Audit

What is your position and what do you teach at your University?

I am Ryan Teeter, I teach Accounting Information Systems in particular, as well as Auditing and Data Analytic at the University of Pittsburg. I am a Clinical Assistance Professor, that just means I am teaching a lot of courses and I am always looking for ways to incorporate technology into my class room and into the projects which I have my students do. A lot of the work we do are very hands on, most of it is what we call experience-based learning. It is focused on getting the students hands on using various accounting and auditing tools, overcoming any challenges with learning a particular tool, and gaining from that experience, to improve their understanding of accounting and auditing.

Which course did you pilot MindBridge Ai Auditor in, and how many students did you have in the class?

I piloted MindBridge in a graduate course on data analytics for accounting. The course is titled Accounting Data Analytics and is part of our Master of Accountancy program at the University of Pittsburgh. We had 28 students this semester and next semester we will be doubling the capacity, so we will have about 50 students participating next time.

It sounds like there is a lot of demand for this course, is it a competitive process to be accepted?

There is cut-off for this program, it is an elective course, there is a lot of demand for it. So that’s why we’ll be increasing capacity in the future forward.

What was your motivation to pilot MindBridge Ai Auditor?

In the Data Analytics course we spend about half of the course teaching fundamental data analytics topics, terminology and foundation. We’re talking about asking the right questions, going through and cleaning up data, data quality issues, particularly how it relates to an audit. We spend a few weeks on different types of models, from classifications to regression to clustering and profiling data and so forth. Next, we move to interpreting the results and generating visualizations for communicating the results of the data analysis to decision makers, management and leadership positions within organizations.

By the time we’ve moved through those fundamentals we have talked about topics like machine learning, different types of risk scores, we have talked about expert models and artificial intelligence. And then, the second half of the course we move into more domain specific topics. We spend a couple of weeks on audit analytics, management accounting analytics, financial statement analysis, and then in the auditing section we’re looking for something more than just the traditional CAATs, computer assisted audit techniques. So, we introduce students to things like double payment checking and fuzzy matching and some of the probabilistic models for outlier detection. By this point however I am really looking for ways to take that to the next level and find a convergence of those different technologies into one place.

I thought that MindBridge was particularly useful for illustrating the different topics we were talking about like Benford’s testing and outlier detection, but also for the concept of discovering the really risky items. So for the platform to set those risk scores, and make it apparent to the auditor as they go through and evaluate ledgers and journals, was an important discovery concept.

After having used MindBridge Ai Auditor in your curriculum, how was your overall experience?

The experience was really good. The software is pretty straightforward aside from some minor issues with importing and running the analytics, meaning just the time that it took to re-evaluate the ledger once we changed some of the risk score items. The students were very satisfied with the program, they liked that they were able to drill into the risky transactions and see exactly what caused some items to be flagged as a high or medium risk. The interface was fairly intuitive.

I would say the only negative is that it’s almost too simple in a sense, because it is so user friendly. You can see the risk scores and see what triggered the scores and then you’re a kind of done. I would like, from an illustrative perspective, to be able to go into a little more depth into the different analysis that are being performed, popping open the hood a little bit to see how this is all working. But otherwise, the students were very satisfied with it and they could see the applicable use of data analytics for the ledger in that particular case.

How was the feedback from your students?

Overwhelmingly the students found it to be eye-opening that they could examine what went into the risk scoring. They liked that they had the control to explore different aspects of the data if they wanted to, so if they wanted to focus more on outlier detection or zero in on individuals or keywords, that the platform enabled them to do so. They liked the flexibility that the platform offered. I think with the cases that were provided they had some clear-cut examples to examine, it would be really interesting to see what they could do with exploring data that was a little more ambitious.

What’s next for you and MindBridge Ai? Will you use Ai Auditor as part of your curriculum again?

I was very pleased with the MindBridge Ai presentations and the illustrative applications of the platform in my Data Analytics course. I really would like to extend it into my undergraduate Accounting Information Systems course as well. We talk about auditing, and audit analytics and risk a bit more in that course, at a basic level. Being able to have something that is straight forward and shows the different techniques while also piquing the undergraduates interest toward data analysis, risk scoring and applied statistics area that would be very useful.

I have a text book written with McGraw Hill on Data Analytics for Accounting which comes out in May. My expectation currently is to add supplement material that I would like to develop for future editions of the text book that may incorporate MindBridge Ai Auditor. It’s all still very preliminary, but for illustrative purposes it’s an  intuitive and wonderful example of applying data analytics in accounting.

The more things change, the more they stay the same (at least that is what my mom would say). This wisdom can only be partially applied to the world of auditing. With the explosive growth of (big) data, and with an ever more connected, globalized world, the manner in which we approach auditing must change, and it must change significantly. The roles and processes of auditing, and the people working in that area will remain the same, but the way we conduct audits will change to address these new realities.

The good news is that, armed with new technologies such as Machine Learning and Artificial Intelligence, auditors can be empowered to face these new challenges — while potentially delivering better assurances on the state of their client’s business, and providing more value-added services than ever before.

The purpose of this blog post is to look at the role of auditors and how it is changing in today’s new landscape.

Auditing is a process in which one party examines another party’s information to ensure that it is fairly stated (Loughran).

One of the core methodologies of the modern audit process is sampling, which draws conclusions about a data population by examining a subset of the data. The reason that sampling is relied upon is one of cost and time, it would simply be too expensive, or too time consuming to audit all of the data manually. There are inherent weaknesses to sampling however, as human bias and the possibility of erroneous decisions based on the conclusions resulting from the examination of only a sample of data, present real problems.

As my colleague Robin Grosset, CTO of MindBridge Ai once said, “Sampling is a coping mechanism for dealing with large data, because it is humanly not possible to examine each and every transaction.” The alternative is to examine all of the data, which can be onerous and not very practical.

The situation is further compounded by the explosive surge of big data. The International Data Corporation (IDC) says that the amount of information stored in the world’s IT systems is doubling about every two years. By the year 2020, the total amount of data will be enough to fill a stack of tablets that reaches from the earth to the moon 6.6 times.

How can I, as an auditor, possibly provide reasonable assurance that financial data is free from material irregularities, when faced with these new challenges introduced by big data?

You can fight fire with fire in this scenario. The ability to process big data is bolstered by recent technological advancements (i.e. microprocessors, internet, software) and now we can begin to leverage cutting edge technologies such as AI, to address these challenges. According to a report by Forbes, an auditor’s key role is to determine a company’s most significant threats, however traditionally auditors have devoted less than 25 percent of their time to risk analysis.

At MindBridge Ai, we recognized this challenge early on, and have developed a purpose-built platform for auditors to utilize machine learning and AI, along with more traditional methodologies such as business rules and statistical methodologies. Our Ai Auditor platform can ingest 100% of financial data and identify any anomalies. Thus, we improve the audit process by not just making it more complete, but by making it faster and more effective.

What does this mean to an auditor? It means an auditor can be more effective and efficient, while reducing their costs and providing greater insight and assurance to their clients. If any regulators have questions about how the audit sampling was conducted, you can simply point to the MindBridge Ai Auditor platform and show them the algorithms that were applied. An auditor in this scenario can now move up the value chain and become a true strategic business advisor to their clients.

For those auditors who do not embrace AI, their future will be more burdensome, and they will certainly be surpassed by their colleagues who are using AI to their advantage. Such is the cycle of innovation, where relics of the video rental and retail industries serve as a testament to the velocity at which antiquated approaches are being replaced by some more technologically sophisticated alternatives.

As I stated at the beginning, “The more things change, the more they stay the same.” In the case of auditors, we can see that role is more crucial today and the future than ever before. Due to the rapidly changing landscape however, of big data and a connected world, the only way to manage that complexity is with technologies such as AI. For those who do not embrace AI, they will be eventually replaced by those auditors that have embraced it. AI in auditing is here today and is making inroads faster than you may know!

An interview with Taryn Abate, Director, Audit & Assurance — Research, Guidance and Support, Chartered Professional Accountants of Canada

I recently met with Taryn Abate, Director, Audit & Assurance – Research, Guidance and Support at Chartered Professional Accountants of Canada (CPA Canada) at the Digital CPA conference.

This conference is hosted by CPA.com and the AICPA and attracts leaders within the industry who truly embrace the digital CPA era, so no doubt it made sense for MindBridge to attend.

Taryn is a thought leader in the CPA space and after completing her CA designation in 2009, has held key positions in firms like MNP LLP, the Institute of Chartered Professional Accountants (CPA) of Ontario, and now with CPA Canada.

I chatted with Taryn about her thoughts on the massive disruption occurring in the audit profession and how innovative technologies like Artificial Intelligence (AI) and blockchain can be leveraged for auditors to graduate towards more of an advisory role. Below is an excerpt from our discussion.

Solon: What did you like the most out of the last two days, out of all the conversations, vendors’ booths, and the work groups? If you had to come back home and say, “I spent two days with hundreds of CPAs and here’s how I feel about the profession,” what would you say?

Taryn: The keynotes from both days were a fantastic frame of reference for the conference and the profession.

Mark Randolph, Netflix co-founder, on the first day talked about innovation; the importance of having an idea, having a tolerance for risk, and having confidence and optimism in everything you do.

Barry Melancon, CEO of the American Institute of CPAs (AICPA), started off the second day by discussing the state of the profession. Technology’s impact on the auditing profession was a trend/theme throughout the conference, focusing on blockchain, AI and data analytics. It was pretty much in every session that I went to. I heard discussions on how practitioners are going to start to use these technologies. It was amazing to hear everyone embrace the idea that these technologies are here, and the fact that it is going to change how we audit and what we are auditing.

Solon: Of the discussions you had with people in the room, do you agree that everyone is more or less ready for innovation? Do you think they know where to start?

Taryn: We have a tiny segment of the bigger population here. These practitioners have accepted the idea of digital transformation and understand the benefits of the new technologies. But, not everyone in the business community has reached this stage. We’re on a journey here, and that’s why CPA Canada has identified audit as a strategic priority. We are working with stakeholders around the globe to understand current challenges facing the profession, identify future needs and explore how the profession must evolve to meet these challenges and opportunities.

CPA Canada and other organizations such as the AICPA are preparing guidance to help members and other stakeholders adapt to an ever-evolving operating environment. Stay tuned for upcoming publications on blockchain and AI and the implication of these technologies on the audit and assurance profession.

Solon: I have to say I’m very impressed with CPA Canada.

Taryn: Me too, and thank you. We are committed to helping our profession and members navigate this changing environment. Our goal is to ensure that our profession and members are well-positioned to take advantage of opportunities associated the evolving technologies. Stay tuned.

Solon: CPA Canada has a TV ad — the one about driving change with the CD player guy, and I loved it. I also saw a poster at the Billy Bishop Airport that asks, “Will machine learning replace human know-how?” and then says, “Ask a CPA.” I have to ask you about that one. Who had that idea?

Taryn: That’s from our current national brand campaign that asks tough and timely questions about the changing business landscape. I think it’s great. It catches your interest and makes you think about innovation and the future and what organizations need to do to stay relevant.

Canadian CPAs have a solid foundation of technical and enabling skills, and we see those skills becoming even more relevant in a world that is increasingly volatile, uncertain and complex.

That’s why preparing the profession for the future is a key focus at CPA Canada. It’s about understanding emerging technologies and utilizing the data, identifying trends and bringing insight into strategy development to help organizations achieve long-term success. As the pace of innovation increases and new technologies continue to spread, the disruption of business models and processes will require rapid adaptation.

Solon: That’s for sure. I was just flying back from a conference reassuring people that AI is not going to take their job away, and then I see that ad…

Taryn: You see an article one day that says AI or blockchain is going to replace audit, completely replace 88% of jobs. Then last week, Forbes produces an article saying in four out of five companies, AI will create new jobs.

We need to reinforce that with technology comes change but that can include opportunities. This is again why helping our members and other stakeholders prepare for the future is so important to CPA Canada.

Solon: I think there are a lot more job opportunities. That is my company MindBridge’s view and vision too. We believe there is going to be a surge of demand that will be for more digitalized solutions that will be easier to access. It is also going to generate new capacities within the marketplace. That’s my personal view too, so I’m glad that you believe in it as well…but is it fair to say that there is fear anytime there’s innovation?

Taryn: Yes. People were scared when computers came in, but they made us smarter and more efficient. And, while computers may have led to the elimination of some jobs, they are responsible for the creation of many others.

Solon: People here at DCPA ‘17 are embracing innovation, but they’re not sure exactly where to start all the time. They rely a lot on the product community here and their peers to guide them. You live and breathe the profession, go to many industry events and know the mandate of CPA Canada. How would you explain the benefits of AI and blockchain technologies to a senior partner that is in the grind, has a medium-sized practice and doesn’t have time to come to these conferences? What advice would you give him or her to understand what the profession is going through right now and how it may change?

Taryn: My advice to all would be to prepare yourself for challenges posed by globalization and technology. Stay abreast of changes in the business world, get familiar with new technologies and proactively assess the implications.

For small to medium-sized practices that may be resource-constrained, I encourage them to check out our available resources and be aware that more are on the way.

The most important call to action is to start now when it comes to assessing what the operating landscape is going to look like for your organization. Identify the challenges and meet them head-on.

Solon: To your point, some of the more prominent partners who are engaging with our vision are moving pretty fast on that.

Taryn: In general terms, it’s important to be aware of everything that’s happening out there. Be honest to yourself and don’t pretend that change hasn’t arrived. More specifically, as an auditor, you look at the problems in a company and help your clients address any pain points, and for that, you must use the appropriate tools. If you don’t have the proper tools, guidance or information, help is available. Taking action today can pave the way for long-term success.

Solon: I recently met a very cool CPA, Natalie Quan, CFO of the CalCPA Association, who was also the controller for the San Francisco Ballet. Who is the coolest CPA you have ever met?

Taryn: We meet a lot of interesting and inspiring people through the work we do at CPA Canada. We work with subject matter experts in Canada and globally, to help the profession and for that reason, I couldn’t pick just one.

Solon: What is the most exciting story you heard?

Taryn: Technology today moves rapidly, resulting in many exciting stories.

Of particular note, I would reference Alan Wunsche, a blockchain expert CPA Canada works with, and he launched Token Funder on November 1st with the Ontario Securities Commission; the province’s first regulated token offering.

My job is a blessing because I get to work with many respected thought leaders and hear how they are moving forward in today’s global economy. It’s amazing to see the innovation that is happening all around us.

Solon: You seem to be doing a great job, and you seem to enjoy it so, congratulations.

Taryn: I certainly do!

Solon: Thank you for your time. The readers are going to enjoy this blog post.

Originally posted on Solon Angel’s Linkedin and can be accessed here.

Recent advancements in Artificial Intelligence (AI) and machine learning are ushering in a new era of possibility for the audit function globally. By touching all transactions in a data set, audit firms around the world are using this cutting-edge technology to drive tremendous efficiency and effectiveness gains.

Gilbert Associates Inc. recently adopted MindBridge Ai Auditor™, which utilizes a hybrid of tests including machine learning based algorithms, rules-based tests, and statistical models, against each transaction in the complete financial dataset. Through the analysis of all the records, the results are presented to the user in an intuitive, visual interface which augments the capabilities of audit and investigative professionals by allowing them to focus their analysis on the most relevant activities. Our VP of Growth, John Colthart had a conversation with David Ljung, CPA, President and CEO, Gilbert Associates Inc. and Kevin Wong, CPA, Director of Audit Practice about how integrating AI technology into their audit practice is creating value for their clients.

Here’s what they had to say!

John Colthart: Tell us about Gilbert Associates Inc.

David: Our clients are a mix of closely-held companies, nonprofit organizations, and governmental agencies. Our emphasis is on delivering high-touch customer service and adding significant value to their organization.

John Colthart: What do you see as your biggest opportunity?

David: Our biggest opportunity lies in our ability to capitalize on technology to improve the efficiency of our work and produce greater insight into our clients’ organizations to increase both their effectiveness and profitability.

John Colthart: What do you see as the biggest threat or challenge?

David: Being unaware of or ineffectively utilizing current technology to improve our service to clients.

John Colthart: How do you plan to address it?

David: We plan to approach technological advances openly, and challenge ourselves to push the envelope to identify those which can effectively improve and expand services to clients while maintaining an appropriate balance with our costs of delivering those services.

John Colthart: What made you choose MindBridge Ai Auditor™? What are the features that you plan to use?

Kevin: MindBridge Ai Auditor™ gives us a scalable opportunity to tap into Artificial Intelligence(AI) technology without the up-front software and data science development costs. As the first product of this kind in the market, we hope to leverage Ai Auditor™ to make our audits more efficient, reduce audit risk, and as a differentiator in the industries we practice in. Beyond the risk analysis of 100% of general ledger transactions, we are in the exploratory stages of determining how we can most effectively incorporate this technology into our processes, provide deeper value-added insight into our clients’ operations, and open new service lines.

Today’s audit environment is more dynamic, complex and growing than ever before concerning financial data.  The challenges with globalization, the growing Internet, Big Data and ERP systems with multiple touch points fuels the growth of financial data and challenges the ability of professional accounting firms to assert high-levels of confidence in performing audits.

However, with the recent advancements in technologies such as artificial intelligence (AI), auditors can augment their capabilities to sift through and analyze these large amounts of data.

At MindBridge™ Ai, we utilize a hybrid of tests including machine learning based algorithms, rules-based tests, and statistical models,  against each transaction in the complete financial dataset. Through the analysis of 100% of the records, the results are presented to the user in an intuitive, visual interface which augments the capabilities of audit and investigative professionals by allowing them to focus their analysis on the most relevant activities.  MindBridge Ai has elevated the definition of ‘reasonable assurance’ to help auditors ensure financial data is free of errors, and potentially intentional misstatement. Accounting and auditing firms across the world are acknowledging the value of AI and are using it as a competitive advantage.

One such forward-looking firm is KNAV P.A., a KNAV International Limited firm that has recently adopted MindBridge AI Auditor™. KNAV International Limited is a not-for-profit, non-practicing, non-trading corporation incorporated in Georgia, USA, and it has more than 400 professionals and 42 partners in nine locations across the world. I recently sat with Atul Deshmukh, Global Leader of Assurance Services, at KNAV to learn how he plans to transform the auditing business with the use of AI.

Let’s meet Atul!

John Colthart: Tell us about KNAV.

Atul:  KNAV International Limited is an association of global accounting and consulting firms, founded in 1999, that offer a complete suite of public accounting services—including set-up, accounting, assurance, taxation, international transfer pricing, risk advisory and business advisory services—and facilitate seamless business growth through mergers and acquisitions.

Today, KNAV is an international organization comprised of more than 400 professionals and 42 partners in nine locations (India, the United States, Canada, Switzerland, Singapore, France, the Netherlands, the United Arab Emirates and the United Kingdom).

Working with some of the largest and most recognized multinational companies, KNAV enables clients to comply with financial reporting, regulations, and taxation across multiple geographies. KNAV P.A., our US public accounting firm, is headquartered in Atlanta, Georgia and is the US founding member firm of KNAV International Limited. KNAV P.A. is also a member of Allinial Global, an association of independent accounting firms within North America and the rest of the world. The resources of Allinial Global are comparable to those of a “Big Four” firm. Allinial Global firms share ideas, training resources, best practices and, most importantly, knowledge as needed to meet the needs of their clients anywhere in the world. Although member firms are owned and managed independently, there is substantial collaboration among the members, allowing member firms to better serve clients in a wide range of industries.

John Colthart: What do you see as your biggest opportunity?

Atul:  At KNAV P.A., we foresee a tremendous growth in investments by multinational companies, specifically companies from India or in North America and companies that thrive on the Indo-US business model. Our presence in Atlanta and the Bay Area in the US and across various cities in India and our ability to provide audit, tax and advisory services in the US and India to these multinational companies are our biggest opportunities. We have a leadership position in this niche market, and we expect to continue to grow in this market segment.

John Colthart: What do you see as the biggest threat or challenge?

Atul:  The need to keep abreast of changing accounting and reporting standards, the complexity of conducting audits of large public multinational companies and the challenges of ever-changing tax laws continue to be our biggest threats and challenges. Coupled with the increasing complexity within our service delivery, the dearth of skilled and trained resources within our niche segment creates a high-risk environment for our firm. The huge investments that larger accounting firms are making in technology will effectively level the price differentiation between these firms and smaller firms such as ours. Losing our coveted space in our market segment to larger firms is a threat that is real and imminent.

John Colthart: How do you plan to address it?

Atul:  KNAV has established a special task force to keep the firm abreast of the latest developments in accounting, auditing and taxation. We are heavily investing and relying on technology to mitigate the risk arising from the deficiency of skilled and trained professionals in the marketplace. We continuously seek ways to get a first-mover advantage by embracing state-of-the-art tools and techniques that enhance the accuracy and efficiency of our services. In this context, the use of AI for data mining and analytics is a strong step that we have taken to dramatically improve and enhance the efficiency of our professional audit staff.

John Colthart: What made you choose MindBridge Ai Auditor™? What are the features that you plan to use?

Atul:  We at KNAV felt that a unique solution such as MindBridge AI Auditor™ would allow us to provide a more time-efficient, more economical, more rigorous and higher quality audit, which provides an elevated level of assurance to our clients. Since our focus is on having stronger analytical, data science and IT skills to complement our financial and cross-border business acumen, we were clear that this tool would help us tremendously in making our audit process faster, more reliable and more efficient. In today’s digital world, it is critical for the audit profession to embrace advanced technology tools—including robotics, automation, and cognitive technology.

The smart data import, out-of-the-box integration with leading ERP and accounting software, features related to risk-based scoring, user-interface design and transaction sampling are the key features of the MindBridge AI Auditor™ that would enable the KNAV team to work closely with the client. The fact that we are exposing each and every transaction from the client general ledger to 26 rigorous tests is a game changer. Never before have we been able to conduct such an in-depth analysis of client data at the transaction level.

To see an announcement of our relationship with the KNAV P.A., please click here.

Compared to humans, new technologies like Artificial Intelligence (AI) are ideal for automating mundane tasks related to auditing. AI can also verify every transaction and codify human knowledge, enabling auditors to review, analyze and audit more effectively. As big firms adopt AI in their auditing processes, smaller firms are also realizing the value and becoming frontrunners for this positive change in the industry.

Garbelman Winslow CPAs (“Garbelman Winslow”) is a full-service public accounting firm servicing businesses and non-profit organizations for over seventy years throughout the Washington, D.C. metropolitan area, has adopted the MindBridge Ai Auditor™. As part of our Customer Spotlight series, I had the chance to catch up with Samantha Bowling, CPA, CGMA, Partner at Garbelman Winslow. Samantha has been with the firm for over 25 years and has been involved with auditing services since her career started. She has utilized technology to enhance the audit process from paper to paperless and is now implementing AI to assist in risk assessment, audit assurance, and effectiveness.

Let’s meet Samantha!

John Colthart: Tell us about Garbelman Winslow.

Samantha:  We are a small public accounting firm located in Prince Georges County, Maryland.  Our firm has been in existence for seventy years. We provide various services to our clients: Audit, Review, Compilation, Tax, Bookkeeping, Payroll, CFO, Information Technology, Financial Planning and Consulting Services. Our clients include non-profit organizations, construction contractors, manufacturers, professional services, wholesalers, and distributors.  We have utilized technology since our formation starting with a mainframe computer and punch cards to desktops and tablets.  We provide services to other public accounting firms who do not invest in technology so that they can meet their customers’ needs.  We are involved in the accounting profession so that we can make it better for everyone.  We are not afraid of change and embrace technology to enhance efficiency for our office and for our clients.

John Colthart: What do you see as your biggest opportunity?

Samantha: The biggest opportunity I see is to be a part of the development of AI technology to make sure it really does enhance audit efficiency, reduce risk and produce a better audit.  I believe our feedback during this implementation will help make AI relevant and demonstrate to other small firms that AI is available to them.

John Colthart: What do you see as the biggest threat or challenge?

Samantha: The threat is not embracing AI. I feel other small firms will not embrace the technology and they will no longer perform audits.  Auditing services will move to larger firms. In today’s rapidly changing technology environment more and more “CPA” functions are being automated. If CPA’s at small firms stop performing audits, then they will have to redefine their services and relevance.

John Colthart: How do you plan to address it?

Samantha: Implementing MindBridge Ai Auditor™, providing feedback and making sure it works the way we need it to be the first step. Also, exploring additional uses; I believe this is a valuable management tool for outsourced CFO services as well as an oversight tool for all businesses looking to identify risk within their financial transactions. Ultimately using this platform to demonstrate the importance of AI supported services and explaining how it works to all Maryland CPAs.

John Colthart: What made you choose MindBridge Ai Auditor™? What are the features that you plan to use?

Samantha: I was looking for an affordable AI platform.  I used my “Google” machine and this was the only application that I thought would work for my small firm.  We plan to use all features in our implementation phase to assess which may be valuable to each of our clients, not just our audit clients.

To see an announcement of our relationship with Garbelman Winslow, please click here.

With the audit season fast upon us, a person stops to think about ‘reasonable assurance’.

Audit standards such as AU-C 240, CAS 240 and ISA 240 stipulate that “…an auditor has a responsibility to plan and perform the audit to obtain reasonable assurance about whether the financial statements are free of material misstatement, whether caused by error or fraud.”

‘Reasonable assurance’ is a term used in industry standards and the audit profession to render an opinion as to whether financial statements are free of error, or in some cases, fraud.

An article published by The Institute of Chartered Accountants in England and Wales (ICAEW) defines ‘reasonable assurance‘ as “…the level of confidence that the financial statements are not materially misstated that an auditor, exercising professional skill and care, is expected to attain from an audit.”

To render a reasonable level of confidence, auditors rely on many factors including the following three key items:

1. Professional skepticism
   Professional skepticism requires a questioning mind and being alert to conditions which may indicate possible misstatement.
   The Public Company Accounting Oversight Board (PCAOB) standards define ‘professional skepticism’ as “…an attitude that includes a questioning mind and a critical assessment of audit evidence, and it is essential to the performance of effective audits under Board standards.”
2. Sample selection of financial transactions
   Given the volume of financial transactions, a sampling methodology is used to analyze the datasets. As it would be labor-prohibitive and not cost efficient to review all transactions manually, a sample selection of the dataset is identified.
   There are two general approaches to ‘audit sampling’: non-statistical and statistical. Both approaches require that the auditor use professional judgment in planning, performing, and evaluating a sample and in relating the evidential matter produced by the sample to other evidential matter when forming a conclusion about the related account balance or class of transactions.
3. Testing of the selected sample of financial transactions
   Traditional computer-assisted audit techniques (CAATs) that are used to perform tests on financial transactions are typically based upon rules. Rule-based testing requires knowledge of the rule to detect and, in the case of traditional software, technical skills to script the rules. Rules-based systems can’t catch unanticipated scenarios—and, in many cases, the rules themselves can be exploited—making this type of detection increasingly inefficient, not to mention labor-prohibitive to review all transactions manually as mentioned previously.

Each one of the above components is subject to human bias.

As evidenced through countless high-profile cases, and some not so high-profile cases, the fact that clean audit reports were given to many failed or failing companies supports the argument that the current method of asserting ‘reasonable assurance’ must be improved.

In fact, just last week, the U.S. Securities and Exchange Commission (SEC) unanimously approved the PCAOB’s new auditor’s reporting standard, supporting the communication of “critical audit matters” as a way for auditors to provide more information to investors and the public.

As defined in the PCAOB standard and related amendments, critical audit matters are any matter arising from the current period’s audit of the financial statements that was communicated or required to be communicated to the audit committee, and that:

• Relates to accounts or disclosures that are material to the financial statements, and
• Involved especially challenging, subjective, or complex auditor judgment.

Further compounding the problem over the last decade are the growth and adoption of:

• The Internet
• Hackers
• ERP systems with multiple touch points
• Big Data

The combination of these issues further hampers the ability to assert high-levels of confidence that rely solely on human, professional experience.

With the advancements of technologies such as artificial intelligence (AI) that are now available in the market, professionals, including auditors, must augment their capabilities with the power of AI to sift through and analyze large amounts of data.

At MindBridge™ Ai, we remove subjective, human bias from the audit process and perform a full coverage analysis using a hybrid of tests against the complete financial transaction dataset.

The automated analysis of the financial datasets is performed by the MindBridge Ai Auditor™, which combines a hybrid of algorithm-based business rules, statistical models, machine learning and artificial intelligence.

Through the analysis of 100% of the records in the datasets, a ‘risk score’ is generated for each transaction to highlight those that warrant further investigation.

The results are presented to the user in an intuitive, visual interface which augments the capabilities of audit and investigative professionals by allowing them to focus their analysis on the most relevant activities.

By performing an analysis and associating a ‘risk score’ on all financial transactions, coupled with MindBridge Ai’s intelligent statistical sampling capabilities, MindBridge Ai has elevated the definition of ‘reasonable assurance’ to help auditors ensure financial data is free of errors, and potentially intentional misstatement.

Here’s what customers are saying about the MindBridge Ai Auditor.

“The MindBridge Ai Auditor™ enables our team to pinpoint unusual transactions and enhances the thoroughness and precision of our analytics. Investigations that have historically involved months of combing through millions of transaction samples are now much more comprehensive—yet more narrowly focused—and can be concentrated in just hours.” (full text here)

“Rather than our trainees using random number sampling or a sample based on what they deem to be risky transactions, MindBridge ranks all of your transactions on a risk rating, and then depending on whatever the sample size is you pick it gives you, say, the top ten riskiest transactions.” (full text here)

“The machine learning capabilities of MindBridge Ai Auditor are unique in the audit field and go well beyond the capabilities of any data analytics technology we’ve seen for the full audit profession” (full text here)

“MindBridge’s tool demonstrated it can usefully detect anomalies in datasets. Its user interface is intuitive and presented the data visually, allowing the user to explore a time series of each variable, whilst comparing the result to the industry average.” (full text here)

If you’re interested to learn more about MindBridge™ and our Ai Auditor™ platform or would like to run your own A/B test, please visit www.mindbridge.ai.

What better way to start the first post in the “CPAs” series than with a world-class lady. Angelique Koopman, Partner Audit Innovation at Baker Tilly Berk, has been following MindBridge since our early days and recently visited our office. We could not resist asking her a lot of questions.

In this series, we will interview various CPAs in the profession as we travel across the globe, asking them for their opinions and personal stories. If you ever would like to share your own experience as a CPA, please do not hesitate to reach out directly.

Solon:  Where do you think analytics and artificial intelligence (AI) would be the most useful in the audit process today?

Angelique:  Planning and risk assessment are often based on professional judgment. And what I would like to see is the use of more data analytics in the planning phase of the audit so we can substantiate our considerations and our risk assessments with facts (quantitative data). This way we are collecting evidence to support our risk assessments early on.

Solon:  So how should we address that deficiency, and what impact do you think it has during the audit process? What surprised me recently is that there are firms that do it in the review phase, then they miss something, and they have to go back. If you do integrate next-generation AI systems in the planning phase, do you think it would help to decrease this need to re-do portions of the audit?

Angelique:  Yes, when you are doing your risk assessment or your planning, it’s better to have a set of preliminary analytics based on facts. That way, you can substantiate the choices you make which can help you decide to perform all the procedures or just a subset of procedures. Right now, we do risk assessments to limit the audit work. If you do not plan your audit well enough, at the end of an audit, you will find that you missed something somewhere and then you have to go back and do additional work, and I believe this is one of the best arguments for using analytics more in the planning phase.

Solon:  At the end of the day, is it just about analytics, or are there other industry best practices we can also be including?

Angelique:  It is the combination. It’s a combination of automating rigorous procedures and it’s about automating specific aspects related to the industry. I strongly believe in an industry driven approach. It is more of the rule-based part using the industry expertise. But I also believe that analytics must be used in combination with the auditor with all his knowledge and the holistic view of the client. Giving the auditor the technology to do better, to improve professional judgment, to improve decisions based on intuition or feeling and to substantiate those decisions more comprehensively. That is really important. To be honest, I don’t believe in just having a tool or platform only, because, in the end, an auditor needs to evaluate the outcome. But what you can do is help the auditor from performing tedious tasks that could otherwise be automated. Such tools provide the auditor with more insights and knowledge such as making cross-references and analyzing data from more than one dimension. What we normally do with audit analytics, is that we have a question, then we build the query and the query gives an answer that’s different, so I believe in the combination of both analytics and best practices in combination, that it will help auditors become more focused on delivering better results.

Solon:  There is a lot of confusion over the role AI plays in the audit. What would you tell a traditional audit partner who is evaluating if he/she should leverage machine learning and artificial intelligence (AI)? 

Angelique:  Mostly when people hear about AI, they believe that it is science fiction. And they might think it is in the preliminary stage and are not aware of the fact that nowadays lots of things in our society are run by algorithms. We use them everywhere. Unfortunately, we are not using it in the audit on a large scale yet. Maybe, we think it is scary. However, when we get into a plane, we fully trust the airplane, but in the audit world, we do not trust algorithms yet. Basically, it’s about combining statistical methods with machine learning. So I think they need to know what machine learning is and how it works. We have to explain it with simple examples, like how does a program operate and learn? As an example how to identify a cat from a picture? In fact, AI is about automating tasks that are beyond the capacity of human beings. Machine learning is a way of making complex analysis possible. Automating repetitive audit tasks makes even greater business sense when you combine it with machine learning and AI algorithms.

Solon:  People talk about the robot taking the job of an accountant… 

Angelique:  It’s very similar to the team that supports you when you are auditing a bank, and the bank has financial instruments, and you have team members who are specialized in that type of audit; they have the know-how of the financial instruments. Or when you are auditing a real estate company, you use the expertise of people who know that space, you cannot do it by yourself. It’s only expertise enshrined in a computer program. That’s the difference.

I was telling Robin and Eli, knowing that this technology is here, and at this point, it would be hard to go back to audit and do the role I used to do without leveraging this technology. I can clearly see the value it adds, I can do a manual sample, but recognizing that with AI I can sample the whole ledger with a higher degree of assurance. And given that it is my signature on that audit statements, I want to do the best job with the best tools available.

Solon:  So using artificial intelligence (AI) is going to become a matter of professional integrity?

Angelique:  I think, this is something in the audit community which is starting now. And I gave the same message at a recent conference in Belgium. People start to think about it, and they are starting to say, “Yes, why not? Change is coming!”

Originally posted on Solon Angel’s Linkedin post

Auditors love statistical sampling and so does the MindBridge Ai team. Why wouldn’t we—statistical sampling uses the laws of probability to measure sampling risk. We truly believe that statistical sampling largely outperforms judgment sampling.

Don’t get us wrong—the experience of a Partner is undisputed and their ability to focus the audit and identify areas of risk in financial statements is the key to a successful audit and, of course, the peace of mind once an audit opinion is issued. However, once the risk areas are identified and a population of thousands (if not millions) of transactions remains to be reviewed, experience alone might not be sufficient to select a test set.

Statistical sampling and the laws of probability make it feasible to pull a test set from a huge population so an audit team can use it to give reasonable assurance that the overall population is free from material misstatements.

Can audit teams give the same reasonable assurance and test fewer transactions?

There are many commonly used methods to enhance statistical sampling in the audit profession. For example, Monetary Unit Sampling is one (very, very popular) way that a test set can enrich the items most likely to be of interest to auditors. In Monetary Unit Sampling, every dollar is regarded as a distinct unit and given equal chance of being in a transaction picked for testing. Therefore, the higher the amount of a transaction is, the more likely it will be part of the test set. In an audit context, this is great as larger transactions, the ones that are more likely to cause a material misstatement, are more likely to be picked for testing.

How did MindBridge come up with an improved sampling methodology?

First, let’s clarify what improved means. For us improved means to enrich data in a meaningful way so it makes the whole testing process more efficient. Similar to Monetary Unit Sampling, we enrich a data set with additional information to make it more likely that transactions get sampled that are of audit interest.

The intelligent sampler

We run a number of tests to calculate a risk score for every single transaction in a data set. This risk score is the basis of our intelligent sampler which pulls a stratified sample set across the whole population. As with Monetary Unit Sampling, every transaction has a chance for being selected for field testing; however, the ones more likely to be of audit interest having a higher chance.

What does “of audit interest” mean?

“Of audit interest” means the likelihood that a transaction is misstated due to fraud or error. In a number of field experiments, the Ai Auditor™ has proven its ability to identify and push fraud- and error-prone transactions to the top of our risk ranking.

This ability of our Ai Auditor™ to identify transactions which are more likely to be fraudulent gives audit teams the ability to reach the desired confidence level with a smaller test set of transactions. MindBridge’s intelligent sampler is a focusing tool that helps the auditor identify audit areas that they should spend the most time on, but at the same time makes sure they also spend enough time in other areas beyond the high-risk transactions.

Comparing statistical random sampling with intelligent sampling

Our data science team created a general journal for educational purposes. This journal consists of 2966 transactions of which 24 transactions are non-compliant. The non-compliance rate in this file is 0.8%.

Assuming an acceptable error rate of 1%, it would be required to test a sample set of 230 transactions to achieve a 90% confidence utilizing statistical random sampling methodology.

Our intelligent sampler takes an equal number of samples from the Low and Medium/High-risk categories. This ensures that every transaction has a chance of being selected in the sample, but those with higher risk have a higher chance. Using this method the auditor has a 90% chance of discovering non-compliance in the file with just testing a sample set of 14 transactions.

Approach	Confidence level / error rate	Required Sample Size
Statistical Random Sampling	90%/1%	230
Intelligent Sampling	90%/1%	14

 

If you’re interested to learn more about MindBridge™ and our intelligent sampler, or would like to run your own A/B test,  please get in touch.

Throughout my investing and business life, I’ve been amazed by the number of accounting scandals and re-statements that have occurred. The issue of regulatory oversight is raised in the press, but even with increased enforcement and higher penalties, a new accounting issue is never far behind, and it’s continued to get worse. Just look at the impact on British Telecom’s stock because of the irregularities found in accounting in their Italian division (read about it here).

One week into joining MindBridge Ai, I can see how we are focused on the goal of solving one of the massive issues underlying these scandals, and I can see how we are building an expert system to help both internal and external auditors provide us with higher levels of assurance about the financial statements they are sworn to certify.

And the baseline issue we are dealing with is the amount of financial data they need to consume. There has always been too much of it. The Big Data problem facing auditors is that they are asked to “go fishing in a murky lake” and find accounting anomalies and irregularities for further review. To this point, accountants and regulators are agreed that this should be done using statistical account sampling. However, the quality of the sample can only be measured after it has been sampled and analyzed. And with the time pressure on providing audited results, if an irregularity or anomaly is found, the process has to start again. And this leads to costly re-statements which impact shareholder value and confidence in the audit firms.

To solve this, Mindbridge Ai is leveraging machine learning AI to provide auditors with a more highly justifiable sample before the audit begins. Our Auditor AI service can ingest and analyze the entire leger and pinpoint areas they should be investigating early on with a higher degree of justification against the standard, and currently accepted sampling techniques. This gives auditors a higher assurance rate and helps them improve upon the current approaches that only meet the standard, and not move past it and towards the answers we, the press and firms like British Telecom need.