Improving audit risk assessments with AI-driven analysis of Accounts Receivable and Accounts Payable subledger data

Improving audit risk assessment longterm

The cornerstone of well-planned and high-quality audit engagements is a robust risk assessment process. Such a process is critical to identifying risks of material misstatement and their relative significance by providing a fulsome understanding of the entity subject to audit and the environment in which it operates.

The nature and extent of these audit risk assessment procedures will certainly differ from engagement to engagement, reflecting different types of operations, industries, and financial reporting complexities, however preliminary analytical review procedures are a common thread across all audits as a requisite component of the risk assessment process.

Traditional preliminary analytical review procedures

Practically speaking, preliminary analytical review procedures could include any combination of the following (not exhaustive):

  • Comparing actual financial performance to historical trends and balances
  • Reviewing actual financial performance (ratios, key financial metrics) against industry benchmarks
  • Reviewing actual financial performance compared to management forecasts and/or budgets
  • Performing inquiry of management to ascertain operational drivers for certain trends and patterns in the year-over-year results (i.e., “what’s changed?”)
  • Examining any material new contractual agreements executed in the period (leases, customer contracts, debt agreements, etc.)

Traditionally, these types of analytical review procedures take place at the level of how the financial statements aggregate the data by account or class of transactions, or perhaps at more granular levels of the chart of accounts. For example, you may compare how gross margin in the current period compares to historical periods or how increases in inventory year-over-year tracks with corresponding movement in the cost of sales accounts. In any case, it is ultimately the general ledger trial balance data and activity detail that underpins this type of review.

With a view towards a robust risk assessment process and obtaining a deep and operationally relevant understanding of your client’s business environment and financial performance, analysis and interrogation of the AR and AP subledger data as a complement to the traditional preliminary analytical review procedures at the financial statement level could be a source of highly valuable context to the results and empower you to conduct a more focused inquiry of your client’s management.

Accounts Receivable & Accounts Payable as critical inputs to audit risk assessment

Visualizing and interrogating subledger data can provide high-value insights and expose “root causes” behind some of the general ledger variances and patterns identified as part of your traditional preliminary analytical review procedures. This empowers you to better pinpoint an assessed risk and tailor your testing approach to most efficiently respond to that assessed risk.

Some examples of how to best leverage subledger information include:

Understanding how certain vendor and customer aged balances trend throughout the year

The aggregate total values of AR and AP at balance sheet dates might be relatively consistent year-over-year but there may be cause for further investigation and inquiry if, for example, the monthly ending balances demonstrate significant volatility throughout the year or seem out of pace with corresponding monthly sales or purchasing trends.

Understanding operational key performance indicators for customer and vendor “health”, and tracking those over the audit period

Tracking basic operational metrics like Days Outstanding and Turnover ratios, for specific vendors, customers, and in total, provides a lens of relative customer “quality” or vendor settlement patterns that may allow for risk to be identified more granularly. Comparing these ratios for a particular customer against the “aggregate” value allows you to identify specific customers or vendors that lag the overall average and therefore may indicate an existence or valuation risk around those balances or underlying contracts.

Expose the nature and volume of transactions on credit with related-party customers and vendors

Reviewing the subledger detail for transactions with all related entities is information that may not be readily available on the surface of the general ledger data and the relative dollar volume and activity of these transactions could be relevant to how risk is assessed around the accuracy, valuation, and presentation assertions.

Surface invoices or other records in the subledger (debit or credit memos, unapplied payments, etc.) that may be significantly aged

Isolating items in the subledgers that are significantly aged may tie directly to the risk around valuation and existence of these items specifically. Under a more nuanced lens, the existence of these types of stale records (or lack thereof) may be a relevant consideration to corroborating your understanding of the controls framework and how closely the subledgers are being reconciled and actively maintained.

Evaluate the volume and frequency of transactions at the level of a specific customer or vendor to corroborate inquiry of management and your understanding of the entity

Understanding basic data points around volume and frequency of transactions with a particular customer or vendor may help corroborate information learned from inquiry or your knowledge. For example, reviewing transactions with the entity’s landlord to confirm that 12 monthly equal rent payments were posted. Scanning this type of activity (either manually or with automated techniques) can surface invoices or payments for amounts that are potentially unusual for a certain customer or vendor and therefore perhaps may be indicative of risk.

Review for the volume and frequency of manual adjustments directly to the subledger detail

Manual adjustments or entries directly to the subledger, i.e., entries that don’t have a commercial document of record (invoice, cheque, credit memo, etc.) associated to them, may indicate fact patterns or internal processes that warrant further consideration from an audit perspective.

Perform basic statistical and rules-based tests and interrogate the subledger data to inform risk assessment

Certain procedures around data quality that are traditionally associated with journal entry testing, such as the following, may be very relevant to the subledger information. This includes any “hits” that would be relevant to deepen your understanding of your client’s accounting system and internal control framework and also advise the severity of assessed risk:

  • Reviewing descriptions for suspicious keywords
  • Duplicate document IDs
  • Two-digit Benford analysis
  • Other rules-based tests

How MindBridge automates and streamlines AR & AP subledger analysis

MindBridge AI has dedicated AR and AP modules that automatically analyze the subledger data and, without any scripting, provide high-value visualizations of the data and transaction-level analysis. These capabilities empower you to leverage subledger-level insights and anomalies as critical inputs to the audit risk assessment process.

Trends and patterns

Ai Auditor provides the ability to visualize how monthly AR and AP balances or net monthly activity tracks over multiple years, at the customer and vendor level and also in aggregate. The visualization is customizable and provides the ability to compare certain customer or vendor trend lines against each other and identify patterns of deviation.

Vendors and customers who are related parties to the entity subject to audit are flagged directly in the summary detail to identify for specific review. 

internal audit tools

Key performance indicators

Days Outstanding and Turnover ratios are calculated at the customer and vendor level and visualized on a monthly basis, allowing you to identify where there are periods of potential distress or deteriorating quality. Similar to the ending balances and activity, you are also able to customize the visualization and compare certain customers or vendors against each other along the lines of these metrics to expose patterns of interest.

internal audit results

Ai Auditor also automatically identifies any new customers or vendors in the audit period, allowing you to identify the related volume of sales or purchasing growth specific to these entities.

Aging

Aging at the customer and vendor level is automatically calculated and captured across respective buckets of days outstanding (0-30 days, 31-60 days, etc.). For certain entries that are significantly aged or stale, you’re able to drill-in to all the transactions with a particular customer or vendor and ascertain which invoice(s) are contributing to those totals.

internal audit and governance

Data interrogation and risk

Navigating and querying the transactional level data via the Data Table in Ai Auditor provides a powerful and effective way to explore and validate the subledger activity. The Filter Builder functionality allows for multiple conditions to be placed on a query, using any element of the transactional record (date, amount, user, entry type, etc.). This allows you to build and save functions that allow you to get a sense of the type, frequency, and volume of transactions with certain vendors or customers.

reasonable assurance audit

Control Points, which are various statistical, rules-based, and machine learning tests, are run against every transaction and the results are summarized on a dashboard that supports interactions like filtering and drill-through.

corporate internal auditor

Combining the query building capabilities of the Data Table with the feature of every transaction being scored against the various Control Point tests, you are empowered to identify relevant populations for sampling and have selections automatically identified on a risk-stratified basis. Approaching the sampling process through the lens of transactional risk ensures that you’re focusing your audit procedures around the entries which appear anomalous.

Take the first step towards unlocking critical subledger-level insights for risk assessment

To learn more about Ai Auditor and subledger analyses, contact sales@mindbridge.ai.

AI in finance: Helping professionals shift from hindsight to insight to foresight

Stopping dominoes with foresight

We are facing an unprecedented time of global uncertainty created by the COVID-19 virus that has unleashed a global healthcare crisis. Humanity is fighting a war against an invisible enemy that is attacking humans around the world and sparing no country. We need not be pessimistic or optimistic but rather realists and learn from the history of humanity. Human ingenuity will prevail, and humanity will survive.

We have entered a new world after COVID-19 with very different assumptions than we had in the old world when the world GDP yielded a record high of $85T. The world GDP has been severely impacted by the lockdown stipulations that were imposed to minimize the spread of the virus within the population. The key pillars of the economy are consumer and companies’ spending. If this slows down, it can lead to a recession and even depression. The lockdown restrictions are being relaxed and governments and central banks around the world are injecting massive amounts of funds into the hands of individuals and companies in an effort to reopen the economy to avoid an economic crisis.

How can artificial intelligence in finance help organizations pull through?

A renewed focus on financial errors

During economic uncertainty, an added vigilance is needed by those responsible to ensure the accuracy and integrity of the financial records that are being relied upon to make decisions about the operations of their organizations. A report by the Association of Certified Fraud Examiners (ACFE) “2020-Report to the Nations”- 2020 Global Study on Occupational Fraud and Abuse estimates that the yearly cost to the world due to fraud and abuse is about $4.5T or 5% of the world GDP. They examined over 2500 cases from 125 countries with combined losses of $3.6B with an average loss by case of $1.5M and a typical case lasting 14 months before being detected.

Whereas corruption was the most common type of fraud, the most costly were financial statements fraud schemes, even though they represented only 10% of the cases.  The breakdown of the detection methods reveals that analytics plays only a small role in the detection of occupational fraud: Human tips; 43%, internal audit; 12%, management reviews; 5%, by accident; 5%, whereas external audit catches only 4%.

A 2019 survey by Blackline provided insights into the concerns by executives with inaccuracies in financial data. With over 1100 C-suite executives and finance professionals from mid- to large-size organizations around the world, the white paper stated that:

“55% are not confident that they can identify financial errors before reporting results, 70% claim that their organizations made a significant business decision based on inaccurate financial data and 26% are concerned over errors that they know must exist but they have no visibility”.

 

The power of AI in finance

Finance professionals that rely on outdated tools and methodologies do not offer the best visibility into finding errors, errors with intent, errors that are considered fraud, and general mismanagement of the financial dataset in their organizations. The world is already witnessing a major trend toward moving to the cloud and becoming digital native and these must be vigorously pursued by organizations that want to be of the forefront of growth post the crisis.

Becoming digital native enables companies to move towards a near real-time view of their financial data and, coupled with AI in finance functions, the ability to fully analyze 100% of transactions. This ensures transparency to key stakeholders such as board members and auditors and aids in the identification of any anomalies in their financial records.

Currently, a company’s financial records are examined by external auditors on a yearly basis and evaluated using a sampling method that leaves the bulk of the dataset untouched. This method of rear view-mirror assessment provides C-suite executives with a hindsight perspective and the fear that decisions are made based on inaccurate and untimely information. Using AI-based tools to review 100% of the financial records in near real-time offers C-level executives with insights into data and, by using the appropriate analytics built into the AI applications, offers foresights into the operations of the company.

The two most important behaviors that companies must have to thrive post COVID-19 are resilience and adaptability. Resilience is defined as the ability to withstand or recover quickly from difficult conditions whereas adaptability is defined as the quality of being able to adjust to new conditions. Companies must build their operations and culture around resilience and adaptability so they can work efficiently during the “new normal” when we emerge out of this dark tunnel will become stronger and better off.

An article published by the Boston Consulting Group titled “The Rise of the AI-Powered Company in the Postcrisis World” highlights the tremendous opportunity for companies that are going to digital native, moving to the cloud, and adopting AI in finance applications to supercharge their operations. Arvind Krishna, in his inaugural speech as IBM’s new CEO, said, “I am predicting today that every company will become an AI company – not because they can, but because they must. Digital transformation means putting artificial intelligence at the center of workflows, and using the insights generated from that process to constantly improve products and services.”

 

Audit in the age of COVID-19: A guide

a complex amount of data put into a pattern

In today’s world of COVID-19, accounting firms can be pressed by clients for short-term basic deliverables. There are still expectations for getting audits completed as pragmatically as possible per the standards along with the new norm of engaging clients virtually and securely.

I believe this challenge presents an opportunity for firms to re-position themselves for success in addressing this new environment. Humans adjust to new challenges well and this will accelerate the digitization and automation of key accounting processes, including auditing. This automation will not happen overnight but will transition as a step change, where the audit of the future bears little resemblance to the audit of today.

“We believe that the application of artificial intelligence will be immensely valuable in helping companies adapt to these trends. The most successful use cases will be those that seamlessly combine AI with human judgment and experience.”

– The Rise of the AI-Powered Company in the Postcrisis World, Boston Consulting Group

The accounting firms that adjust with speed and agility will be well-positioned to grow today and in the future.

Audit analytics as a competitive differentiator

The topical issues we are witnessing today include ‘going concern’ and financial performance analysis. Tremendous focus is being applied to cash flow, debt management, and yes, business survival. Businesses that are feeling financial stress are seeking additional education and guidance.

Remember, many times clients do not know what they want or what you can do for them. This is a perfect time to make your firm relevant to your clients. You can critically evaluate what is good for your clients and do so by leveraging audit analytics tools to educate them and develop appropriate plans to address their challenges.

type of audit sampling

Audit analytics builds usable market or industry-specific knowledge, so while you might not be able to sell advisory services directly to your audit clients, having better market knowledge improves your ability to sell this value to other companies and win new customers. Your firm becomes more relevant to their business and you have created a competitive advantage for your firm.

Remote auditing begins with security

It will also be paramount to ensure that the technology and services you leverage are designed to work in a virtual environment securely. Ensure that your audit tools are cloud-based, have primary and backup infrastructure providers that are fully ISO 27001 and SSAE 16 compliant, and use data encryption using NIST-approved algorithms (AES 256). It’s also critical that the vendor has completed the AICPA Security Organization Controls (SOC) compliance and has completed its SOC 2 Type 2 certification against all five trust services criteria.

Audit analytics in action

A MindBridge customer spoke recently about the value of our platform and how it positions the CPA firm for success. They stated that Ai Auditor improves the client-auditor relationship by allowing them to ask better questions and enhance the knowledge of their client business more than traditional tools. The platform becomes the single source of information that leverages the general ledger and provides 100% coverage with its transactional approach.

This positions accounting firms to:

  • Understand and guide their clients appropriately, especially in the storm we are witnessing today
  • Critically evaluate what’s good for their clients, including risk awareness and management
  • Educate clients on their options and provide appropriate advice in making better decisions for their business

Accounting firms can re-invent and position themselves for success in this new world by delivering value-added services primarily driven by what is good for their clients. Your commitment to deploying innovative new solutions, such as audit analytics, and creating a competitive advantage for your firm is critical in today’s world of a virtual practice. Internally, firms and their employees will be inspired with the latest innovations and automations that our platform delivers.

There are risks in making this transition and investment but by working with the right partners and being astute about it, the benefits for your practice will be considerable.

Streamlining your going concern audit procedures

digital train

In these challenging times, virtually all organizations are faced with disruptions to the status quo. Depending on the industry and profile of one organization to the next, these disruptions can range from creating slight instability in day-to-day activities to having a catastrophic impact on the basic viability and sustainability of operations.

Transparent and accurate financial information and the auditor’s conclusions thereon are a cornerstone of market and investor confidence in the best of times, and the criticality of this responsibility is only magnified in the current environment.

The auditor’s procedures around the going concern assumption are therefore receiving an increasing focus and consideration by audit teams, particularly for engagements that are well-in-flight and in the concluding phase (i.e., just ahead of financial statements being formally issued). For example: a calendar 2019 audit engagement where financial statements haven’t been issued yet will need to consider a renewed examination of going concern.

How can MindBridge add value and assist in this assessment?

A going concern refresher

Management is required to make the assessment of whether the organization is a going concern for the foreseeable future and the auditor’s responsibility is to obtain sufficient and appropriate audit evidence to support this. If there is a material uncertainty (substantial doubt) regarding the entity’s ability to continue as a going concern, there are additional disclosure requirements in the financial statements and/or qualification of the audit report that may be required by the prevailing audit guidance.

While the applicable auditing standard framework and/or regulatory environment specific to your audit engagement may differ, this assessment must generally consider at least the period of 12 months from the reporting date (i.e., the balance sheet date). Often this requirement is extended for the auditor to consider the period of 12 months from the issuance of the financial statements.

Evaluating the going concern assumption under a new lens

Against the backdrop of the current crisis and considering the auditor’s responsibilities around the going concern assessment, some practical challenges may arise:

  • The question of going concern may suddenly be relevant for an engagement or client that had previously never had any doubt regarding the sustainability of its operations. The company may be well capitalized, have a strong liquidity position, and demonstrable sales growth but is perhaps in an industry that is hard-hit by the crisis, introducing uncertainty into the assumption. Two considerations become relevant in this case:
    • Management may not have the historical experience in providing material to support the going concern assumption (forecasts of P&L, cash flow, summarized non-financial data, etc.) for the foreseeable future, that is up to 12 months from reporting date or issuance date.
    • The auditor may not have the historical experience in obtaining sufficient and appropriate audit evidence around the accuracy of the kind of “forward-looking” material on which management would base their going concern assertion. Further, there may not be any robust experience from previous years in the relationship with the client that objectively supports management’s ability to estimate forecasts effectively.
  • There may be significant uncertainties around future outlook, especially in these (relatively) early stages of this crisis, and management may be challenged to make even the most basic assumptions in their forward forecasting. What will revenue look like and how long may it take to return to pre-crisis levels? How successful will receivable collection be? Where is there flexibility in discretionary expenditures? Various scenarios may be required to be modelled out, allowing for sensitivities in critical financial statement areas, that the auditor may have to review and consider on balance.
  • These uncertainties around future outlook are currently mirrored in the realm of potential government assistance or relief that may be relevant for the organization. Governments and financial institutions are stepping in with significant relief measures being announced and operationalized but information around eligibility and interpretations is changing rapidly. Whether the form of this relief is subsidies, cash flows loans, or tax relief, these are critical inputs to support sustainability of operations that the auditor needs to consider.

How MindBridge helps evaluate going concern

MindBridge Ai Auditor is a powerful enabling tool for auditors to test the going concern assumption:

  • Key trends and patterns can be surfaced
  • Critical ratios can be visualized
  • Transaction-level data can be interrogated

Let’s review each of these capabilities.

Trends and patterns

Ai Auditor allows for financial data to be visualized, layering in current year results against prior periods to surface critical trends and material deviations from history. The example here showcases trending of the accounts receivable line over time.

Within your engagement in Ai Auditor, you are able to create multiple analyses of your client’s financial information. You can create a new analysis that includes financial data from the period under audit and extend the analysis to include the most current financial information into the next fiscal year to assess the going concern assumption and management’s forecasts. This allows you to quickly understand more recent trends and let the data speak for itself against management’s assessment of near-term performance.

internal audit points

Other trended views, with examples, to consider around the going concern assessment may include:

Visualizing cash over-time to get a sense of monthly burn and compare against management’s cash flow analysis. This allows for the review of sudden peaks that may indicate cash from financing or investing activities and can be normalized to derive a sense of cash flow from operations.

internal audit requirements

Visualizing accounts payable and the recent ability to settle balances owing to vendors. This can be compared against management’s cash flow analysis.

internal audit methods

Other potentially relevant trending patterns to explore, as a reference:

  • Visualizing short- and long-term debt facilities and consideration of whether these are indicative of a deteriorating liquidity position.
  • Visualizing revenue trends and comparing them with the expense/cost of sales trends to understand where levers potentially exist for management to manage the economic shock.

Ratios

Ai Auditor includes a library of critical financial ratios that enable you to visualize how each of these metrics move through the year. You can easily create custom ratios that account for a specific industry that your client operates in or perhaps to mirror debt covenants that are in effect.

Similar to the Trending graphs, by extending your data to include more current financial information via a new analysis in your engagement, the ratio visualizations capture the recent movement in these key metrics and surface insights quickly.

Some examples:

Visualizing debt-to-equity ratio over time, and for the most recent period, to assess whether bank covenants are well within acceptable ranges or to get a sense of how operating lines are being tapped as a source of cash flow.

internal audit in accounting

Visualizing gross profit as a percentage of sales over time, especially in recent months, to understand how the economic “shock” of the crisis has impacted margins and income statement relationships.

internal audit features

Other potentially relevant ratios and metrics to explore related to the going concern assessment, as a reference:

  • Current ratio
  • Working capital
  • Debt to assets ratio
  • Debt to equity ratio
  • Expenses to sales ratio
  • Long-term debt to net working capital ratio
  • Accounts receivable to sales ratio

Pro tip: With more than four years (48 months) of historical financial information, a regression analysis called seasonal autoregressive integrated moving average (SARIMA) analysis is performed by Ai Auditor to graphically visualize the expected ranges for the ratio in the current period in addition to the trend lines. In the context of a going concern assessment, this can be extremely valuable to indicate whether a particular ratio or series of ratios is not only potentially down from pre-crisis level but also outside of a normal range. The latter might be more of a signal as it relates to sustainability of operations.

Interrogation of transaction-level data

Navigating and querying the transactional level data via the Data Table in Ai Auditor provides a powerful and effective way to explore and validate the nature of certain accounts in the ledger. The Filter Builder functionality allows for multiple conditions to be placed on a query, using any element of the transactional record (date, amount, user, etc.) as well as the relevant Control Points (the algorithms behind the analysis) that apply to a particular transaction.

internal auditor general

Some examples of where this could be applied to the going concern assessment:

  • Validating whether certain criteria for government assistance are met by your client, i.e., query for total amounts spent on payroll, rent, etc., in a particular period of time
  • In evaluating management’s forecasted P&L against historical results, evaluate the implied assumptions of certain income statements accounts for reasonability, by understanding the nature and frequency of underlying transactions. For greater clarity, validate whether certain material categories of expenses are fixed or flexible in nature.

As the current crisis unfolds, it’s more important than ever for auditors to add value for clients and a going concern assessment is critical in understanding the basic viability and sustainability of operations. MindBridge Ai Auditor can help test this assumption by identifying key patterns (layering in current year results over prior years to surface critical trends), visualizing critical ratios (such as debt-to-equity or gross profit as a percentage of sales), and allowing for the in-depth interrogation of data through customizable filters.

To learn more about how Ai Auditor can help your going concern assessments, contact sales@mindbridge.ai.

Embracing technology as a CFO in 2020

internal audit and risk

CFOs continue to be one of the most important resources to their business. In the last 20 years or so, they have spent countless hours working through regulatory and reporting changes, implementing new systems, and partnering with other leaders in the business on analytics. Through all this, they also have to come up with new ideas to find funding and preserve revenue streams, and maintain the fiscal discipline that CEOs and boards have come to expect.

How can CFOs and their teams balance these needs against higher fiscal scrutiny, cost cutting, and changing work environments?

The answer is to bring longer-term thinking up front, to measure, plan, and execute on our new environment now and get comfortable with the new normal.

CFOs here and now

Many companies are shedding resources and re-aligning their operations to protect their core business, while also hoping to make themselves indispensable to clients. Some are successful while others are struggling to adapt and find themselves trying new ways to look at cash flow, going concern ratios, and most importantly, customer engagement and retention.

This is only natural as the global economic slowdowns and supply chain uncertainties mean that CEOs and boards are tasking CFOs to review all expenses. These short-term projects start with salaries and travel expenses and follow with software subscriptions and other suppliers. While these are good actions to take, they don’t necessarily prepare the organization for the new normal, when people are returning to work, supplies start shipping again, and customer expectations have shifted.

CFOs must build a longer-term strategy into their short-term goals.

Another key consideration is the rise in fraud. According to the latest ACFE Report to Nations 2020, we know that up to 5% of top line revenue is lost to fraud around the world. There’s an expectation that COVID-19-related business and personal stressors will eclipse that figure quickly if we’re not careful.

To evolve beyond the short-term and reactive decision making now, organizations must buckle down and work through their long-haul strategies. From a CFO perspective, this could be:

  • Assessing the level of granularity on reviews and reports
  • Identifying areas of the business to trim or reduce
  • Determining any new risks for the organization to consider
  • Understanding how quarterly reporting, audit, and governance cycles will change

Preparing for post-crisis business operations

As former CFO, Shaye Thyer, posted on LinkedIn: “I would have given my left leg to have access to some of the amazing tech we have now.”

It’s not easy for business leaders and their teams to shift to the new normal and that’s where strategies, people, and tools must come together.

How does this differ from leadership advice in the past?

Rather than focus on reactive measures that use traditional processes and historical data, leaders must plan and strategize updates to their finance organization that take advantage of today’s unique opportunities to outpace the competition. This also means understanding the changed expectations of employees working in a different environment to keep them satisfied, motivated, and productive.

This could mean taking stock of internal remote working situations, and that of clients, to build them into new strategies. Augmented working environments open up a wealth of opportunities for collaboration, communication, and value creation. As this Forbes article states, returning the 2.7 billion people affected by lockdowns and stay-at-home measures could mean that, “While some employees will return onsite, others may continue to work remotely or engage in a hybrid model. In addition to arming workers with the skills and access needed to meet work requirements, re-engaging the workforce will involve assigning meaningful work.”

A big piece of this puzzle will be tools that adapt to these shifts in working models and leverage those changes to open up new opportunities. Moving to a digital-first strategy is key, as it will help teams collaborate better and remove as many manual steps as possible. This should cover everything from payables and receivables processes, such as getting all contracts signed digitally, to working on the assumption that travel will be limited.

Some offices are moving away from physical locations to hybrid models or even full remote working. Whatever each firm decides to do, there’s no question that professions are changing:

“Three elements of our practice have changed forever: the unprecedented move to a virtual practice, the client experience and our relationships with traditional office real estate.”
– Gary Shamis for Accounting Today

The bottom line for CFOs

To prepare for the new normal, I recommend these steps:

  1. Perform a full review of your tech stack and tools to see what needs to change for a post-COVID business model. This includes seeing where AI can fit to empower your teams and bring value.
  2. Start thinking digitally and how to support vendors, customers, and other stakeholders that are making their moves now.
  3. Prepare for a new way of working together on financial reporting from a distance, and evolving audits to be completely “touch free”
  4. Identify risks, especially potential fraud opportunities, and shore up the team with tools that augment their data assessment capabilities and provide deeper insights than traditional descriptive analytics technology

Since my start in this space over 20 years ago, we’ve had a number of times where we’ve relied on the CFO more than any other C-suite executive. This time around, we need to augment the Office of the CFO with state of the art technology, new normal of workplaces (virtual or not), and trust the professionals to take us into new strategies. We need to continue to be lean, execute extremely fast, and ensure that our strategy includes insight-driven tech (such as AI) and become digital in all that we do.

 

To see why finance teams trust MindBridge, watch this 4-minute video now

 

Baldwin CPAs enhances technology-first services with MindBridge

Baldwin CPAs

In the lead up to their panel presentation at Influence 2020, we connected with Myron Fisher, CPA, CGMA from Baldwin CPAs, PLLC (Baldwin) to talk about their approach to technology and audit.

Baldwin is experienced and qualified to provide accounting services to a wide variety of businesses and industries. The firm has concentrations in the industries of construction contractors, governmental, not for profit, and medical. Baldwin is a member of the Private Companies Practices Section of the American Institute of Certified Public Accountants and the AICPA’s Governmental Audit Quality Center and Employee Benefit Plan Audit Quality Center.

Baldwin’s vision is to be an innovative firm that creates value for their clients, supported by their mission statement and core values:

We are dedicated to strategies that enhance the growth and success of our team and clients.

Core values

  • Integrity and honesty
  • Respect and trust
  • Personal development and growth
  • Accountability/Responsibility
      •  

What is Baldwin’s overall strategy and approach to adopting new technology?

MF: Baldwin’s approach to technology is based upon a comprehensive and holistic strategy, from an aspect of ‘what do we want to look like in 3-5 years’?

We look at the adoption of new and emerging technologies and try to position ourselves on the early adopter position of the bell curve. We do not want to be a late adopter as we believe that it does not agree with our vision statement.

Examples of technologies that have been incredibly critical to our success as a firm are adopting virtual/cloud-based platforms early in our past, such as moving to a virtual platform 16 years ago, and moving to a paperless retention environment in 2003. Recent examples are the use of Suralink for a secure document exchange platform for assurance engagements and complete firm integration of Microsoft Teams as communication platform. All these applications made the challenges presented by the COVID-19 pandemic fairly seamless.

What problem(s) were you trying to solve when engaging with MindBridge?

MF: When we look at implementing specific tools, it’s not just about solving one problem, it’s multi-faceted. With MindBridge AI specifically, it’s not just about efficiency, making intelligent samples, doing audit procedures faster, or audit evidence quality — it’s all of these things combined. In addition, the adoption of an innovative tool such as Ai Auditor aligns with shaping the future of our firm.

How is Ai Auditor providing value to your firm & clients?

MF: Overall, it’s driving better conversations internally and externally.

Internal discussions

Internally, we’re just having better conversations within our teams when we open ourselves up to data and insights. We are becoming more aware of transactional details within our clients’ ERP systems.

Just recently, we had a planning meeting on an audit client. In the previous year, we would have put the risk assessment as higher, however, after internal discussions and analysis, we came back and said that the risk assessment should be lower, allowing us to more confidently assess audit risks.

We will also be implementing use of the tool for review engagements. Our team will be able to perform more informed analytic procedures resulting in improved inquiries.

External with clients

We don’t have a “we found this” per se but it’s driving better conversations with our clients, which drives value. The response has been, “you’re asking better questions.”

One example is a client relationship with a city. We approached them early about leveraging Ai Auditor and asked for their data. One of our accountants was able to show the client what the analysis looked like right there onsite. It drove a meaningful discussion and provided more value to the client.

What are some challenges and lessons learned from your experience with implementing emerging technologies?

MF: We know that taking a proactive approach to technology adoption comes with significant challenges and we accept those challenges. Implementation is a challenge with all applications and we are not immune. Early realization and acceptance allows for better planning and depth of understanding within the entire team. Resource allocation is paramount.

Specifically, with tools like Ai Auditor, we recognize the need to have team members better trained in the application of data analytics. We have enabled team members to invest time to become application champions to assist the entire team.

Our biggest pain point and process challenge is getting data from our clients early. We have addressed this area by implementing an internal tool designed to increase communication of expectations from clients.

Communication is critical. We try to ensure that we keep communications flowing and keep all team members informed. Ai Auditor is a standing agenda item for bi-weekly assurance team meetings.

Myron D. Fisher, CPA, CGMA

Baldwin CPAs, PLLC, Member. As the Firm’s Leader of Assurance Services, Myron Fisher brings more than 25 years of assurance and tax experience to the Firm. Myron leads assurance engagements including financial statement audits, reviews and compilations, ERISA employee benefit plan audits and other agreed-upon procedures engagements. He performs assurance services for private businesses, governmental clients, non-profit organizations, financial institutions, construction clients, and medical institutions. Myron also serves as the firm’s Quality Control Director.

In addition to assurance engagements, Myron has been very involved in the Kentucky Peer Review program. Myron has worked with the AICPA Peer Review Enhanced Oversight Program. Myron performs engagement and system peer reviews throughout the state of Kentucky. He enjoys working with other CPA firms in helping them with achieving a high level of compliance in their assurance practice.Over the years, Myron has been tremendously involved in both the accounting community and the local community. He has served as a member of the KyCPA Peer Review Committee and currently serves on the Peer Review Alliance Program with the Illinois Society of CPAs. Myron has also served as a member of the KyCPA Board of Directors and is an Audit Quality Partner for the AICPA Employee Benefit Plan Audit Quality Center. In his local community, Myron has served as the Chair of the Richmond Chamber of Commerce from 2016 to 2017 and is currently a member of the Central Kentucky Regional Airport Board.

How to add more value to your final audit meetings with clients

internal audit assessment

Audit services are traditionally viewed as compliance requirements by regulators or a way to instill confidence with a company’s investors. As a result, the focus of the CFO might shift to minimizing costs and efforts in order to comply with the required audits.

During the limited interactions with the audit committee or the company’s CFO, how can auditors demonstrate their value as a trusted advisor that goes beyond traditional assurance to delivering valuable insights? How do auditors build strong working relationships with respective clients for future audit engagements?

Enhanced Audit Findings Reports or Presentations

Leveraging MindBridge Ai Auditor, the audit team can enhance their Audit Findings Report or Audit Committee Presentations to include visualizations, reports, and trends analysis to better communicate the work performed by the audit team. Reports can be tailored to include areas that are beyond formal requirements to areas that would be of most interest to the audit committee or that the CFO would be most concerned about. This helps create an open and data-driven dialogue with clients regarding their business and financial risk areas with related observations and findings.

As Ai Auditor uses business rules, statistical models, and machine learning to risk score each transaction, it allows the audit team to present the breakdown of high risk, medium risk, and low-risk transactions to clients, by percentage and dollar value. The risk can further be presented by specific accounts that could indicate a higher risk or a time period of higher risks. Stratifying this risk by time, Ai Auditor further breaks down risk by month, weeks, and days to identify unusual periods of activity. The risk graphs can be exported and used in any audit presentations to show clients where high-risk transactions are by account, time period, or any of their interests.

The Trends and Ratios functions help analyze key performance indicators and trends within the client’s business. MindBridge uses a proprietary implementation of an algorithm called SARIMA, developing an expected range based on the historical data of the company and comparing it to actual results to identify any outliers. This information is plotted onto a graph within the “Trending’s” tab that can be downloaded and incorporated in audit presentations. Key ratios such as Liquidity (Current Ratios, Quick Ratios, etc.), Profitability (Return on Assets, GPM, etc.) and Leverage (Asset turnover, Debt to Equity, etc.) can be computed and plotted onto graphics within the tool and then saved to be used as a part of the audit presentation. With multi-year data comparisons, audit teams can show their clients which key ratios are changing year over year or month over month. They can also identify any key ratio deviations and potential causes associated.

Better client discussions 

Traditional Audit Closing meetings usually involve a presentation from the audit partner and team on the Audit Strategy, Audit Status, key audit findings, and any areas of interest. Given the limited time that the audit team has in front of the CFO or audit committee, technology such as Ai Auditor can be leveraged to articulate value beyond audit requirements to those of business insights and financial risk observations.

Using the Financial Analysis Template provided by MindBridge, Trends and Ratios can be used to explain key findings and trends related to the account of interest and. For example, Gross Profit Margin can be computed using Ai Auditor’s Trends functionality, incorporating SARIMA and leveraging multi-year data to develop an expected range of Gross Profit Margin within the data set. With multi-year data points showing on the same graph, auditors can identify and show any ratio outliers to clients.

These types of data-driven insights help client conversations to be more targeted. For example: “the gross profit margin for July 2018 is outside the expected range per our AI analysis. We identified the issues to be related to increased material costs during the first quarter of the year impacting the gross profit margin.”

internal audit team

Ai Auditor’s ability to risk assess 100% of the company’s GL data allows the audit team to show their clients the risk breakdown of their transaction data. By illustrating audit work performed to investigate these high-risk or medium-risk transactions, the conversation with the client can be enhanced to: “The audit team identified $100M in high transactions, which represents 27% of the ledger. The high-risk transactions were identified as related party transactions that occurred near year-end. Upon further investigation by the audit team, all related party transactions were reviewed, and no issues were identified.”

internal audit financial audit

In addition, the Ai Auditor risk assessment can also be adjusted to show risk by account. Under the Reporting function, a report can be downloaded and imported into any audit presentation. The risk by account chart breaks down each grouping found within the ledger and risk associated with that grouping. From there, the audit team can show clients key areas of risk as it relates to a specific account.

Similarly, the risk can also be filtered by the users who are entering the accounting transaction. The client might be interested in a specific user, with most of their posted transactions identified as high risk. A high risk by the user could indicate a potential control risk: “We analyzed controls based on the user’s function and identified control issues for the following users: User 123, User XYZ, and User ABC. These users were sharing passwords and recording transactions outside of the scope of their duties. Further, we identified User 456 may lack the appropriate training based on the transactions being entered.”

internal it audit

Other opportunities

Ai Auditor helps auditors to provide their client with more confidence over the organization’s financial information. Auditors can become trusted advisors for their clients by leveraging technology to identify risky transactions, areas of potential control risks, and any downward trends.

Being a trusted advisor creates an open dialogue with clients and can lead to other opportunities for the audit firm, such as risk advisory, accounting policy advisory, tax, forensics and more, all while keeping Auditor Independence in mind. With the power of machine learning and AI analysis, Ai Auditor can provide clients new perspectives of their businesses unlike anything they have ever seen before.

See Ai Auditor in action now by watching this 4-minute demo

How AI restores the public’s trust in the fiscal accountability of governments

Handshake illustration between government and public

The public’s trust of governmental budgeting, fiscal management, and reporting is at an all-time low, especially in the aftermath of the 2008 financial crisis, where only four out of ten people in OECD countries expressed confidence in their government. Cases of fraud, bid-rigging, and pay-to-play are never far from the headlines, and have continued to undermine trust in the public servants and elected officials tasked to oversee the complex work of managing government finances.

A large portion of this mistrust can be attributed to the struggle that government finance managers and auditors are facing in analyzing the increasing amount of financial data. Current financial control and audit techniques, including legislated audit requirements, are not able to scale to keep pace with the massive data explosion coming from their own accounting, payroll, and expense management systems. One government response to this issue, open data, enables a sense of fiscal transparency with the public but it doesn’t replace the rigorous professional analysis required to identify fraud, errors, and omissions in large amounts of data.

Enter artificial intelligence (AI). Leveraging a mix of machine learning and natural language processing (NLP) techniques, AI can help government auditors and finance officials deal with the massive amounts of data they are required to professionally process in a timely fashion to meet their fiduciary responsibilities to their taxpayers, which in turn will help restore the public’s trust in government.

The financial data explosion in government

Imagine you are running a government department that has 150 different operational entities but only have the resources to audit four or five a year. That’s a massive financial blind spot that will make your comptroller or CFO lose sleep at night. It’s not a question of whether fraud or errors are occurring, it’s a question of when the news will break that they have happened.

Equally challenging is the government audit department that must perform 150 audits per year by legislative mandate. With so many audits required, where is the time to dive into different areas of analysis and reveal insights that can help lead to improved service to the public?

PwC estimated that 18 zettabytes of financial information was created globally last year. Visualize a standard pitcher of water as a byte. One zettabyte is all the water on planet earth.  PwC also estimates that only 0.5% of that data is analyzed, and it’s in this unreviewed data that the errors, omissions, and frauds that the press reports on is occurring.

Let’s also be clear on what governments are catching in the data they are analyzing. Current financial controls, audit methodologies, and analytics catch about 3% of the total global fraud as estimated by the Association of Certified Fraud Examiners. Tips, on the other hand, uncover 50% of the major corruption cases.

Current government processes and professionals are not catching the errors faster than whistle-blowers are reporting it. So it’s not surprising that governments are perceived as being ineffective in how they deal with the detection of fraud and errors in their financial statements.

Fraud hotlines & open data: First steps

Governments have responded to this issue in a number of ways. One of the first has been the rapid rollout of fraud hotlines, driven by statistics on how fraud has been uncovered to date in the majority of cases.

The other approach has been to broadly publish budget, financial, and audit reports to the public. This approach has been tied to the open data/open government movement and has been seen by many as a more citizen-inclusive approach to solving this problem. The idea is, by releasing all the data to the public, concerned citizens can dig into finances and find errors and mistakes to help share the burden of analysis.

This refreshing approach to transparency in government has its benefits, including seeing governments become better stewards of their own data, and being more open to feedback. However, the open data movement hasn’t been able to put an end to the public’s mistrust as first promised. Missteps in areas such as the standardization of data formats and APIs, the frequency of updates to the released data sets and the scope of the data released has limited analysis by external parties.

In addition, as larger data sets are released, individuals are no longer able to perform a full analysis of the data in a single pass. Microsoft Excel, the world’s most widely available financial analysis tool, has a million-row limit for data processing, and other available data science and accounting tools and resources are out of reach for the majority of citizens. The data might be readily available, but the professional tools and skills are not.

Artificial intelligence: Creating government efficiencies

Artificial intelligence is part of what is being dubbed the Fourth Industrial Revolution and has the ability to dramatically improve the efficiency of organizations. In the financial and audit worlds, AI offers an approach that includes:

  1. Continuously ingesting large amounts of financial data from different sources
  2. Risk assessing 100% of all transactions against all current and past data
  3. Indexing all transactions in a way that can be interrogated with common language questions, such as “Show me all transactions with high risk at the end of 2018”
  4. Producing reports that allow auditors and financial officers to extract insights into how their government is operating, and take corrective or reinforcing actions accordingly

In this way, AI builds on what the open data movement has started, as it offers a means of democratizing the application of complex analytics to governmental financial review.  Governments can now load and analyze all their financial data, applying the open government standard of transparency to both the data and the algorithms they are using, and then releasing the results for the public to review when completed.

AI solves the problem of the department with 150 potential audits and having the resources to run 4-5 audits only. AI can run continuously on every department and help to direct the limited resources to the departments that exhibit high risk instead of burning resources using round-robin audit approaches and random sampling of transactions to review.  For the departments not chosen for an audit, financial managers can be sent risk reports in each department allowing them to take corrective measures in advance of a future audit.

And for the organization facing 150 mandatory audits, AI can drive cost efficiencies as standard procedures can be automatically performed, freeing up auditor time for deeper interrogations of the data.

AI can also make fraud hotline tip review more efficient, namely the requirement that anonymous tipsters have to be convinced to give up their anonymity to prove the claim being made is true. Upon receiving a tip, an AI tool can be directed to review the data claimed at risk. This allows the financial data to speak for itself, relieving the tipster of having to reveal their identity early on in the risk assessment of the tip.

Artificial intelligence: Finding financial anomalies

So how does AI find anomalies in financial data and allow auditors and financial officers to search the data quickly? These capabilities are found in the application of machine learning and NLP.

Machine learning is a sub-field of artificial intelligence that focuses on the application of algorithms to large amounts of data to enable further insights. MindBridge Ai uses both supervised and unsupervised algorithms to risk rank all the financial transactions loaded into platform. Supervised algorithms are based on training data, and we developed an algorithm based on known patterns of fraud that was provided to us by forensic accountants.

Unsupervised algorithms are special, because they are developed to allow the data to speak for itself, meaning that transactions are clustered into neighborhoods of numbers that are interesting to accountants, such as rare connections between two accounts. These algorithms can also identify transactions that fall outside neighborhoods of numbers, called outliers.

artificial intelligence audit

These algorithms, run in concert with standard accounting rules and statistical techniques, such as Benford’s Law, allow us to risk score every transaction in a financial ledger. While this is done, the data is also indexed for rapid search capabilities, which brings us to the application of NLP.

NLP is another sub-field of AI and, in the accounting context, allows auditors and financial officers to ask questions of the data that has been risk ranked using machine learning, returning a list of risky transactions that fit the criteria.

ai and audit

Together, machine learning and NLP have been empirically tested to show that we can conservatively detect financial anomalies 10-30x better than current audit and financial analysis methodologies.

Artificial intelligence: Restoring public trust

The inability of government audit and financial departments to analyze 100% of the data in the government’s trust has been a major factor in its inability to spot financial anomalies. While fraud hotlines and open data techniques have been a step in the right direction, AI offers an opportunity for the government to actively pursue the detection of financial anomalies before whistle-blowers think to act on ethical and moral grounds.

Private sector audit firms are already turning to platforms such as MindBridge Ai Auditor, and over 40% of the top 100 audit firms in North America are currently engaged with us. In the public sector world, the auditors and financial officers in the Canadian and UK federal governments have already tested the MindBridge platform and measured the advantages of using AI against current techniques.

Students in accounting programs at over 60 universities in Canada, the UK, US, and Australia have also engaged in using Ai Auditor in their accounting courses. As AI-ready individuals move to becoming workers and taxpayers, they will demand that AI be employed by all levels of government to help in the detection of fraud, errors, and omissions in financial data. Citizens are already becoming aware of the capabilities of AI, as they hear about it every day in its application to autonomous vehicles and other government services, such as automated government decision making.

The Fourth Industrial Revolution is upon us, and there are significant benefits for governments in the early application of AI to detect financial anomalies to turn the tide on fraudsters and bad actors. Beating whistle-blowers to detect and mitigate fraud is an achievable goal through AI and will make major leaps towards restoring the public’s faith in a government’s ability to manage the public’s finances.

To learn more about our government solutions, including real use cases, visit our government finance page.

Giveaway: Win a digital assistance package for your firm

audit sampling tools

The world is changing and we’re all looking for ways to navigate the current crisis landscape together. That’s why we’ve partnered with Future FirmXeroPractice IgnitionKarbonFloat, and Ron Baker to offer you a chance to win a Digital Firm Assistance Package!

Valued at over CDN $13K, the Digital Firm Assistance Package provides the support, tools, and advice that allows your firm to try new technologies, learn from the experts, and plan your evolution to a stronger digital model.

This package includes:

  • A one-hour consulting call with one of our resident CPAs to answer questions on how to adopt AI for advisory services, mapping to firm methodology, and how to pitch AI to clients
  • 2 one-hour coaching calls from Future Firm to answer any questions you have about navigating a cloud-based accounting firm model
  • A premium white-glove Xero Kickoff Call with their Regional Director, Partner Consultant & Account Manager to understand your firm’s online accounting needs & objectives plus 2 meetings with their Partner Consultant to create a tailored Implementation Plan that includes recommendations to help you achieve those objectives
  • A free Xero partner account + special offers (which cannot be advertised) on Xero licenses based around the Implementation Plan
  • A free Float Gold Plan (which includes up to 50 licenses!) for 1 year, so that you can provide your clients with automated cloud-based cash flow forecasting services when they need it most
  • Karbon‘s premium, white-glove Full Service Onboarding service to get you trained and migrated to their cloud-based workflow management software in less than 30 days
  • 25% off your first year’s Practice Ignition annual subscription to help you engage and onboard clients remotely
  • A digital copy of Ron Baker & Ed Kless’ The Soul of Enterprise book

Every single entry receives some cool freebies, so check out the details on the contest entry page.

The Digital Firm Assistance Package will be awarded randomly to one firm by entering the draw below. Contest closes on April 21, 2020.

 

Enter now

 

Quality audit vs. efficiency: How technology bridges the gap

audit sampling techniques

As someone who has worked in big-firm transformational change for quite a while, I’ve often reflected on the perils of success and its ability to stand in the way of innovation and agility. We work really hard in transformation teams to articulate URGENCY, and NECESSITY, and ABSOLUTE DIRE NEED to transform. But no matter how creative we are, without a great deal of immediate pain, it is incredibly difficult to steer a new course for big ships that have been historically successful.

Undeniably, COVID-19 is a catalyst for urgent and mission-critical pivoting across most areas of professional services, and indeed business in general.

I’ve been checking in with many of my clients and industry colleagues over the last couple of weeks, seeing how I can help them, seeing if they’re ok. This has helped me learn a lot about how many audit firms across Australia and New Zealand are coping.

CLOSING
DECLINING
PROVIDING
THRIVING
CURRENT STATE
Hibernating or liquidating
Open (just), panic over decline in recurring revenue
Open and BAU (as far as the market is aware)
Open & thriving
REVENUE MIX
None
Traditional recurring engagements only
Mostly traditional recurring engagements
Maintained traditional recurring engagements, adding parallel services and /or opportunistic blue-sky work
CLIENT APPROACH
In the wind
Overwhelmed by client emotional burden
Reactive client emotional support
Proactive, deliberate and direct client management
WORKFLOW FOCUS
Nil
All client work reducing
Laser focus on core client deliverables
BAU on core + new (relevant) service offerings
STRATEGIC FOCUS
Nil
Holding breath, can’t see past next week
Wishing for the dust to settle
Planning for acceleration when the dust settles

Regardless of which state you and your firm fall into, no one will argue that ‘business as usual’ is no longer a thing. All those posters we’ve all seen about needing to embrace change seem to have come rushing at us all with force.

The push-pull between audit quality and efficiency

ai in internal audit

How are firms around the country reconciling the absolute mission-critical need to be agile, to adapt, to change rapidly while protecting their sole reason for existing: Audit quality?

Materiality

Many firms are considering their materiality levels. Are those that have always been used still appropriate in the current climate? If lowering them is most appropriate to capture risk properly, how will firms deal with the significant uptick in sampling effort required as a result?

Focus on fraud

artificial intelligence audit

Pressure – Employees within our client’s businesses will be under enormous stress, thinking about potential job loss, financial strain, and social distancing.

Opportunity – Management review may not be as vigilant due to distractions by the crisis and other management responsibilities, and internal controls may be circumvented in times of crisis for the reason of expediency to keep business processes operating.

So firms are considering how they can appropriately resource, looking more closely in areas that are ripe for fraud in these economic conditions – areas like payroll, termination payments, shrinkage of inventory, revenue recognition…anywhere where there’s not great segregation of duties, management override of controls, etc.

Big picture mindset

Following a normal process, one designed for ‘business as usual times,’ is just not sufficient in the current state of COVID-19, so firms need their auditors to step back and look at more of the big picture. Considering the broader context of what they’re doing, evaluating the effects of COVID-19 and surrounding behaviours on their risk assessments is critical for effective audits.  This requires perhaps more space and ‘thinking time’ than the normal production line of audit engagements so again, firms are contemplating the effect of this change on resources and profitability of current engagements.

Carrying on as normal is unacceptable. What was identified as the top risk when you did your audit planning and risk assessment­ —what you are auditing as you read this —is almost certainly not the top risk today.

Each of these considerations means a diversion from very structured and process-driven methodologies and practices that have been refined over the recent years to deal, in many cases, with the downwards fee pressure on audit engagements. And pivoting away from ingrained processes risks the need for more WIP and more resources.

As Tim Kendall, BDO National Leader for A&A shared with the AFR recently: These things coupled with any rigidity in ASIC’s views around current financial reporting time deadlines pose a significant risk to audit quality as firms are forced to squeeze engagements into a very tight delivery timeframe. (full AFR article HERE)

The key difference between those firms who are Closing, Declining, or Providing and those firms who are Thriving is simple – either an ongoing commitment to best-of-breed tech to support the most efficient and effective high quality audit engagement delivery OR an immediate prioritising of adoption of such. Or both.

Thriving firms already have, or are seeking to have, tech that provides ways to be more efficient AT THE SAME TIME as expanding the lens to have a broader contextual view of risk.

Read more

How auditors use AI-driven ratios to understand risk

Effective audit execution in remote work environments

Getting ready for AI-powered audit in 2020

Why the ICAEW Technology Accreditation Scheme matters to you

ICAEW Technology Accreditation for MindBridge

It should come as no surprise that the accounting software market is exploding. With increasing demands on chartered accountants to be smarter, faster, and more data-driven than their peers, we’re seeing massive growth in available tools, and the leading-edge technologies behind them.ICAEW Technology Accreditation logo

This new landscape means that we’re in an age of faster time-to-market, constant product evolution, and, with the adoption of AI, taking on new ways of doing things. That’s why it’s critical for vendors to ensure a high degree of testing and quality assurance behind their products and for accountancy firms to understand the technology being offered to them.

The ICAEW Technology Accreditation Scheme helps accounting firms take the guesswork out of choosing the best software solution and MindBridge Ai Auditor is the first and currently only data audit & analysis software solution provider to have gone through this rigorous evaluation methodology.

The ICAEW methodology

The Institute of Chartered Accountants in England and Wales (ICAEW) is a professional membership organization providing insight and leadership to the global accountancy and finance professions. With over 181,500 chartered accountants and students worldwide, ICAEW provides qualifications and professional development, insights and technical expertise, and protects the quality and integrity of these professions.

The ICAEW Technology Accreditation Scheme is a rigorous evaluation methodology that goes into a software company’s management structure and financials, software development details, customer satisfaction processes, and more. This typically entails all departments coming together to answer questions in support of the company’s ability to successfully deliver features, value, and support to users.

Why it matters

This accreditation gives current and future Ai Auditor customers every confidence about choosing and using our solution. This is important for the following reasons:

  • The ICAEW Technology Accreditation Scheme is an independent evaluation of software packages, giving you the confidence that Ai Auditor brings value to your practice
  • Completion of the accreditation involves the completion of detailed questions about our product, functionality, support processes, and corporate management, including an on-site visit by the ICAEW
  • All submissions are evaluated and verified by an independent top UK accountancy firm, RSM UK, who has the final say as to whether a product has passed the accreditation process
  • The Scheme’s independence is very important as it means software companies cannot simply pay to join the Scheme but must meet the required criteria laid out in the questionnaire

As Ai Auditor is the first and currently only data audit & analysis software solution provider to have gone through this evaluation methodology, we are uniquely positioned to deliver real value and support to audit practices.

Craig McLellan, manager of the ICAEW Technology Accreditation Scheme, has the final word: “We are delighted that MindBridge has been accredited by the ICAEW. With the ICAEW Technology Accreditation Scheme being the benchmark for software used by accountants in both the business and practice markets, we welcome industry and software companies in embracing a modern approach to finance and accountancy.”

Learn more about MindBridge Ai Auditor here.

How auditors use AI-driven financial ratios to understand risk

information about auditor

In times of great uncertainty, we all look for a crystal ball.

Also known as an orbuculum or crystal sphere, legend has it that a crystal ball is a fortune-telling object. But the use of crystal balls to predict the future is pseudoscience and there’s no evidence that they can validly predict the future.

Time and again, businesses and their advisors have proven that monitoring key performance indicators and ratios can be helpful to understand current business health and, some might say, predict future events. With the advent of artificial intelligence and machine learning, we now have the ability to augment this work with large amounts of data and perform complex calculations using an unprecedented number of variables to increase its accuracy.

MindBridge Ai Auditor gives this power to auditors, helping to evaluate financial health, discover trends in risk, and enabling better decision making.

Here’s a quick rundown on some ratios within Ai Auditor and how they can help.

 

Current ratio

The current ratio is a liquidity ratio used to evaluate a company’s ability to meet its short-term debt obligations by measuring the adequacy of the company’s current resources to cover its debt. To calculate, you divide current assets by current liabilities.

Companies in crisis will likely see their current ratio decrease as they draw down lines of credit to stockpile cash and use cash to maintain operations while revenue and accounts receivable decline. An example is Boeing drawing down its full $13.8B line of credit to stockpile cash to maintain operations and deal with the damage the airline industry is experiencing.

A healthy company has a current ratio of more than 2, whereas a company who is in trouble has a current ratio of less than 1.

 

Operating cash flow to sales ratio

Even with a healthy current ratio, cash and cash flow must be monitored because of uncertainty on accounts receivable and cash is key to the success and survival of any business. The operating cash flow to sales ratio indicates a company’s ability to generate cash from its sales.

Ideally, as sales increase, operating cash flow should increase by the same. However, in a time of crisis, accounts receivable may take unusually longer to collect as the market manages cash more carefully and takes longer to pay. An example of this ratio decreasing is the difficulty that oil producers across the world are facing as demand for oil plummets, supply increases, and oil companies have a more difficult time generating cash from their sales.

Though it is normal to see change in a period of change, the higher the ratio the better, and it should find a level of consistency over time.

 

Debt to equity ratio

The debt to equity ratio is an indicator of a company’s financial health. This ratio is indicative of the company’s ability to meet financing obligations as well as its financing structure.

It will be normal in a crisis to see this ratio increase as companies borrow heavily against their lines of credit and other debt. Investors will also be hesitant to provide more equity in a crisis especially as the markets are in decline. Further, raising money via equity offerings at a time of depressed markets is expensive to businesses. This causes companies to rely on debt and since increasing debt brings an increasing ratio, lenders will eventually consider it unhealthy.

This is part of the reason that the Small Business Administration announced additional small business support of up to $2M loans to small businesses who qualify during the coronavirus (COVID-19) epidemic.

A ratio of about 1 is optimal where a ratio higher than 2 is considered to be unhealthy.

 

Cash flow to debt ratio

Cash flow is king to any business as no business can operate without an ability to pay their bills. The cash flow to debt ratio is often considered the best predictor of financial business failure. This ratio is calculated by dividing cash flow from operations by total debt. A higher ratio indicates a company is more able to cover its debt.

Often free cash flow is used rather than operating cash flow because this takes into account capital expenditures. With COVID-19 essentially grounding international air travel, airlines are seeing a huge decrease in cash flow to debt ratio, so much so that the airlines are seeking a $50B aid package from the US government.

A ratio higher than 1 is healthy but any value below 1 is indicative of an impending bankruptcy within a few years unless the company takes steps to improve its situation.

Another metric often used to predict potential bankruptcy is the Z-score, which is a combination of several financial ratios used to produce a single composite score.

 

What do these ratios have in common?

Other than the fact that they are in no way associated with crystal balls, they are very important to a business of any size in a time like this and they can be augmented and presented using MindBridge Ai Auditor.

As businesses create plans and seek advice from their advisors, Ai Auditor can present intuitive dashboards of ratios such as these (and more) by using a 100% complete set of general ledger data. In addition, by leveraging machine learning and AI, Ai Auditor can provide analytics of these ratios to evaluate deviations from expected ranges across 12 months of data. Additional analysis is also possible on more detailed ledger data such as accounts payable and accounts receivable ledgers.

 

So what’s with the crystal balls?

Whereas we have all been led to believe that the future-telling effect of crystal balls is pseudoscience—which very well may be true—there do exist approaches and high-tech tools that enable the use of massive data sets to help gain incremental clarity about the future.

Ai Auditor isn’t pseudoscience, it’s right here, right now.