The Securities and Exchange Commission’s Accounting Quality Model, a.k.a. Robocop, is a potential game changer for the SEC and for filers of XBRL. The SEC now has the ability to electronically examine each and every file submitted through the EDGAR system looking beyond XBRL acceptance to patterns or anomalies that could trigger closer inspection by SEC enforcement teams. In this article, we will examine what the Accounting Quality Model is and what is its purpose. We will also look at the steps preparers should take given the SEC’s analytical approach filed data.
Who is Craig Lewis and what is the Accounting Quality Model?
Craig Lewis joined the SEC as Economic Fellow in 2011 and soon after was appointed Chief Economist and Director of the Division of Risk, Strategy, and Financial Innovation. Dr. Lewis came to the SEC from Vanderbilt University with a charge to improve the SEC’s use of data. To that end, he created several new approaches to data within the SEC. In his own words,
“The Division of Risk, Strategy and Financial Innovation, or “RSFI”, was formed, in part, to integrate rigorous data analytics into the core mission of the SEC. Often referred to as the SEC’s “think tank,” RSFI consists of highly trained staff from a variety of backgrounds with a deep knowledge of the financial industry and markets.”
In order to accomplish the core mission, Lewis and his team created risk assessment models, a data warehouse and a set of risk assessment tools to analyze the data. One of the many outcomes from his work is the Accounting Quality Model.
What is the Accounting Quality Model?
In a recent speech, Dr. Lewis indicated that “At its core, AQM is a structured analytic model that takes flier information and identifies outliers and things that stick out by the type of disclosures being made and uses that data as a means to better understand our (SEC) filer space.” It should be noted that the AQM was not named the Accounting Fraud Detector, although it does play a role in identifying high risk companies.
Lewis goes on to describe the functionality and purpose of the AQM
“As you know, the SEC has a veritable treasure trove of information from various registrant filings. We are mining that rich vein of information and are applying the same quantitative approach to develop various ways to evaluate registrant filings and search for potential areas of risk. While we have several projects in development, we are particularly excited about what we call an “Accounting Quality Model” (AQM). This model is being designed to provide a set of quantitative analytics that could be used across the SEC to assess the degree to which registrants’ financial statements appear anomalous.”
So what exactly does the AQM look for? Although the SEC will not specifically say, here are a few possibilities:
|Earnings Management||The AQM seeks to find companies who attempt to smooth earnings in periods where performance is either much greater or such less than prior periods relative to the company performance and industry performance.|
|Ratios out of line with industry||For example, the model may flag a company whose margins are much greater than the industry norm.|
|Discretionary Accruals||The difference between free cash flow and reported net income is made up of accruals. Non-discretionary accruals such as depreciation are removed, exposing management’s discretionary adjustments. The AQM attempts to measure this and create a risk index for possible further analysis.|
|XBRL errors and extensions||Any XBRL error allowed to enter into the SEC’s EDGAR system is identified and assessed for risk. The thought is that companies not paying attention to the details of XBRL may not be paying attention to other factors and therefore carry more risk. Extensions can also trigger additional attention especially when industry accepted tags are available for use. Being different but compliant is fine but will add to your score in the AQM|
|Frequent changes in outside auditors||Possible additional risk points will add to the score of an SEC filer as frequent changes may signal conflict with accounting decisions made by management.|
|Prior SEC actions related to the company||Additional risk points will most likely be added to the score of an SEC filer for prior SEC enforcement actions.|
Once an overall number or rating is established for each return, the return may be referred to an appropriate division within the SEC for further review.
Although the AQM has already led to at least seven SEC actions for fraudulent activities, Lewis insists that the model is not designed specifically to detect fraud. Rather, the AQM’s goal is to improve the quality of financial information reported to the SEC by allowing the regulator to comment more quickly and comprehensively about reporting that needs improvement.
The SEC does not, according to Lewis, intend to publish the criteria within the AQM that leads to a high risk score. The “special sauce” will remain an evolving secret as the SEC identifies reporting tendencies both good and bad filings.
What are the XBRL filing Implications?
Here are a few things to keep in mind when filing with the SEC:
As always, choosing a high quality XBRL vendor such as DataTracks will help to keep you and your filings as error free as possible. DataTracks is here to help you every step of the way to excellence in XBRL filing and to adhere to SEC best practices.
Must See / Must Read Resources:
2013 XBRL US National Conference Keynote: “SEC Chief Economist View on XBRL” Chief Economist and Director of the Division of Risk, Strategy, and Financial Innovation
https://www.youtube.com/watch?v=AYq8o4V7sTk Published on Sep 28, 2013
Risk Modeling at the SEC: The Accounting Quality Model, Speech given to the Financial Executives International Finance and Technology Committee, December 2012.
Editor’s note: Craig Lewis resigned from the SEC on May 2, 2014 after three years with the SEC to return to his position at Vanderbilt University.
DataTracks US is part of DataTracks Services Limited, leaders worldwide in preparation of financial statements in EDGAR HTML, XBRL and iXBRL formats for filing with regulators. DataTracks prepares more than 12,000 XBRL statements annually for filing with regulators such as SEC in the United States, HMRC in the United Kingdom, Revenue in Ireland and MCA in India.
The views expressed are that of the author’s and DataTracks is not responsible for the contents or views expressed therein. If any part of this blog is incorrect, inappropriate or violates the IP rights of any person or organization, please alert us at email@example.com. We will take immediate action to correct any violation.