Reporting financial information requires not only accuracy but also attention to possible qualitative issues that will affect decisions made in the future. To understand how various issues influence the opinion and choices analysts make, it is important to explore the difference between the quality of reported results and financial reporting quality. Also, it is imperative to identify warning signs associated with the analysis of financial statements and evaluate the extent to which the presentation of financial statements influences analysts’ decisions.
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Financial statement analysis
Financial reporting quality and the quality of reported results differ in several ways. On the one hand, the former implies the information that institutions use for making financial decisions, the real representation of an economic position in which a company finds itself, and the compliance with standards. On the other hand, the latter represents the quality of earnings that imply sustainable activities, adequate results, and increases in the value of an organization. It is notable that financial reporting quality and earnings quality are interrelated and can influence analysts’ opinions. For instance, the high quality of financial reporting plays a role in enabling the assessment while the high quality of earnings increases the value of a company. However, low financial reporting limits the assessment of earnings’ quality while the low quality of earnings decreases the value that a company has.
When it comes to different problems associated with financial statements, there are several aspects to consider. First, in revenue recognition, it is essential to implement such analytical procedures as examining the policies of accounting to make conclusions about how a company approaches its policies. Also, an analyst can look at revenue relationships and assess the turnover of assets. Second, when dealing with inventory, analysts should look at turnover, problems in inventory management, overstated net profits, and so on. Third, detecting long-lived assets is possible by comparing policies with industries’ practices, cross-checking asset turnover, and evaluating policies for long-term assets.
Apart from issues that appear in financial statements and differences in the financial quality and the quality of reported results, the presentation of financial statements also has an impact on analysts’ decisions. When choosing a presentation method, a company has to decide what information should be included and how to present it, for example, should the positive aspects of performance be emphasized or whether irrelevant details or “boilerplate” can be overlooked to preserve the cohesiveness of reports (EY, 2014, p. 3). In general, analysts will value reports that include all of the required disclosures and some mentions of positive and negative aspects of performance while overlooking the disclosure overload, which may be confusing.
Thus, when a financial report is of high quality, the assessment that analysts conduct will be successful in measuring all necessary variables such as profitability, liquidity, cash flow, company-wide efficiency, and others (“Financial statement analysis,” 2017). If the information presented in statements is skewed or is over-abundant, analysts may find it hard to complete the required measurements and will experience difficulties in filtering through the unnecessary data that adds no value. To improve the quality of disclosed information, organizations should work on flexibility, relevance, streamlining, and filtering what they present in financial statements (Center for Audit Quality, 2012). Establishing a benchmark for applying judgment on which data will be relevant and which will not is the desired method for reaching the high quality of financial statements and allow analysts to make decisions that have not been hindered by unnecessary information.
Center for Audit Quality. (2012). Financial statement disclosure effectiveness: Forum observations summary. Web.
EY. (2014). Improving disclosure effectiveness. Web.
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Financial statement analysis. (2017). Web.