 315 during the work programme, which walks through the various steps required to assess risk of material misstatement.

There are a number of improvements to the standard, including an enhanced focus on controls (particularly IT controls), stronger requirements on exercising professional scepticism and documentation, and considerations around the use of data analytics for risk assessment. The new standard comes into effect from 15th December 2021, so now is the time to start planning how you will address the changes in your audit. Below we discuss some key considerations on how analytics can support a strong risk assessment.

Credit: https://www.ifac.org/system/files/publications/files/IAASB-Introduction-to-ISA-315.pdf

So how can data analytics support your risk assessment according to ISA 315? The areas identified above in red show the different procedures that can be supported by the use of these techniques. A key element of the revised standard is that this should be an iterative process conducted throughout the audit. This means using data analytics tools that can be easily refreshed with the latest information will better support this requirement than more traditional approaches.

Identifying risks of material misstatement at the financial statement level

Data analytics can support the risk assessment procedures laid out in ISA 315 by analysing previous and current accounting data to the financial statement level. This allows the auditor to see the material balances in the accounts, and if machine learning is applied, where the concentration of risky transactions lies. This is where the knowledge gained in the blue boxes above can be brought to bear. Comparing understanding gained through observation to the data is a powerful way to sense check and identify areas for further investigation.

Identifying risks of material misstatement at the assertion level

Specific analyses can target assertion risks and show where there are particular problems with an assertion. To do so effectively, several different analytics tests can be applied and combined to develop a good indicator of an assertion risk, for example accuracy. These can then be applied in an automatic way to give the auditor the information needed for their risk assessment.

Determine significant classes of transactions, account balances or disclosures (COTABD)

Combining assertion analytics with the ability to profile similar transactions can help auditors identify significant classes of transactions or balances. Analytics can help to produce similarity scores, but also to identify sets of transactions that are unusual. This can indicate previously unknown business processes that may require a separate assessment of their control environment.

Assess inherent risk by assessing likelihood and magnitude

Following identification of risk, the audit can guide their assessment by understanding the level of unusualness. Data analytics can provide finer grain evaluations of risk rather than simply risky or not. This can help support assessments aligned with the spectrum of inherent risk as defined in the standard.

Assess control risk

Data analytics such as process mining or automated testing of segregation of duties can help to inform or test control risk. These analytics can provide more comfort around the controls risk assessment and help to identify deviations in the control environment that require further examination.

Material but not significant COTABD

Where COTABD has been determined as material but not significant, recurring analytics can ensure that this assessment remains valid. Anomaly detection methods can be particularly helpful here, allowing the auditor to regularly check that nothing unusual has occurred since the initial assessment was undertaken.

Next Steps: ISA 315 and Data Analytics

Audit methodologies will need to reflect the revised workflow, with particular emphasis on the iterative nature of the risk assessment and ensuring that auditors are prompted to exercise professional scepticism and document it at every stage. Data analytics can help to ensure that the information used to continuously conduct risk assessment is timely, appropriate and relevant.

These improvements to the standard will result in a stronger audit approach and an advancement towards industry adaption data and analytics technologies. With AI audit software, accountants and auditors can gain deeper insights into their client’s financial data, in less time. Overall, the audit software can increase the efficiency of their processes, so they can focus on delivering better results, in time for the ISA 315 (revised) December 15th, 2021 deadline.

Want to learn more about the benefits of AI auditing software? Read our article on “Assessing audit risk during engagements” to learn more.

Want to learn more about how auditors are using AI?

Digital auditing tools and AI in auditing practice: A conversation

May 26, 2022January 13, 2021 by Mike McLean

INTERVIEW WITH

Stephen McIntosh
Tax consultant, auditor, INTARIA AG

In July of 2020, MindBridge took another step in the journey to global expansion. Partnering with Regensburg-based startup, 5FSoftware, MindBridge’s software solution is now being distributed to firms in the German and Austrian markets.

This is a major development that will allow more firms to expose anomalies, intentional or not, during their annual financial statement audits as efficiently as possible.

We sat down with Stephen McIntosh, an auditor and tax consultant for Intaria AG in Munich. Intaria is the first firm in Germany to use MindBridge, and we wanted his perspective on the importance of AI for audits, and what the future of the industry holds.

Stephen sat down with Marco Bogendörfer, co-founder of 5FSoftware.

For more information on MindBridge’s partnership with 5FSoftware, check out our release here, or check out the full interview from 5FSoftware here.

Without further ado, enjoy this excerpt.

This interview has been translated into English from German.

Marco Bogendörfer: Let’s start with a look at the audit profession in general: How far have we come in the digital transformation of the auditing practice in Germany and Austria – and what impact does it currently have on existing processes in an annual audit?

Stephen McIntosh: That’s not easy to answer and depends crucially on which audit firm you look at. The Big Four have invested several billion euros in digital technologies for years now to create their own solutions. Of course, small and medium-sized audit firms do not have this financial strength.

Data such as requirement notification, order, receipt of goods or payment are still too often left unused during the annual audit.

But beyond that, in my opinion, it is a matter of fundamental affinity for digital solutions and a willingness to invest in the auditing practice or its management. If it is the case that firms possess this willingness, the digital transformation can and will continue to advance in medium-sized and smaller auditing firms as well.

Marco Bogendörfer: How can digital tools make audits more efficient and higher quality?

Stephen McIntosh: An increase in efficiency is usually achieved when digital audit tools can take over recurring tasks. When employees no longer have to manually print, envelope, send and evaluate balance confirmations, they can focus more on important issues.

With digital audit tools – the International Standards on Auditing (ISA) refer to them as Automated Tools and Techniques (ATT) – I can seamlessly analyze 100 percent of the business transactions of a fiscal year for specific anomalies. A human being would take far too long to do this. Increasing audit quality by using digital tools such as these is our top priority. We can review certain areas without any gaps, while in other areas digital audit tools enable us to take samples of even better quality, as we can consciously select items with a greater risk of error.

Marco Bogendörfer: Currently, what are the biggest obstacles or challenges for the widespread use of data analytics tools?

Stephen McIntosh: From a technical point of view, the biggest challenge is to get the data first and then to import it quickly and completely into the respective data analysis tool. There are simply so many different ERP or accounting systems that the process of exporting data is never the same and the information contained in each is very different.

Within the auditing practice, the auditing process must be adapted. The analyses must be used from the beginning of the audit planning and then until the end of the audit. Only then can the integration of the software lead to increased efficiency. However, this also requires that the audit teams have IT competence in addition to accounting and auditing knowledge. This in turn means that training is required for the employees concerned.

Marco Bogendörfer: How does MindBridge add value during a final audit?

Stephen McIntosh: In many ways. The first, very significant improvement compared to our previous tool is that MindBridge generates the balance sheet and profit and loss statement from the imported data. We can therefore immediately check the data received from the client for completeness and accuracy.

MindBridge carries out a risk assessment of all transactions in a fiscal year. For each individual transaction, the system is transparent in showing how it arrived at the risk assessment. In particular, the AI-based machine learning algorithms can identify those transactions that are unusual or conspicuous compared to all others.

We can immediately check the data received from the client for completeness and correctness with MindBridge.

Marco Bogendörfer: How can digital tools make audits more efficient and higher quality?

Marco Bogendörfer: Currently, what are the biggest obstacles or challenges for the widespread use of data analytics tools?

Marco Bogendörfer: How does MindBridge add value during a final audit?

We can immediately check the data received from the client for completeness and correctness with MindBridge.

Additional added value is provided by the visualization of financial results and the many possibilities to dive directly into the trends and ratios for further evaluation. These are very helpful for understanding account performance during the course of the year, and for discussing the causes of these developments with clients.

Marco Bogendörfer: How does MindBridge actually work for auditing practice and what kind of data sets can be analyzed with the help of MindBridge?

Stephen McIntosh: MindBridge analyzes all postings of a fiscal year at the general ledger level. For this purpose, we usually have our clients provide us with the “export tax audit”, formerly also called GdPdU data. MindBridge also offers the possibility of carrying out analyses for the subsidiary ledgers of debtors and creditors. We do not currently use these yet, as we are focusing on the introduction and use of the analyses at the general ledger level.

Marco Bogendörfer: How was the use of MindBridge in your office received by employees? Clients?

Stephen McIntosh: All employees who have seen MindBridge or its analyses were impressed by the visual presentations and the possibilities of evaluating and analyzing the existing data in greater depth. There is also great interest in seeing and questioning the risk assessment.

During an audit, I showed my client MindBridge and we looked at the higher risk transactions together. We also questioned why the AI-based algorithms classified these transactions as “high risk”. For all transactions, we were able to understand the “assessment” of the algorithms, even if in the end there was no booking error or even a fraud issue behind it. But first and foremost, it was all about identifying anomalies, so-called outliers, and that worked. My client took a very positive view of the software and also the use of the software during our audit.

Marco Bogendörfer: How can the audit evidence obtained through new technologies be documented appropriately?

Stephen McIntosh: Basically, there are no concrete regulations on how the use of the technologies, and the results and audit evidence obtained must be documented. As a result, it must be possible for a knowledgeable outside third party to understand what was done with which results and on what basis and what conclusions were drawn from them.

MindBridge, for example, provides a standard report that explains the analyses carried out by way of example, as well as graphically depicting the risk classification of all transactions and the risks per balance sheet and P&L item with the respective employees making book entries – and summarizing the quantitative analysis results per analysis (control point). This report can be supplemented with comments via editable text fields, so that the conclusions drawn in each case and/or the further audit procedures can be documented centrally in this report. In my opinion, this report is a good basis for documentation.

Marco Bogendörfer: What skills and mindset should auditors bring to the successful digitization of an annual audit?

Stephen McIntosh: They should be open to current digital developments, recognize the relevance of digital transformation in their own auditing practice and be willing to invest. It is also very helpful if auditors have a certain amount of knowledge about the basic nature and structure of the financial data to be analyzed.

They should be open to current digital developments, recognize the relevance of digital transformation in their own practice and be willing to invest.

We are in the middle of the nationwide implementation of MindBridge and the investments have been kept within reasonable limits. The intensive work on digitization regularly leads to further exciting topics and questions, so there are already other topics that I would like to tackle next.

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Want to learn more about how auditors are using AI?

Source: Gartner.

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AI, automation, data, and AICPA

What does the release of DAS mean for the industry?

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DAS, and the future of audit

MindBridge is performing tomorrow’s audits, today.

ISA 315 (revised) and Data Analytics: Risk assessment procedures reimagined

Want to learn more about how auditors are using AI?

INTERVIEW WITH

Want to learn about how to drive efficiency with data-driven audit planning?