Marina Narvaez - Business Librarian
Lora Lennertz - Data
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Covers: 1971-. This business and trade database indexes and offers full text for U.S. and international academic and trade journals covering business and economic conditions, accounting, finance, corporate strategies, management techniques, as well as competitive and product information.
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Accounting for Business by
This book is not an introduction to accounting. It is an explanation of how accounting is used for pursuing business success and avoiding failure. All types of organizations keep some form of accounting records, whether it is an international conglomerate or a local charity concerned with the welfare of stray animals. The simple reason is that organizations do not want to go "bust" and they need to know how they can best understand and control the financial consequences of their activities. In addition, financial information enables organizations to strategize and make decisions that are in line with their mission and objectives. Much of the accounting information these organizations generate is provided to their stakeholders. Certain types of information are mandatory and legally regulated by regulatory bodies. International conglomerates must report to their stockholders, charities to their donors, and governments to the electorate. In this book, we concentrate on for-profit businesses, although most of our explanations and discussions can be applied to many types of organizations. In Chapter 1, we discuss different types of businesses and how this can determine the nature of the financial information that is generated and how it is used. We continue this theme in Chapter 2 that explains financial accounting, what is meant by that term, and how such information is used. Chapter 3 focuses on making business decisions internally. We explain the various decisions that businesses have to make. These can range from deciding on the price to charge for their products or services to downsizing or globalization. All of these internal decisions need financial information and this leads us to Chapter 4 Management Accounting. We explain the various techniques that can be used and how this financial information assists managers in decision-making. In our final chapter, we explain new developments that are taking place in and accounting and business and the effects they have on each area. Developments such as algorithms, blockchain, cryptocurrencies, and big data are not just jargon but impact what businesses do and how we account for them. In each chapter we provide straightforward explanations without the use of jargon. We also include copious references so that readers who wish to pursue a topic further can do so.
Analytics and Big Data for Accountants by
Analytics is the new force driving business. Tools have been created to measure program impacts and ROI, visualize data and business processes, and uncover the relationship between key performance indicators, many using the unprecedented amount of data now flowing into organizations. Featuring updated examples and surveys, this dynamic book covers leading-edge topics in analytics and finance. It is packed with useful tips and practical guidance you can apply immediately. This book prepares accountants to: Deal with major trends in predictive analytics, optimization, correlation of metrics, and big data. Interpret and manage new trends in analytics techniques affecting your organization. Use new tools for data analytics. Critically interpret analytics reports and advise decision makers.
Audit Analytics in the Financial Industry by
In Audit Analytics in the Financial Industry, editors Jun Dai, Miklos A. Vasarhelyi and Ann F. Medinets bring together a cast of expert contributors to explore ways to integrate Audit Analytics techniques into existing audit programs for the financial industry. Separated into six parts, the contributors take a variety of approaches to this exploration. In Part One, the contributors present two articles illustrating the process of applying Audit Analytics to solving audit problems. Part Two contains four studies that use various Audit Analytics techniques to discover fraud risks and potential frauds in the credit card sector. In Part Three, the chapter focus on the insurance sector and show the application of clustering techniques in auditing. Part Four includes two chapters on how to employ Audit Analytics in the transitory system for fraud/anomaly detection. Finally, Parts Five and Six illustrate the use of Audit Analytics to assess risk in the lawsuit and payment processes. For students, researchers, and professionals in the accounting sector, this is an unmissable read exploring the latest research in Audit Analytics.
Forensic Analytics by
Become the forensic analytics expert in your organization using effective and efficient data analysis tests to find anomalies, biases, and potential fraud--the updated new edition Forensic Analytics reviews the methods and techniques that forensic accountants can use to detect intentional and unintentional errors, fraud, and biases. This updated second edition shows accountants and auditors how analyzing their corporate or public sector data can highlight transactions, balances, or subsets of transactions or balances in need of attention. These tests are made up of a set of initial high-level overview tests followed by a series of more focused tests. These focused tests use a variety of quantitative methods including Benford's Law, outlier detection, the detection of duplicates, a comparison to benchmarks, time-series methods, risk-scoring, and sometimes simply statistical logic. The tests in the new edition include the newly developed vector variation score that quantifies the change in an array of data from one period to the next. The goals of the tests are to either produce a small sample of suspicious transactions, a small set of transaction groups, or a risk score related to individual transactions or a group of items. The new edition includes over two hundred figures. Each chapter, where applicable, includes one or more cases showing how the tests under discussion could have detected the fraud or anomalies. The new edition also includes two chapters each describing multi-million-dollar fraud schemes and the insights that can be learned from those examples. These interesting real-world examples help to make the text accessible and understandable for accounting professionals and accounting students without rigorous backgrounds in mathematics and statistics. Emphasizing practical applications, the new edition shows how to use either Excel or Access to run these analytics tests. The book also has some coverage on using Minitab, IDEA, R, and Tableau to run forensic-focused tests. The use of SAS and Power BI rounds out the software coverage. The software screenshots use the latest versions of the software available at the time of writing. This authoritative book: Describes the use of statistically-based techniques including Benford's Law, descriptive statistics, and the vector variation score to detect errors and anomalies Shows how to run most of the tests in Access and Excel, and other data analysis software packages for a small sample of the tests Applies the tests under review in each chapter to the same purchasing card data from a government entity Includes interesting cases studies throughout that are linked to the tests being reviewed. Includes two comprehensive case studies where data analytics could have detected the frauds before they reached multi-million-dollar levels Includes a continually-updated companion website with the data sets used in the chapters, the queries used in the chapters, extra coverage of some topics or cases, end of chapter questions, and end of chapter cases. Written by a prominent educator and researcher in forensic accounting and auditing, the new edition of Forensic Analytics: Methods and Techniques for Forensic Accounting Investigations is an essential resource for forensic accountants, auditors, comptrollers, fraud investigators, and graduate students.
Fraud and Fraud Detection: A Data Analytics Approach by
Detect fraud faster--no matter how well hidden--with IDEA automation Fraud and Fraud Detection takes an advanced approach to fraud management, providing step-by-step guidance on automating detection and forensics using CaseWare's IDEA software. The book begins by reviewing the major types of fraud, then details the specific computerized tests that can detect them. Readers will learn to use complex data analysis techniques, including automation scripts, allowing easier and more sensitive detection of anomalies that require further review. The companion website provides access to a demo version of IDEA, along with sample scripts that allow readers to immediately test the procedures from the book. Business systems' electronic databases have grown tremendously with the rise of big data, and will continue to increase at significant rates. Fraudulent transactions are easily hidden in these enormous datasets, but Fraud and Fraud Detection helps readers gain the data analytics skills that can bring these anomalies to light. Step-by-step instruction and practical advice provide the specific abilities that will enhance the audit and investigation process. Readers will learn to: Understand the different areas of fraud and their specific detection methods Identify anomalies and risk areas using computerized techniques Develop a step-by-step plan for detecting fraud through data analytics Utilize IDEA software to automate detection and identification procedures The delineation of detection techniques for each type of fraud makes this book a must-have for students and new fraud prevention professionals, and the step-by-step guidance to automation and complex analytics will prove useful for even experienced examiners. With datasets growing exponentially, increasing both the speed and sensitivity of detection helps fraud professionals stay ahead of the game. Fraud and Fraud Detection is a guide to more efficient, more effective fraud identification.
Fraud Data Analytics Methodology by
Uncover hidden fraud and red flags using efficient data analytics Fraud Data Analytics Methodology addresses the need for clear, reliable fraud detection with a solid framework for a robust data analytic plan. By combining fraud risk assessment and fraud data analytics, you'll be able to better identify and respond to the risk of fraud in your audits. Proven techniques help you identify signs of fraud hidden deep within company databases, and strategic guidance demonstrates how to build data interrogation search routines into your fraud risk assessment to locate red flags and fraudulent transactions. These methodologies require no advanced software skills, and are easily implemented and integrated into any existing audit program. Professional standards now require all audits to include data analytics, and this informative guide shows you how to leverage this critical tool for recognizing fraud in today's core business systems. Fraud cannot be detected through audit unless the sample contains a fraudulent transaction. This book explores methodologies that allow you to locate transactions that should undergo audit testing. Locate hidden signs of fraud Build a holistic fraud data analytic plan Identify red flags that lead to fraudulent transactions Build efficient data interrogation into your audit plan Incorporating data analytics into your audit program is not about reinventing the wheel. A good auditor must make use of every tool available, and recent advances in analytics have made it accessible to everyone, at any level of IT proficiency. When the old methods are no longer sufficient, new tools are often the boost that brings exceptional results. Fraud Data Analytics Methodology gets you up to speed, with a brand new tool box for fraud detection.
Strategic Management Accounting by
This book critically analyzes the concept of strategic management accounting, the implications this emerging paradigm will have on the accounting profession, and the ramifications for businesses at large. This research examines current literature, and illustrates these concepts with current market examples. This manuscript approaches the topic in a way that is unique by linking the concept of SMA to the integrated reporting framework. In essence, strategic management accounting is a theory with broad-based support, but the IR framework and reporting structure provides a vehicle through which progress, costs, and benefits of a more strategic accounting function can be evaluated. Focusing on principles, primarily for internal management utilization, the following provides an outline and summary of concepts and techniques that can be used to elevate the role of the management accounting function. Whether you are a management expert, an accounting professional, or simply someone looking to keep up to date with emerging business trends, this text provides the content, and action-oriented steps to meet those expectations.