Will the AICPA announcing the DAS, or dynamic audit solution, work?

Well, it depends.

When you look at the state auditing software in 2015, not much had changed in the past 30 years. It was the same companies creating the same type of software. Working papers, engagement management, time management, things like that. Yes, “paper” in the title of a software. That should give you an idea of the state of the industry. Don’t get me wrong, this has served the industry well, but they were created in an age where the internet did not exist and most bookkeeping software fit on a desktop running windows.

I used to work in one of these three incumbent software companies, Wolter Kluwers, which alongside Thomson Reuters and Caseware have dominated the accounting industry. There is nothing wrong with large multi billion dollar companies making healthy profits. But, as most of us know, the problem is that innovating becomes a problem as ancient processes and massive user bases need to be served.

As the Big Four started to make major investments in various emerging technologies, many of the large accounting firms in the USA started to get nervous. They asked the AICPA to try to come up with a joint effort together. Their goal was to automate the checklist and analytics into an updated methodology, and that is exactly what they are doing now. The profession committed to investing tens of millions of dollars into the initiative.

Now, the collaboration between the AICPA and some of the USA’s largest firms will be released at some point next year.

During the foundational months of MindBridge, we approached the standards committee of the AICPA to explain our vision: why better data driven audit technology is poised to change the world of finance. It had to be AI first, not committees and standards first. It would be driven by market needs, and, most importantly, would be a faster approach.

After 3 years and with hundreds of firms using Mindbridge, I firmly believe that this was the right decision. The reason is quite simple: people don’t move fast enough.

The standards and the best audit methodology in the world is created by a select group of people making assumptions by a committee to follow a checklist based approach. They don’t have the ability to scan and know at scale all what happens in the dataset in industry. They will be able to never keep up with artificial intelligence driving the changes. There is a big difference between a standard set by a professional body, the law, and the reality on the ground.

If Elon Musk had to wait for the auto industry standards committee or for lawmakers to make the transition to an electric transportation future a reality today, it would have never happened. The conflict of interest and simple orthodoxy prevents it. Even for the most basic proven safety technologies such as anti-brake systems, there was a huge delay. The first commercially successful ABS system was put in Concorde airplanes landing at high speed in the 1970’s, and massively adopted in commercial cars in the 90’s only to be adopted as a standard in the 21st century, decades later. In the meantime, countless cases such as Enron, Wirecard, Worldcom, Luckin Coffee, and Carillon have highlighted the lack of audit effectiveness in preventing cases of fraud. Same as how the adoption of the ABS was driven by casualties and lawsuits.

This is the very same mentality that led to the adoption of the ABS system. Casualties and lawsuits drove change, while the writing was all over the wall.

As the AICPA was not ready at the time, I chose to raise money from Silicon Valley and NYC without taxing the profession. Our investors from both of these locales push us as an organization to perform at the highest level, with sound governance and to focus on tangible outcomes. 4 years later, MindBridge continues to work with leading firms that benefit from our technology every day. I can’t wait to see how we will compare to CPA.com’s product.

I’m also excited to see what the Dynamic Audit Solution from the AICPA has in store, and how it differs from what Wolter Kluwers and Thomson Reuters have already produced as part of their new cloud offerings. As MindBridge was recognized as a pioneer in this space, I find it crucial and useful to have large organizations such as these join in our view that AI matters today, and for the future of auditing. This will help give our solution support in a sea of traditional methodologies.

The President of the AICPA, Barry Melanchon, and CPA.com have shown leadership in this space with a consortium approach to try something new. For this, we need to give them credit. Although, the critics would say that there was no need to tax the profession. Also, given the amount of issues around algorithmic discrimination and peer review, I’d be curious to see if they subscribed to the Algorithmic Impact Assessments and peer reviews we do as a registered ai vendor.

This announcement is already having a positive effect on the industry, including reactions from Thomson Reuters and Wolter Kluwers, who have both committed to updating their software and tech stacks. The goal, as announced, will be to include artificial intelligence and machine learning into their once manual and outdated processes.

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, the need for as many initiatives as the Dynamic Audit Solution as possible, no matter if they have the best algorithms or not, is better than the status quo.

Ultimately it’s up to the Wolter Kluwers, Thomson Reuters, Dynamic Audit Solution, MindBridge, and other organizations in our space to drive technological change for the betterment of finance, the accounting industry, and, of course, our clients.

Will the Dynamic Audit Solution work? was originally published in AuditScience on Medium, where people are continuing the conversation by highlighting and responding to this story.

When it comes specifically to journal entry testing, most auditors today have been using antiquated approaches and sampling techniques. Many justify the use of these limited audit risk methods by saying they comply with existing standards. But these standards such as SAS 99, Consideration of Fraud, actually only require auditors to gain an understanding of the business and focus on identifying items that warrant further auditor considerations.

According to SAS 99 or other international standards, there is nothing to discredit the use of advanced methodology and latest AI-powered technologies. In fact, almost 20 years ago, the American Institute of CPAs published the 2003–02 Practice Alert with guidance for the use of analytics. Today, recent advancements in auditing software allow accountants to better evaluate audit risks and deliver pertinent insights to various stakeholders.

The challenges with traditional journal entry testing

Traditionally, accountants had a lot of groundwork to do during an audit risk assessment. First, they would spend a considerable amount of time doing data preparation on usually limited data columns and file sizes. Then, they would try to determine which analytics to apply to the data.

As Enterprise resource planning (ERP) systems grow more complex, not all audit procedures can keep up. Data clipping or manually converting a GL report into an Excel file is known to exclude data or cause errors during the audit process.

Existing script-based data analytics engines are exclusionary based, meaning they extract data as an auditor applies various procedures. This decreases the chance of detecting anomalies and doesn’t allow for a truly comprehensive audit risk assessment. This is why many leading accounting firms, including the Big Four, are moving away from these outdated auditing procedures. These more traditional methods for risk-based journal entry testing cause inherent liability and poor quality.

Using more advanced AI-powered auditing software, an audit team can gain more far-reaching insight. By pinpointing control points, the AI auditing software can identify and learn what’s normal or not and then analyze a wider range of data without inherent exclusions.

3 ways to automate risk-based journal entry testing

1. Start with a data-first approach

Before thinking about which audit tests or procedures to apply, you need to start with the data. This is called a bottom-up approach to audit risk assessment, instead of top-down. The idea is to let the data speak first. Then, you can look for standard procedures and identify any underlying risks.

Seek to get as much information on the system available as possible from your client: GL reports, Charts of Accounts, opening and closing balances, bank statements, as well as the previous year’s data.

With this modern approach, you can leverage historical data in new ways. This can include automatically doing pre-emptive calculations and forecasts to better understand potential audit risks.

For example, MindBridge Ai Auditor automatically generates ratios and forecasts that you can annotate and add to your audit plan, seamlessly.

2. Leverage the community effect

Try to avoid reinventing the wheel and be curious of what automation can accomplish. It is not just about using new auditing technology. Try to understand the definition of risk that is built into the automation. A few AI or cloud accounting software vendors like MindBridge have spent countless hours with industry partners embedding specific risk analysis into their software packages.

Auditors are required to “test the appropriateness of journal entries recorded in the general ledger and other adjustments”. In the past, you would have had to define the procedures yourself. But today, with everyone connected online, communities have emerged around your choice of tools. These communities include other accountants that might have implemented fully automated procedures into their methodology and are eager to contribute best practices and tips with others.

During the Influence 2020 conference, some MindBridge Ai Auditor customers such as Baldwin CPAs and GRF CPAs shared their first-hand experience of using our AI accounting software as well as practical advice for other users.

3. Pay attention to complex transactions

Your clients are not in the business of ensuring the right controls or worrying about anything else other than running their business. They simply don’t anticipate bad behavior, bad actors, or white-collar criminals. It is not enough to just design procedures or automate the classic CAATs-style audit tests. Instead, you can leverage the full power of advanced audit risk assessment techniques such as “Rare Flows” and “Expert score” using powerful AI auditing software. These improve your ability to detect high-risk transactions or the sidestepping of the company’s internal controls.

Some employees, including senior management learn ways to work around a specific control. For example, employees can post numerous smaller journal entries to various departmental general ledgers to circumvent approval processes. This also makes it more difficult for auditors to detect the fraud.

This is where AI can excel and really help you. Rare flows and unusual transaction analysis can help you quickly identify audit risks and conduct a more thorough journal entry testing. After saving time on the previous tasks, you will be able to dig into the data and ask the right questions.

Evolving audit risk assessments and your business

Accountants and auditors are not here just to perform repetitive tasks or follow outdated procedures. The core principle of the profession is to be business advisors to their clients.

By using advanced technology for risk-based journal entry testing, auditors can streamline the auditing process and avoid spending billable hours digging for issues in only one area. Instead of limiting themselves to simply extracting data from a general ledger, they can ask for more reports and more data. This allows them to get a deeper understanding of all the anomalies in client files to perform a more thorough audit risk assessment.

With greater automation in journal entry testing, auditors will be able to get more insights from a larger dataset in minutes, and their clients will notice. That’s because after using AI accounting software in the auditing process, the audit team will be able to ask more relevant questions that lead to smarter business outcomes.

Want to learn more about the benefits of AI auditing software? Read how one of the largest CPA firm in the USA, K·Coe Isom embraces AI accounting technology to gain new insights into their clients’ businesses.

A better approach to journal entry testing: Audit analytics automation with Artificial Intelligence was originally published in AuditScience on Medium, where people are continuing the conversation by highlighting and responding to this story.

White-collar workers who are part of the knowledge economy are beginning to experience what manual labourers have in the past when new technology made their jobs obsolete. Given the improvements we have recently seen in computing, many professionals fear for their future as machines threaten to overtake them.

Rather than fear changes that machine learning will have on accounting tasks, it’s an opportunity for accounting professionals to be excited. The profession is going to become more interesting as repetitive tasks shift to machines. There will be changes, but those changes won’t completely eliminate the need for human accountants, they will just alter their contributions.

It will propel innovation in accounting when accounting software companies eliminated desktop support in favor of cloud-based services, accounting firms were forced to adapt to life in the cloud. Similarly, accounting departments and firms will be forced to adopt machine learning to remain competitive since machines can deliver real-time insights, enhance decision making and catapult efficiency.

Accounting tasks that machines can learn to do

Rather than eliminate the human workforce in accounting firms, the humans will have new colleagues — machines — who will pair with them to provide more efficient and effective services to clients. Currently, there is no machine replacement for the emotional intelligence requirements of accounting work, but machines can learn to perform redundant, repeatable and oftentimes extremely time-consuming tasks. Here are some of the possibilities:

1. Auditing
2. Clear invoice payments
3. Risk assessment
4. Analytics calculation
5. Siri-type interface for business finance:
6. Automated invoice categorization:
7. Bank reconciliation

It is high time for every accountant to reflect on their job, identify the opportunities machine learning could offer to them, and focus less on the tasks that can be automated and more on those inherently human aspects of their jobs.

The future of accounting with Artificial Intelligence was originally published in AuditScience on Medium, where people are continuing the conversation by highlighting and responding to this story.

As I was walking downtown Manhattan on a rainy March day, that also happened to coincide with the 2nd anniversary of MindBridge AI, a sad and chilling reminder of why we started MindBridge stared at me in the face.

Charles Murphy, a Partner that once worked for a Bernie Madoff feeder fund had committed suicide by jumping off the Sofitel in NYC — 9 years after the unravellings had begun. I instantaneously had tears in my eyes.

On a personal side, my family was decimated over two generations by a large case of fraud by an accountant. I was myself the victim of fraud and corruption — twice! One of my first memories was when I was 3 years old and the Brazilian police pointed a rifle at me and my mother as they said to my father “You pay, or they go”.

In the Madoff scheme, $65B was stolen and millions of victims were impacted. Charles Murphy had decided to put an end to his life, leaving a wife and 4 children behind. Over my career I had seen and helped countless compliance professionals working on many cases, many unheard but as devastating to families and too often, human life.

As professionals, we often talk about “accounting errors” and “governance issues” as if it’s just part of the new normal of business, but let’s not forget that financial crimes are real crimes. It’s surging to the point large national databases of financial criminals similar to the sex-offender registry list are being created. There are countless more stories of suicides, depressions, and lives that have been impacted by financial scandals ranging from Madoff to a small business owner that was forced to close his 15-man shop because an employee had gone rogue and he can no longer meet payroll. The lack of trust by individuals towards corporations and governments has become a sad reality and a reflection of how low we have fallen as a civil society.

In an era of alternative facts, fake news, inflated books and huge amounts of data, we decided that AI is needed as humans alone can not check all the facts. A recent article from Harvard Business Review suggested that professionals have “failed” and technology will take over their job. We believe that it is not that simple. Corporations and governments are acting within a specific regulatory framework and if that framework is obsolete, who should we blame? Let’s not forget that Rome did not fall because it had bad armies, or suffered from a poor economy. It fell because of corruption by all individuals at various levels of its civil society.

All members of the MindBridge AI team are driven by making the world a better place. From our CEO, who in addition to being a successful serial entrepreneur, has led the largest corporate responsibility conference in North America, all the way through to our data scientist, development, marketing, sales and administrative teams, we stand for the world being fixed.We firmly believe that Artificial Intelligence will augment human cognitive capabilities to compensate for the increasing demands placed on professionals.

Two years after starting MindBridge AI, we have spent countless hours with executives, accountants, bankers, lawyers and fraud fighters and there is still so much work ahead to make a positive societal impact. What we did not anticipate is that containing fraud and restoring trust is just the beginning of increase in productivity and the key to unlocking substantial value for our customers. Fraud is often the canary in the coal mine. If you have a case of fraud, it is typically foreshadowed by breakdowns in process and management. Fraud is often enabled by circumstances relating to management issues, poor system controls, a toxic culture and inadequate hiring practices. By unleashing an AI expert system that is capable of detecting 80% to 170% more issues in data than existing methods and softwares, our customers led us down a path to introduce solutions that were beyond our original direction. World class partners have said that the MindBridge AI platform goes “well beyond the capabilities of any data analytics technology we’ve seen”. One of our coolest projects (so far!) was associated with MindBridge’s acceptance into the Bank of England FinTech program.

The analytic capabilities of countless finance professionals are severely limited, and by default they have been forced to use aging tools. Today’s professionals spend countless hours in visualization, data acquisition and analytics softwares that creates more work and generates analyst fatigue. MindBridge’s goal is to invert this trend, and have the computing work for the humans, not the other way around

This is why MindBridge introduced the world’s first commercial AI Auditor at the end of 2016. We wanted to provide professionals with an easy way to perform their financial data analysis more efficiently, with higher assurance and in a consistent, reliable, unbiased manner by harnessing the power of artificial intelligence. By doing so, we can minimize the risk of financial loss, and ultimately restore trust in corporations and governments — and help prevent the tragic impacts of fraud that society has experienced. The market so reaction has been fantastic, we are being featured by various press outlets in Europe and North America, partnered with existing software providers and I am filled with confidence that it’s a matter of time before we see the benefits of this technology on a very large scale.

See the links below for the news coverage following the announcement of a recent round of funding:

Bank Of England and MindBridge Ai Collaboration

https://globenewswire.com/news-release/2017/04/03/953688/0/en/Bank-of-England-announces-collaboration-with-MindBridge-AI.html

Thomson Reuters Announcement

https://www.thomsonreuters.com/en/press-releases/2017/may/thomson-reuters-tax-accounting-reaches-agreement-with-mindbridge-analytics-inc.html

Globe and Mail Feature, 16 June 2017

https://www.theglobeandmail.com/report-on-business/international-business/ottawa-ai-firm-training-machines-to-blow-whistle-on-fraudsters-poised-for-breakout/article35325475/

National Post, 19 June 2017 (the digital version will be available in a couple of days)

http://business.financialpost.com/entrepreneur/0619-biz-dd-ottawa/wcm/3e35358c-6ac5-46d9-8401-751fa115364b

Betakit

www.betakit.com/mindbridge-raises-4–3-million-with-goal-to-ipo-within-five-years

Why MindBridge. was originally published in AuditScience on Medium, where people are continuing the conversation by highlighting and responding to this story.