the accounting homework solution

the accounting homework solution

Innovative Approaches to Solving Complex Accounting Problems

1. Introduction to Advanced Accounting Concepts

The primary purpose of accounting is to provide useful financial information to users. Accountants provide useful information primarily through measurement and reporting. Accountants are charged with the responsibility of applying a set of reporting and recognition standards to real-world economic events defined, measured, and classified by management. Inherent in the financial accounting function is some degree of uncertainty attributable to the judgmental nature of financial accounting. Government regulatory bodies, including the U.S. Congress and Securities and Exchange Commission, have focused an enormous amount of effort on promulgating rules to assist in narrowing measurement and classification flexibility. Despite best efforts, there will always be some measurement flexibility remaining embedded in those rules. The accounting principles employed today are derivatives of centuries of business concepts, practices, and experiences; they constitute a storehouse of corporate knowledge. All of these business experiences are represented in the accounting principles used in financial reporting.

This knowledge base (marked by professional judgment and flexibility) applies to an unlimited array of evolving and emerging real-world problems facing accounting practitioners. This knowledge from various knowledge sources has many faces. It may consist of accounting standards or principles learned in accounting courses, or the collective experiences of former auditing encounters as an audit staff member. That knowledge may consist of the management accounting topics discussed in cost accounting courses, or the business and legal knowledge gained from labor relations courses. In addition to the subject matter knowledge gained from all of the diverse business disciplines, there are other types of knowledge that are required by practicing accountants. Knowledge derived from computer hardware and software skills and general information technology systems are essential in the rapid evolution of tools and information technology. Society also provides knowledge from its legal and ethical systems, and many organizations provide the manner in which to acquire that knowledge. All of the knowledge, including relevant accounting content, can be approached from various advanced accounting perspectives. These perspectives are the subject of this book. The challenging environment of advanced accounting needs a variety of relevant viewpoints to address the complex problems associated with the type of business dealings that fall within the scope of this book.

2. Analytical Techniques for Financial Statement Analysis

As in any other area of accounting, the use of analytical procedures in financial statement analysis has increased remarkably in recent years. Sophisticated analytical models have been developed and have provided insights into the choice of accounting procedures and other complex accounting issues. This section examines selected innovative models that extend the scope of traditional techniques to account for problems that have heretofore been recognized but not satisfactorily addressed with existing measures. Our focus is on returned measures of wealth, return, and risk.

Rapid assessment of the performance or condition of a firm is important. As access to public information and computing power has increased, many financial statement analysis models have been developed to help users assess the wealth or current performance of a firm. Still, most of the widely-used models conceptualize the problem as one of predicting less-detailed measures of either future stock returns or future profits. Furthermore, the models are largely based on readily available accounting data and can, therefore, be derived easily. It is no surprise then that currently most financial statement analysis involves straightforward, regressive calculation of commonly employed measures of performance and related risks.

3. Utilizing Technology in Accounting Solutions

Materiality is a long-contentious topic among practicing accountants, auditors, and regulators regarding its proper use, particularly for certain line items within financial statements. The application of materiality reporting for professional auditing standards requires the capacity to aggregate and organize financial information. Taming the complexity of accounting normalizations to more simply and understandably present enterprise financial performance is both a beginning to addressing the more complex business issues covered by GAAP and a foundation for teaching a more cogent link between financial statements and business processes.

Presently, the technology capable of automatically generating detailed internal financial reports without add-on calculations is beyond the capability of frontline financial reporting systems. However, the ledger is capable of providing detailed and projectable line items to automate such surplus accounting systems either through reading of account balances or parsing aggregates. Once several business cycles are automated, a library of automated templates will be developed for public and commercial enterprises that can be replicated, reducing the associated capital buildout in subsequent implementations. Tremendous advantages exist for early technology adopters who can utilize these financial reporting solutions to restate and reframe reams of cumbersome and largely unreadable disclosures buried within recent Commission filings.

4. Case Studies and Real-World Applications

For accounting educators to change the ways their students learn, the development, dissemination, and implementation of new teaching practices, also known as pedagogical innovation, is necessary. Innovative approaches to solving complex accounting problems are needed. Meaningful accounting education involves teaching students how to make accounting decisions under conflicting and poorly defined conditions. Pedagogical innovation has been recognized as a significant driving force behind modern education and lifelong learning and is needed to address the call in higher education for personalization, effectiveness, quality, and innovation. Consequently, innovative accounting education requires innovative educators who are committed to changing the delivery of their courses to achieve the stated goals of accounting programs.

This book aims to provide accounting educators with guidance on incorporating innovative approaches into their accounting courses. The innovative approaches are demonstrated through various actual classroom examples and opinion pieces of how accounting educators have or plan to change their accounting courses to incorporate new or innovative teaching techniques in response to changes in business organizations and the accounting profession. This chapter accomplishes the stated objectives by suggesting 50 innovative teaching tips in the form of opinion and experience pieces. With the emergence of accounting as a critical part of business organizations, it is especially important for faculty teaching accounting to identify new and innovative methods of instruction.

5. Conclusion and Future Trends in Accounting

The objective of this article is to examine the current status of artificial intelligence applications in accounting and suggest how it can be improved. The first part of the article reviews the main approaches to solving complex accounting problems, including mathematical programming heuristics, statistical methods, and machine learning methods. The second part of the article demonstrates the need for innovative approaches in accounting using a few typical accounting problems. Innovative AI and big data applications, either administrative such as accounting, financial, marketing, human resources, or industrial such as manufacturing and logistics, are leading to increased interest from researchers on how these methods can be used to solve problems in these domains. Even in consulting applications, business experts are combining business rules with soft computing tools.

The role and importance of these approaches is still debated in different areas of accounting. There are at least two reasons for this debate. First, the output of an accounting system information is believed to require numerical precision (‘Augustinian’ notion). Second, the output should be plausible in a human observer’s judgment (‘Probabilistic’ notion). Influential models in both approaches have their origin in economic modeling and are based on aggregating individual behaviors. Although this is not a matter of ‘engineering’, one can come out with a trade-off model. Our purpose follows developing such a model. We put aside the hard-to-get numerical precision or other devil-in-the-details problems. Instead, we focus on exploiting vast amounts of data coined Big Data. We try to build some kind of confident-acceptable risk-based measures of our objectives stated in this paper. With real applications at hand, there are many trading issues to investigate. Although these data-based performances seem to encourage the world of data science approach, there are a lot of methodological issues and constraints to becoming a standard procedure.

That way, we suggest big data research questions be carried on from the accounting domain by trying to improve degrees of plausibility while ensuring consistency and stability. The rest of the paper is as follows: Section contains state-of-the-art; First a survey of existing methods in accounting literature that is most related to our study: We separately handle two categories – heuristics search methods and statistical methods; Section contains the need for innovative AI methods in accounting with a few typical problems; Section concludes the article with a discussion on the possible further directions and their implications for AI.