This resource guide discusses the application of MindBridge for Review engagements.
MindBridge is not responsible for any errors or omissions or for the results obtained from the use of this information. All information in this site is provided "as is", with no guarantee of completeness, accuracy, timeliness, or of the results obtained from the use of this information
We’ve put together this practical guide so you have the top resources and documents at your fingertips.
This guide includes:
- Analytical Procedures
- Documentation and Evidence
- Appendix A: MindBridge Review Engagement Checklist
- How to get help
The accountant’s objectives in performing a review engagement are achieved primarily through analytical procedures and inquiry. Traditionally, analytical procedures performed in these engagements were limited to simple point-in-time comparisons of balances and variances as of a reporting date. Inquiries of management were predictable and contained only surface-level insights, which limited the ability of the accountant to determine whether a material misstatement may exist in the financial statements.
MindBridge empowers accountants to enhance their analytical capabilities by analyzing the underlying data contained in the financial statements. The use of advanced analytics, such as multivariate regression, statistical analyses, and data visualization, provides insights that improve the sufficiency and appropriateness of review evidence. This document outlines the application of advanced data analytics to AR-C 90 Review of Financial Statements.
Reliability of Data
Before relying on analytics, the engagement team must gain confidence over the completeness and accuracy of data provided, which forms the basis of your engagement. This can be done while reconciling the financial statements to the accounting records, as required in paragraph 41.
Any inconsistencies within the data should be documented and reconciled where appropriate. If the data is still able to be relied upon for your analysis, consider any impacts this may have on areas of the financial statements that may contain a material misstatement.
Understanding the Entity
In planning the engagement, accountants are required to obtain an understanding of the entity, as well as knowledge of the industry in which the entity operates. Understanding the entity encompasses a general understanding of the entity’s organization, operating characteristics, and nature of assets, liabilities, revenues, and expenses. Such an understanding allows the accountant to determine which areas in the financial statements are more likely to contain material misstatements.
To obtain an understanding of the business and potential areas likely to contain a misstatement, consider examining changes in trends and relationships within the data underlying the financial statements.
Analyzing the transactional activity that underlies the period-end account balances helps uncover key trends or major events critical to your engagement team and helps identify relationships between financial and non-financial data. These same analytical procedures may be used as review evidence once you have determined areas material to the users of the statements.
The accountant should design and perform analytical procedures and inquiries to address all material items in the financial statements and areas in the financial statements where the accountant believes there are increased risks of material misstatement.
To appropriately scope your engagement, enter materiality as determined by the engagement team using your understanding of the entity. Materiality can be entered and edited at any point post-analysis if you become aware of factors that would require a change.
Learn more about materiality.
Scoping the Analysis
Too often, engagement teams rely on work performed in previous periods. This approach generally results in either:
- The identification of risks that may no longer be considered material to the users, or
- An inadequate detection of risk in the current year.
The former results in an inefficient use of the engagement’s team time, while the latter may lead to providing an inappropriate conclusion on the review report.
To facilitate identifying scoped-in accounts, MindBridge can automatically scope quantitatively material balances based on user input. Additionally, a user may overlay their judgment to identify areas that are qualitatively material for areas with a higher risk of material misstatement.
Learn more about account scoping.
Increased Risk of Material Misstatement
Analyzing the general ledger will help to surface indicators that risk of material misstatement may exist. These may either be standard rules-based tests, statistical analysis, or machine learning algorithms to aid in anomaly detection. The results of these analytics may be quantified to provide further insight and explain what specific risks exist within the financial statements.
This summary dashboard will allow you to view the full spectrum of tests and areas of identified risks. Additionally, you may filter the view on various criteria identified within the data ingestion phase, and can focus specifically on analytics available for accounts that were included in your scoping decisions.
Completion of Preliminary Analytical Procedures
Once the analysis has been scoped, MindBridge offers a report export that summarizes the scoped accounts, including in-line commentary from preliminary discussions between the engagement team and the client.
The primary sources of evidence in a review engagement are analytical procedures and inquiries of management; therefore, it is imperative that you verify the reliability of the data before performing any analytical procedures. Analytical procedures may range from simple comparisons of information to more complex analyses, and can be performed at either the financial statement or account level.
Exploration of Client Data
The application material to AR-C 90 discusses performing analytical procedures on disaggregated revenue data, which may include revenue reported by month, product line, or operating segment, as compared to prior periods. An accountant may choose to disaggregate any account grouping with properly labeled data to identify specific trends not available at the account level. These trends can also be compared to the same disaggregated data from prior periods.
Additionally, the engagement team may choose to create a trended view of ratios relevant to their client to understand relationships between accounts.
As part of developing analytical procedures, accountants should compare recorded amounts or ratios to expectations developed by the accountant. Expectations are generally developed through identifying and using relationships that are reasonably expected to exist, based on the accountant’s understanding of the entity and industry in which it operates. Furthermore, the accountant should determine the acceptable difference between recorded amounts and expected values (which would require no further investigation), and compare the recorded amounts with expectations.
Analyzing detailed activity for the engagement allows the accountant to understand typical trends and develop informed expectations. Comparing detailed activity across multiple periods may also allow for the application of machine learning regression algorithms. These sophisticated algorithms can help provide expected balances and ranges based on historical information, as well as identify exceptions that may require additional investigation or inquiry.
Inquiries of Management
In addition to inquiries driven from the visualizations above, exploring the Risk Overview and Data Table dashboard yields additional insights about unusual or anomalous activity. Filtering criteria are available on the Data Table to narrow the population to include or exclude relevant factors for your engagement.
Although inquiries will vary depending on the entity and the industry, inquiries are required for significant, unusual, or complex transactions, events, or matters that have affected or may affect the entity’s financial statements.
Additionally, the accountant can evaluate not only the significant journal entries, but all journal entries or adjustments made to the financial statements throughout the year. Evaluating the entire population helps the accountant understand which adjustments are typical for the organization and which may appear unusual.
Documentation and Evidence
For all scoped-in accounts, reports may be generated that aggregate all applicable trends, ratios, and selected transactions into a PDF on a per-grouping basis. You may also add in-line commentary within the report to support documenting inquiries with management throughout the engagement.
Additionally, all visualizations within MindBridge can be exported to an .xlsx file, including the raw data in most instances. Export these visualizations to help support communications with management or to append the information to existing review evidence documented elsewhere.
After evaluating the evidence collected in analytical procedures and inquiries of management, you may choose to adjust or reclassify balances on the financial statements. You can then import these entries into MindBridge to facilitate final analytics and ensure that account balances reconcile to issued financial statements.
Appendix A: MindBridge Review Engagement Checklist
- Request data (refer to data checklists)
- Load/connect data, including all optional columns to be used for analytics
- Verify integrity of data with completeness checks
- Perform preliminary analytics using Financial Statement annotations
- Explore data on risk overview to identify areas likely to contain a misstatement
- Input materiality
- Scope material accounts and accounts likely to contain a material misstatement
- Create planning analytics report to summarize preliminary analytics
- Explore relevant Trends for scoped-in accounts by drilling down from the Financial Statement tab
- Create ratios specific to your client
- Identify significant or unusual activity through the Data Table, specifically transactions towards the end of the reporting period
- Generate and edit significant account reports for relevant inquiries and supporting documentation
- Export significant account reports for scoped-in accounts
- Import adjusting and reclassifying entries to perform final analytics
How to get help
Learn about the types of support available, including:
- A Knowledge Base for step-by-step instructions
- Live Chat for a quick response
- Get Assistance tickets for data inquiries
- MindBridge Academy for courses at your fingertips