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| benford's law analysis: Benford's Law Mark J. Nigrini, 2012-03-09 A powerful new tool for all forensic accountants, or anyone whoanalyzes data that may have been altered Benford's Law gives the expected patterns of the digits in thenumbers in tabulated data such as town and city populations orMadoff's fictitious portfolio returns. Those digits, in unaltereddata, will not occur in equal proportions; there is a large biastowards the lower digits, so much so that nearly one-half of allnumbers are expected to start with the digits 1 or 2. Thesepatterns were originally discovered by physicist Frank Benford inthe early 1930s, and have since been found to apply to alltabulated data. Mark J. Nigrini has been a pioneer in applyingBenford's Law to auditing and forensic accounting, even before hisgroundbreaking 1999 Journal of Accountancy article introducing thisuseful tool to the accounting world. In Benford's Law, Nigrinishows the widespread applicability of Benford's Law and itspractical uses to detect fraud, errors, and other anomalies. Explores primary, associated, and advanced tests, all describedwith data sets that include corporate payments data and electiondata Includes ten fraud detection studies, including vendor fraud,payroll fraud, due diligence when purchasing a business, and taxevasion Covers financial statement fraud, with data from Enron, AIG,and companies that were the target of hedge fund short sales Looks at how to detect Ponzi schemes, including data on Madoff,Waxenberg, and more Examines many other applications, from the Clinton tax returnsand the charitable gifts of Lehman Brothers to tax evasion andnumber invention Benford's Law has 250 figures and uses 50 interestingauthentic and fraudulent real-world data sets to explain boththeory and practice, and concludes with an agenda and directionsfor future research. The companion website adds additionalinformation and resources. |
| benford's law analysis: Benford's Law Steven J. Miller, 2015-06-09 Benford's law states that the leading digits of many data sets are not uniformly distributed from one through nine, but rather exhibit a profound bias. This bias is evident in everything from electricity bills and street addresses to stock prices, population numbers, mortality rates, and the lengths of rivers. Here, Steven Miller brings together many of the world’s leading experts on Benford’s law to demonstrate the many useful techniques that arise from the law, show how truly multidisciplinary it is, and encourage collaboration. Beginning with the general theory, the contributors explain the prevalence of the bias, highlighting explanations for when systems should and should not follow Benford’s law and how quickly such behavior sets in. They go on to discuss important applications in disciplines ranging from accounting and economics to psychology and the natural sciences. The contributors describe how Benford’s law has been successfully used to expose fraud in elections, medical tests, tax filings, and financial reports. Additionally, numerous problems, background materials, and technical details are available online to help instructors create courses around the book. Emphasizing common challenges and techniques across the disciplines, this accessible book shows how Benford’s law can serve as a productive meeting ground for researchers and practitioners in diverse fields. |
| benford's law analysis: Handbook of Research on Accounting and Financial Studies Farinha, Luís, Cruz, Ana Baltazar, Sebastião, João Renato, 2020-03-06 The competitive nature of organizations in today’s globalized world has led to the development of various approaches to increasing profitability and maintaining an advantage over rival companies. As technology continues to be integrated into business practices, specifically in the area of accounting and finance, professionals and educators need to be prepared for advancing economic techniques, and they need to maintain a high level of financial literacy. The Handbook of Research on Accounting and Financial Studies is a pivotal reference source that provides vital research on advanced knowledge and emerging business practices and teaching dynamics in the fields of accounting and finance. While highlighting topics such as cost-benefit analysis, risk management, and corporate governance, this publication explores new initiatives in entrepreneurship and performance management. This book is ideally designed for business managers, consultants, entrepreneurs, auditors, tax practitioners, economists, accountants, academicians, researchers, and students seeking current research on modern advancements and recent findings in accounting and financial studies. |
| benford's law analysis: Forensic Analytics Mark J. Nigrini, 2020-04-20 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. |
| benford's law analysis: Using Benford's Law to Detect Fraud Association of Certified Fraud Examiners, Association of Certified Fraud Examiners Staff, Christopher J. Rosetti, 2002-01 Can a mathematical theory first conceived by Dr. Frank Benford over sixty years ago really help you detect fraud? Amazingly, the answer is yes! This workbook will provide you with an understanding of the history behind Benford's Law and give you the tools needed to apply Benford's Law while undertaking a fraud audit or fraud examination. |
| benford's law analysis: An Introduction to Benford's Law Arno Berger, Theodore P. Hill, 2015-05-26 This book provides the first comprehensive treatment of Benford's law, the surprising logarithmic distribution of significant digits discovered in the late nineteenth century. Establishing the mathematical and statistical principles that underpin this intriguing phenomenon, the text combines up-to-date theoretical results with overviews of the law’s colorful history, rapidly growing body of empirical evidence, and wide range of applications. An Introduction to Benford’s Law begins with basic facts about significant digits, Benford functions, sequences, and random variables, including tools from the theory of uniform distribution. After introducing the scale-, base-, and sum-invariance characterizations of the law, the book develops the significant-digit properties of both deterministic and stochastic processes, such as iterations of functions, powers of matrices, differential equations, and products, powers, and mixtures of random variables. Two concluding chapters survey the finitely additive theory and the flourishing applications of Benford’s law. Carefully selected diagrams, tables, and close to 150 examples illuminate the main concepts throughout. The text includes many open problems, in addition to dozens of new basic theorems and all the main references. A distinguishing feature is the emphasis on the surprising ubiquity and robustness of the significant-digit law. This text can serve as both a primary reference and a basis for seminars and courses. |
| benford's law analysis: Benford's Law Alex Ely Kossovsky, 2015 This leads to the key finding that the phenomenon is actually quantitative in nature. Why? The author illustrates that in extreme generality, nature creates many small quantities but very few big quantities, corroborating the motto small is beautiful, and that therefore all this is applicable just as well to data written in the ancient Roman, Mayan, Egyptian, and other digit-less civilizations. Fraudsters are typically not aware of this digital pattern and tend to invent numbers with approximately equal digital frequencies. The digital analyst can easily check reported data for compliance with this digital law, enabling the detection of tax evasion, Ponzi schemes, and other financial scams. |
| benford's law analysis: Forensic Analytics Mark J. Nigrini, 2011-05-12 Discover how to detect fraud, biases, or errors in your data using Access or Excel With over 300 images, Forensic Analytics reviews and shows how twenty substantive and rigorous tests can be used to detect fraud, errors, estimates, or biases in your data. For each test, the original data is shown with the steps needed to get to the final result. The tests range from high-level data overviews to assess the reasonableness of data, to highly focused tests that give small samples of highly suspicious transactions. These tests are relevant to your organization, whether small or large, for profit, nonprofit, or government-related. Demonstrates how to use Access, Excel, and PowerPoint in a forensic setting Explores use of statistical techniques such as Benford's Law, descriptive statistics, correlation, and time-series analysis to detect fraud and errors Discusses the detection of financial statement fraud using various statistical approaches Explains how to score locations, agents, customers, or employees for fraud risk Shows you how to become the data analytics expert in your organization Forensic Analytics shows how you can use Microsoft Access and Excel as your primary data interrogation tools to find exceptional, irregular, and anomalous records. |
| benford's law analysis: Using Analytics to Detect Possible Fraud Pamela S. Mantone, 2013-07-16 Detailed tools and techniques for developing efficiency and effectiveness in forensic accounting Using Analytics to Detect Possible Fraud: Tools and Techniques is a practical overview of the first stage of forensic accounting, providing a common source of analytical techniques used for both efficiency and effectiveness in forensic accounting investigations. The book is written clearly so that those who do not have advanced mathematical skills will be able to understand the analytical tests and use the tests in a forensic accounting setting. It also includes case studies and visual techniques providing practical application of the analytical tests discussed. Shows how to develop both efficiency and effectiveness in forensic accounting Provides information in such a way that non-practitioners can easily understand Written in plain language: advanced mathematical skills are not required Features actual case studies using analytical tests Essential reading for every investor who wants to prevent financial fraud, Using Analytics to Detect Possible Fraud allows practitioners to focus on areas that require further investigative techniques and to unearth deceptive financial reporting before it's too late. |
| benford's law analysis: Fraud Analysis Techniques Using ACL David Coderre, 2009-07-23 When people ask me what they can do to better utilize ACL, I tell them, 'Take an instructor lead course, participate in the ACL Forum, and study (not read, study) David Coderre's Fraud Analysis Techniques Using ACL.' I studied this book, and would not be where I am today without it. Even without the anti-fraud material, the book is worth the investment as a tool to learning ACL! —Porter Broyles, President and founder of the Texas ACL User Group, Keynote Speaker at ACL's 2009 San Francisco Conference, Official ACL Super User For individuals interested in learning about fraud analysis techniques or the art of ACL scripting, this book is a must-read. For those individuals interested in learning both, this book is a treasure. —Jim Hess, Principal, Hess Group, LLC Your very own ACL Fraud Toolkit—at your fingertips Fraud Analysis Techniques Using ACL offers auditors and investigators: Authoritative guidance from David Coderre, renowned expert on the use of computer-assisted audit tools and techniques in fraud detection A website containing an educational version of ACL from the world leader in fraud detection software An accompanying website containing a thorough Fraud Toolkit with two sets of customizable scripts to serve your specific audit needs Case studies and sample data files that you can use to try out the tests Step-by-step instructions on how to run the tests A self-study course on ACL script development with exercises, data files, and suggested answers The toolkit also contains 12 'utility scripts' and a self-study course on ACL scripting which includes exercises, data files, and proposed answers. Filled with screen shots, flow charts, example data files, and descriptive commentary highlighting and explaining each step, as well as case studies offering real-world examples of how the scripts can be used to search for fraud, Fraud Analysis Techniques Using ACL is the only toolkit you will need to harness the power of ACL to spot fraud. |
| benford's law analysis: The Perfect Bet Adam Kucharski, 2016-02-23 An elegant and amusing account of how gambling has been reshaped by the application of science and revealed the truth behind a lucky bet (Wall Street Journal). For the past 500 years, gamblers-led by mathematicians and scientists-have been trying to figure out how to pull the rug out from under Lady Luck. In The Perfect Bet, mathematician and award-winning writer Adam Kucharski tells the astonishing story of how the experts have succeeded, revolutionizing mathematics and science in the process. The house can seem unbeatable. Kucharski shows us just why it isn't. Even better, he demonstrates how the search for the perfect bet has been crucial for the scientific pursuit of a better world. |
| benford's law analysis: Digital Image Forensics Husrev Taha Sencar, Nasir Memon, 2012-08-01 Photographic imagery has come a long way from the pinhole cameras of the nineteenth century. Digital imagery, and its applications, develops in tandem with contemporary society’s sophisticated literacy of this subtle medium. This book examines the ways in which digital images have become ever more ubiquitous as legal and medical evidence, just as they have become our primary source of news and have replaced paper-based financial documentation. Crucially, the contributions also analyze the very profound problems which have arisen alongside the digital image, issues of veracity and progeny that demand systematic and detailed response: It looks real, but is it? What camera captured it? Has it been doctored or subtly altered? Attempting to provide answers to these slippery issues, the book covers how digital images are created, processed and stored before moving on to set out the latest techniques for forensically examining images, and finally addressing practical issues such as courtroom admissibility. In an environment where even novice users can alter digital media, this authoritative publication will do much so stabilize public trust in these real, yet vastly flexible, images of the world around us. |
| benford's law analysis: Cybersecurity in Nigeria Aamo Iorliam, 2019-03-15 This book reviews the use of digital surveillance for detecting, investigating and interpreting fraud associated with critical cyberinfrastructures in Nigeria, as it is well known that the country’s cyberspace and cyberinfrastructures are very porous, leaving too much room for cyber-attackers to freely operate. In 2017, there were 3,500 successful cyber-attacks on Nigerian cyberspace, which led to the country losing an estimated 450 million dollars. These cybercrimes are hampering Nigeria’s digital economy, and also help to explain why many Nigerians remain skeptical about Internet marketing and online transactions. If sensitive conversations using digital devices are not well monitored, Nigeria will be vulnerable to cyber-warfare, and its digital economy, military intelligence, and related sensitive industries will also suffer. The Nigerian Army Cyber Warfare Command was established in 2018 in order to combat terrorism, banditry, and other attacks by criminal groups in Nigeria. However, there remains an urgent need to produce digital surveillance software to help law enforcement agencies in Nigeria to detect and prevent these digitally facilitated crimes. The monitoring of Nigeria’s cyberspace and cyberinfrastructure has become imperative, given that the rate of criminal activities using technology has increased tremendously. In this regard, digital surveillance includes both passive forensic investigations (where an attack has already occurred) and active forensic investigations (real-time investigations that track attackers). In addition to reviewing the latest mobile device forensics, this book covers natural laws (Benford’s Law and Zipf’s Law) for network traffic analysis, mobile forensic tools, and digital surveillance software (e.g., A-BOT). It offers valuable insights into how digital surveillance software can be used to detect and prevent digitally facilitated crimes in Nigeria, and highlights the benefits of adopting digital surveillance software in Nigeria and other countries facing the same issues. |
| benford's law analysis: Humble Pi Matt Parker, 2021-01-19 #1 INTERNATIONAL BESTSELLER AN ADAM SAVAGE BOOK CLUB PICK The book-length answer to anyone who ever put their hand up in math class and asked, “When am I ever going to use this in the real world?” “Fun, informative, and relentlessly entertaining, Humble Pi is a charming and very readable guide to some of humanity's all-time greatest miscalculations—that also gives you permission to feel a little better about some of your own mistakes.” —Ryan North, author of How to Invent Everything Our whole world is built on math, from the code running a website to the equations enabling the design of skyscrapers and bridges. Most of the time this math works quietly behind the scenes . . . until it doesn’t. All sorts of seemingly innocuous mathematical mistakes can have significant consequences. Math is easy to ignore until a misplaced decimal point upends the stock market, a unit conversion error causes a plane to crash, or someone divides by zero and stalls a battleship in the middle of the ocean. Exploring and explaining a litany of glitches, near misses, and mathematical mishaps involving the internet, big data, elections, street signs, lotteries, the Roman Empire, and an Olympic team, Matt Parker uncovers the bizarre ways math trips us up, and what this reveals about its essential place in our world. Getting it wrong has never been more fun. |
| benford's law analysis: Fraud Analytics Using Descriptive, Predictive, and Social Network Techniques Bart Baesens, Veronique Van Vlasselaer, Wouter Verbeke, 2015-08-17 Detect fraud earlier to mitigate loss and prevent cascading damage Fraud Analytics Using Descriptive, Predictive, and Social Network Techniques is an authoritative guidebook for setting up a comprehensive fraud detection analytics solution. Early detection is a key factor in mitigating fraud damage, but it involves more specialized techniques than detecting fraud at the more advanced stages. This invaluable guide details both the theory and technical aspects of these techniques, and provides expert insight into streamlining implementation. Coverage includes data gathering, preprocessing, model building, and post-implementation, with comprehensive guidance on various learning techniques and the data types utilized by each. These techniques are effective for fraud detection across industry boundaries, including applications in insurance fraud, credit card fraud, anti-money laundering, healthcare fraud, telecommunications fraud, click fraud, tax evasion, and more, giving you a highly practical framework for fraud prevention. It is estimated that a typical organization loses about 5% of its revenue to fraud every year. More effective fraud detection is possible, and this book describes the various analytical techniques your organization must implement to put a stop to the revenue leak. Examine fraud patterns in historical data Utilize labeled, unlabeled, and networked data Detect fraud before the damage cascades Reduce losses, increase recovery, and tighten security The longer fraud is allowed to go on, the more harm it causes. It expands exponentially, sending ripples of damage throughout the organization, and becomes more and more complex to track, stop, and reverse. Fraud prevention relies on early and effective fraud detection, enabled by the techniques discussed here. Fraud Analytics Using Descriptive, Predictive, and Social Network Techniques helps you stop fraud in its tracks, and eliminate the opportunities for future occurrence. |
| benford's law analysis: Cognitive Computing for Big Data Systems Over IoT Arun Kumar Sangaiah, Arunkumar Thangavelu, Venkatesan Meenakshi Sundaram, 2017-12-30 This book brings a high level of fluidity to analytics and addresses recent trends, innovative ideas, challenges and cognitive computing solutions in big data and the Internet of Things (IoT). It explores domain knowledge, data science reasoning and cognitive methods in the context of the IoT, extending current data science approaches by incorporating insights from experts as well as a notion of artificial intelligence, and performing inferences on the knowledge The book provides a comprehensive overview of the constituent paradigms underlying cognitive computing methods, which illustrate the increased focus on big data in IoT problems as they evolve. It includes novel, in-depth fundamental research contributions from a methodological/application in data science accomplishing sustainable solution for the future perspective. Mainly focusing on the design of the best cognitive embedded data science technologies to process and analyze the large amount of data collected through the IoT, and aid better decision making, the book discusses adapting decision-making approaches under cognitive computing paradigms to demonstrate how the proposed procedures as well as big data and IoT problems can be handled in practice. This book is a valuable resource for scientists, professionals, researchers, and academicians dealing with the new challenges and advances in the specific areas of cognitive computing and data science approaches. |
| benford's law analysis: Challenges and Opportunities of Corporate Governance Transformation in the Digital Era Kuznetsov, Mikhail Yevgenievich, Nikishova, Maria Igorevna, 2019-12-27 While corporate governance has been a successful concept throughout the centuries, it is in question whether this concept can remain sustainable in the digital era and during a time of technological and managerial disruption. Under the pressure of new economic, social, and ecologic challenges, it is vital to understand how this concept needs to transform. Challenges and Opportunities of Corporate Governance Transformation in the Digital Era is an essential reference source that discusses concepts, trends, and forecasts of corporate governance and examines its transformation under the pressure of new technologies and economic changes. Featuring research on topics such as corporate identity, e-commerce, and cost management, this book is ideally designed for corporate leaders, managers, executives, business professionals, consultants, professors, researchers, and students. |
| benford's law analysis: Machine Learning: ECML 2005 João Gama, Rui Camacho, Pavel Brazdil, Alípio Jorge, Luís Torgo, 2005-09-22 This book constitutes the refereed proceedings of the 16th European Conference on Machine Learning, ECML 2005, jointly held with PKDD 2005 in Porto, Portugal, in October 2005. The 40 revised full papers and 32 revised short papers presented together with abstracts of 6 invited talks were carefully reviewed and selected from 335 papers submitted to ECML and 30 papers submitted to both, ECML and PKDD. The papers present a wealth of new results in the area and address all current issues in machine learning. |
| benford's law analysis: Ending the Mendel-Fisher Controversy Allan Franklin, A.W.F. Edwards, Daniel J. Fairbanks, Daniel L. Hartl, Teddy Seidenfeld, 2008-03-15 In 1865, Gregor Mendel presented Experiments in Plant-Hybridization, the results of his eight-year study of the principles of inheritance through experimentation with pea plants. Overlooked in its day, Mendel's work would later become the foundation of modern genetics. Did his pioneering research follow the rigors of real scientific inquiry, or was Mendel's data too good to be true—the product of doctored statistics? In Ending the Mendel-Fisher Controversy, leading experts present their conclusions on the legendary controversy surrounding the challenge to Mendel's findings by British statistician and biologist R. A. Fisher. In his 1936 paper Has Mendel's Work Been Rediscovered? Fisher suggested that Mendel's data could have been falsified in order to support his expectations. Fisher attributed the falsification to an unknown assistant of Mendel's. At the time, Fisher's criticism did not receive wide attention. Yet beginning in 1964, about the time of the centenary of Mendel's paper, scholars began to publicly discuss whether Fisher had successfully proven that Mendel's data was falsified. Since that time, numerous articles, letters, and comments have been published on the controversy.This self-contained volume includes everything the reader will need to know about the subject: an overview of the controversy; the original papers of Mendel and Fisher; four of the most important papers on the debate; and new updates, by the authors, of the latter four papers. Taken together, the authors contend, these voices argue for an end to the controversy-making this book the definitive last word on the subject. |
| benford's law analysis: Advances in Network Clustering and Blockmodeling Patrick Doreian, Vladimir Batagelj, Anuska Ferligoj, 2020-02-03 Provides an overview of the developments and advances in the field of network clustering and blockmodeling over the last 10 years This book offers an integrated treatment of network clustering and blockmodeling, covering all of the newest approaches and methods that have been developed over the last decade. Presented in a comprehensive manner, it offers the foundations for understanding network structures and processes, and features a wide variety of new techniques addressing issues that occur during the partitioning of networks across multiple disciplines such as community detection, blockmodeling of valued networks, role assignment, and stochastic blockmodeling. Written by a team of international experts in the field, Advances in Network Clustering and Blockmodeling offers a plethora of diverse perspectives covering topics such as: bibliometric analyses of the network clustering literature; clustering approaches to networks; label propagation for clustering; and treating missing network data before partitioning. It also examines the partitioning of signed networks, multimode networks, and linked networks. A chapter on structured networks and coarsegrained descriptions is presented, along with another on scientific coauthorship networks. The book finishes with a section covering conclusions and directions for future work. In addition, the editors provide numerous tables, figures, case studies, examples, datasets, and more. Offers a clear and insightful look at the state of the art in network clustering and blockmodeling Provides an excellent mix of mathematical rigor and practical application in a comprehensive manner Presents a suite of new methods, procedures, algorithms for partitioning networks, as well as new techniques for visualizing matrix arrays Features numerous examples throughout, enabling readers to gain a better understanding of research methods and to conduct their own research effectively Written by leading contributors in the field of spatial networks analysis Advances in Network Clustering and Blockmodeling is an ideal book for graduate and undergraduate students taking courses on network analysis or working with networks using real data. It will also benefit researchers and practitioners interested in network analysis. |
| benford's law analysis: Artificial Intelligence in Finance Yves Hilpisch, 2020-10-14 The widespread adoption of AI and machine learning is revolutionizing many industries today. Once these technologies are combined with the programmatic availability of historical and real-time financial data, the financial industry will also change fundamentally. With this practical book, you'll learn how to use AI and machine learning to discover statistical inefficiencies in financial markets and exploit them through algorithmic trading. Author Yves Hilpisch shows practitioners, students, and academics in both finance and data science practical ways to apply machine learning and deep learning algorithms to finance. Thanks to lots of self-contained Python examples, you'll be able to replicate all results and figures presented in the book. In five parts, this guide helps you: Learn central notions and algorithms from AI, including recent breakthroughs on the way to artificial general intelligence (AGI) and superintelligence (SI) Understand why data-driven finance, AI, and machine learning will have a lasting impact on financial theory and practice Apply neural networks and reinforcement learning to discover statistical inefficiencies in financial markets Identify and exploit economic inefficiencies through backtesting and algorithmic trading--the automated execution of trading strategies Understand how AI will influence the competitive dynamics in the financial industry and what the potential emergence of a financial singularity might bring about |
| benford's law analysis: The Despot's Guide to Wealth Management J. C. Sharman, 2017-03-07 An unprecedented new international moral and legal rule forbids one state from hosting money stolen by the leaders of another state. The aim is to counter grand corruption or kleptocracy (rule by thieves), when leaders of poorer countries—such as Marcos in the Philippines, Mobutu in the Congo, and more recently those overthrown in revolutions in the Arab world and Ukraine—loot billions of dollars at the expense of their own citizens. This money tends to end up hosted in rich countries. These host states now have a duty to block, trace, freeze, and seize these illicit funds and hand them back to the countries from which they were stolen. In The Despot's Guide to Wealth Management, J. C. Sharman asks how this anti-kleptocracy regime came about, how well it is working, and how it could work better. Although there have been some real achievements, the international campaign against grand corruption has run into major obstacles. The vested interests of banks, lawyers, and even law enforcement often favor turning a blind eye to foreign corruption proceeds. Recovering and returning looted assets is a long, complicated, and expensive process. Sharman used a private investigator, participated in and observed anti-corruption policy, and conducted more than a hundred interviews with key players. He also draws on various journalistic exposés, whistle-blower accounts, and government investigations to inform his comparison of the anti-kleptocracy records of the United States, Britain, Switzerland, and Australia. Sharman calls for better policing, preventative measures, and use of gatekeepers like bankers, lawyers, and real estate agents. He also recommends giving nongovernmental organizations and for-profit firms more scope to independently investigate corruption and seize stolen assets. |
| benford's law analysis: The Online Journalism Handbook Paul Bradshaw, Liisa Rohumaa, 2013-09-13 How do we practice journalism in a digital world, in which the old 'rules' no longer apply? This text offers comprehensive, instructive coverage of the techniques and secrets of being a successful online journalist, both from a theoretical and practical point of view. Reflecting the vitality of the web, it will inspire you to acquire new skills and make sense of a transforming industry. Key Features: How to investigate and break stories online Learn to broadcast to millions using video and podcast How to blog like a pro Learn to manage and stimulate user-generated content Include and use social media in your toolkit How to dig out stories using data journalism Rise to the challenge of citizen journalism Make your journalism more interactive at every stage of the process Dedicated chapter for Law and Online Communication The Online Journalism Handbook is essential reading for all journalism students and professionals and of key interest to media, communication studies and more broadly the social sciences. |
| benford's law analysis: The Essence of Software Engineering Ivar Jacobson, Pan-Wei Ng, Paul E. McMahon, Ian Spence, Svante Lidman, 2013-01-11 SEMAT (Software Engineering Methods and Theory) is an international initiative designed to identify a common ground, or universal standard, for software engineering. It is supported by some of the most distinguished contributors to the field. Creating a simple language to describe methods and practices, the SEMAT team expresses this common ground as a kernel–or framework–of elements essential to all software development. The Essence of Software Engineering introduces this kernel and shows how to apply it when developing software and improving a team’s way of working. It is a book for software professionals, not methodologists. Its usefulness to development team members, who need to evaluate and choose the best practices for their work, goes well beyond the description or application of any single method. “Software is both a craft and a science, both a work of passion and a work of principle. Writing good software requires both wild flights of imagination and creativity, as well as the hard reality of engineering tradeoffs. This book is an attempt at describing that balance.” —Robert Martin (unclebob) “The work of Ivar Jacobson and his colleagues, started as part of the SEMAT initiative, has taken a systematic approach to identifying a ‘kernel’ of software engineering principles and practices that have stood the test of time and recognition.” —Bertrand Meyer “The software development industry needs and demands a core kernel and language for defining software development practices—practices that can be mixed and matched, brought on board from other organizations; practices that can be measured; practices that can be integrated; and practices that can be compared and contrasted for speed, quality, and price. This thoughtful book gives a good grounding in ways to think about the problem, and a language to address the need, and every software engineer should read it.” —Richard Soley |
| benford's law analysis: An Invitation to Modern Number Theory Steven J. Miller, Ramin Takloo-Bighash, 2020-07-21 In a manner accessible to beginning undergraduates, An Invitation to Modern Number Theory introduces many of the central problems, conjectures, results, and techniques of the field, such as the Riemann Hypothesis, Roth's Theorem, the Circle Method, and Random Matrix Theory. Showing how experiments are used to test conjectures and prove theorems, the book allows students to do original work on such problems, often using little more than calculus (though there are numerous remarks for those with deeper backgrounds). It shows students what number theory theorems are used for and what led to them and suggests problems for further research. Steven Miller and Ramin Takloo-Bighash introduce the problems and the computational skills required to numerically investigate them, providing background material (from probability to statistics to Fourier analysis) whenever necessary. They guide students through a variety of problems, ranging from basic number theory, cryptography, and Goldbach's Problem, to the algebraic structures of numbers and continued fractions, showing connections between these subjects and encouraging students to study them further. In addition, this is the first undergraduate book to explore Random Matrix Theory, which has recently become a powerful tool for predicting answers in number theory. Providing exercises, references to the background literature, and Web links to previous student research projects, An Invitation to Modern Number Theory can be used to teach a research seminar or a lecture class. |
| benford's law analysis: Randomness Through Computation: Some Answers, More Questions Hector Zenil, 2011-02-11 This review volume consists of a set of chapters written by leading scholars, most of them founders of their fields. It explores the connections of Randomness to other areas of scientific knowledge, especially its fruitful relationship to Computability and Complexity Theory, and also to areas such as Probability, Statistics, Information Theory, Biology, Physics, Quantum Mechanics, Learning Theory and Artificial Intelligence. The contributors cover these topics without neglecting important philosophical dimensions, sometimes going beyond the purely technical to formulate age old questions relating to matters such as determinism and free will.The scope of Randomness Through Computation is novel. Each contributor shares their personal views and anecdotes on the various reasons and motivations which led them to the study of Randomness. Using a question and answer format, they share their visions from their several distinctive vantage points. |
| benford's law analysis: Benford's Law Mark J. Nigrini, 2012-04-24 A powerful new tool for all forensic accountants, or anyone who analyzes data that may have been altered Benford's Law gives the expected patterns of the digits in the numbers in tabulated data such as town and city populations or Madoff's fictitious portfolio returns. Those digits, in unaltered data, will not occur in equal proportions; there is a large bias towards the lower digits, so much so that nearly one-half of all numbers are expected to start with the digits 1 or 2. These patterns were originally discovered by physicist Frank Benford in the early 1930s, and have since been found to apply to all tabulated data. Mark J. Nigrini has been a pioneer in applying Benford's Law to auditing and forensic accounting, even before his groundbreaking 1999 Journal of Accountancy article introducing this useful tool to the accounting world. In Benford's Law, Nigrini shows the widespread applicability of Benford's Law and its practical uses to detect fraud, errors, and other anomalies. Explores primary, associated, and advanced tests, all described with data sets that include corporate payments data and election data Includes ten fraud detection studies, including vendor fraud, payroll fraud, due diligence when purchasing a business, and tax evasion Covers financial statement fraud, with data from Enron, AIG, and companies that were the target of hedge fund short sales Looks at how to detect Ponzi schemes, including data on Madoff, Waxenberg, and more Examines many other applications, from the Clinton tax returns and the charitable gifts of Lehman Brothers to tax evasion and number invention Benford's Law has 250 figures and uses 50 interesting authentic and fraudulent real-world data sets to explain both theory and practice, and concludes with an agenda and directions for future research. The companion website adds additional information and resources. |
| benford's law analysis: Benford's Law Steven J. Miller, 2015-05-26 Benford's law states that the leading digits of many data sets are not uniformly distributed from one through nine, but rather exhibit a profound bias. This bias is evident in everything from electricity bills and street addresses to stock prices, population numbers, mortality rates, and the lengths of rivers. Here, Steven Miller brings together many of the world’s leading experts on Benford’s law to demonstrate the many useful techniques that arise from the law, show how truly multidisciplinary it is, and encourage collaboration. Beginning with the general theory, the contributors explain the prevalence of the bias, highlighting explanations for when systems should and should not follow Benford’s law and how quickly such behavior sets in. They go on to discuss important applications in disciplines ranging from accounting and economics to psychology and the natural sciences. The contributors describe how Benford’s law has been successfully used to expose fraud in elections, medical tests, tax filings, and financial reports. Additionally, numerous problems, background materials, and technical details are available online to help instructors create courses around the book. Emphasizing common challenges and techniques across the disciplines, this accessible book shows how Benford’s law can serve as a productive meeting ground for researchers and practitioners in diverse fields. |
| benford's law analysis: Database of Piano Chords Ana M. Barbancho, Isabel Barbancho, Lorenzo J. Tardón, Emilio Molina, 2013-05-27 Database of Piano Chords: An Engineering View of Harmony includes a unique database of piano chords developed exclusively for music research purposes, and outlines the key advantages to using this dataset to further one’s research. The book also describes the physical bases of the occidental music chords and the influence used in the detection and transcription of the music, enabling researchers to intimately understand the construction of each occidental chord. The online database contains more than 275,000 chords with different degrees of polyphony and with different playing styles. Together, the database and the book are an invaluable tool for researchers in this field. |
| benford's law analysis: Solving Modern Crime in Financial Markets Marius-Cristian Frunza, 2015-12-09 This comprehensive source of information about financial fraud delivers a mature approach to fraud detection and prevention. It brings together all important aspect of analytics used in investigating modern crime in financial markets and uses R for its statistical examples. It focuses on crime in financial markets as opposed to the financial industry, and it highlights technical aspects of crime detection and prevention as opposed to their qualitative aspects. For those with strong analytic skills, this book unleashes the usefulness of powerful predictive and prescriptive analytics in predicting and preventing modern crime in financial markets. - Interviews and case studies provide context and depth to examples - Case studies use R, the powerful statistical freeware tool - Useful in classroom and professional contexts |
| benford's law analysis: Economic Fables Ariel Rubinstein, 2012 I had the good fortune to grow up in a wonderful area of Jerusalem, surrounded by a diverse range of people: Rabbi Meizel, the communist Sala Marcel, my widowed Aunt Hannah, and the intellectual Yaacovson. As far as I'm concerned, the opinion of such people is just as authoritative for making social and economic decisions as the opinion of an expert using a model. Part memoir, part crash-course in economic theory, this deeply engaging book by one of the world's foremost economists looks at economic ideas through a personal lens. Together with an introduction to some of the central concepts in modern economic thought, Ariel Rubinstein offers some powerful and entertaining reflections on his childhood, family and career. In doing so, he challenges many of the central tenets of game theory, and sheds light on the role economics can play in society at large. Economic Fables is as thought-provoking for seasoned economists as it is enlightening for newcomers to the field. |
| benford's law analysis: Optimization, Learning Algorithms and Applications Ana I. Pereira, Florbela P. Fernandes, João P. Coelho, João P. Teixeira, Maria F. Pacheco, Paulo Alves, Rui P. Lopes, 2021-12-02 This book constitutes selected and revised papers presented at the First International Conference on Optimization, Learning Algorithms and Applications, OL2A 2021, held in Bragança, Portugal, in July 2021. Due to the COVID-19 pandemic the conference was held online. The 39 full papers and 13 short papers were thoroughly reviewed and selected from 134 submissions. They are organized in the topical sections on optimization theory; robotics; measurements with the internet of things; optimization in control systems design; deep learning; data visualization and virtual reality; health informatics; data analysis; trends in engineering education. |
| benford's law analysis: Analyzing the Social Web Jennifer Golbeck, 2013-02-17 Analyzing the Social Web provides a framework for the analysis of public data currently available and being generated by social networks and social media, like Facebook, Twitter, and Foursquare. Access and analysis of this public data about people and their connections to one another allows for new applications of traditional social network analysis techniques that let us identify things like who are the most important or influential people in a network, how things will spread through the network, and the nature of peoples' relationships. Analyzing the Social Web introduces you to these techniques, shows you their application to many different types of social media, and discusses how social media can be used as a tool for interacting with the online public. - Presents interactive social applications on the web, and the types of analysis that are currently conducted in the study of social media - Covers the basics of network structures for beginners, including measuring methods for describing nodes, edges, and parts of the network - Discusses the major categories of social media applications or phenomena and shows how the techniques presented can be applied to analyze and understand the underlying data - Provides an introduction to information visualization, particularly network visualization techniques, and methods for using them to identify interesting features in a network, generate hypotheses for analysis, and recognize patterns of behavior - Includes a supporting website with lecture slides, exercises, and downloadable social network data sets that can be used can be used to apply the techniques presented in the book |
| benford's law analysis: An Introduction to Benford's Law Arno Berger, Theodore P. Hill, 2015-05-26 This book provides the first comprehensive treatment of Benford's law, the surprising logarithmic distribution of significant digits discovered in the late nineteenth century. Establishing the mathematical and statistical principles that underpin this intriguing phenomenon, the text combines up-to-date theoretical results with overviews of the law’s colorful history, rapidly growing body of empirical evidence, and wide range of applications. An Introduction to Benford’s Law begins with basic facts about significant digits, Benford functions, sequences, and random variables, including tools from the theory of uniform distribution. After introducing the scale-, base-, and sum-invariance characterizations of the law, the book develops the significant-digit properties of both deterministic and stochastic processes, such as iterations of functions, powers of matrices, differential equations, and products, powers, and mixtures of random variables. Two concluding chapters survey the finitely additive theory and the flourishing applications of Benford’s law. Carefully selected diagrams, tables, and close to 150 examples illuminate the main concepts throughout. The text includes many open problems, in addition to dozens of new basic theorems and all the main references. A distinguishing feature is the emphasis on the surprising ubiquity and robustness of the significant-digit law. This text can serve as both a primary reference and a basis for seminars and courses. |
| benford's law analysis: Advanced Technologies, Systems, and Applications III Samir Avdaković, 2018-11-04 This book introduces innovative and interdisciplinary applications of advanced technologies. Featuring the papers from the 10th DAYS OF BHAAAS (Bosnian-Herzegovinian American Academy of Arts and Sciences) held in Jahorina, Bosnia and Herzegovina on June 21–24, 2018, it discusses a wide variety of engineering and scientific applications of the different techniques. Researchers from academic and industry present their work and ideas, techniques and applications in the field of power systems, mechanical engineering, computer modelling and simulations, civil engineering, robotics and biomedical engineering, information and communication technologies, computer science and applied mathematics. |
| benford's law analysis: Elections, Protest, and Authoritarian Regime Stability Regina Smyth, 2020-10-29 This comprehensive study of Russian electoral politics shows the vulnerability of Putin's regime as it navigates the risks of voter manipulation. |
| benford's law analysis: The Theory of Perfect Learning Nonvikan Karl-Augustt Alahassa, 2021-08-17 The perfect learning exists. We mean a learning model that can be generalized, and moreover, that can always fit perfectly the test data, as well as the training data. We have performed in this thesis many experiments that validate this concept in many ways. The tools are given through the chapters that contain our developments. The classical Multilayer Feedforward model has been re-considered and a novel $N_k$-architecture is proposed to fit any multivariate regression task. This model can easily be augmented to thousands of possible layers without loss of predictive power, and has the potential to overcome our difficulties simultaneously in building a model that has a good fit on the test data, and don't overfit. His hyper-parameters, the learning rate, the batch size, the number of training times (epochs), the size of each layer, the number of hidden layers, all can be chosen experimentally with cross-validation methods. There is a great advantage to build a more powerful model using mixture models properties. They can self-classify many high dimensional data in a few numbers of mixture components. This is also the case of the Shallow Gibbs Network model that we built as a Random Gibbs Network Forest to reach the performance of the Multilayer feedforward Neural Network in a few numbers of parameters, and fewer backpropagation iterations. To make it happens, we propose a novel optimization framework for our Bayesian Shallow Network, called the {Double Backpropagation Scheme} (DBS) that can also fit perfectly the data with appropriate learning rate, and which is convergent and universally applicable to any Bayesian neural network problem. The contribution of this model is broad. First, it integrates all the advantages of the Potts Model, which is a very rich random partitions model, that we have also modified to propose its Complete Shrinkage version using agglomerative clustering techniques. The model takes also an advantage of Gibbs Fields for its weights precision matrix structure, mainly through Markov Random Fields, and even has five (5) variants structures at the end: the Full-Gibbs, the Sparse-Gibbs, the Between layer Sparse Gibbs which is the B-Sparse Gibbs in a short, the Compound Symmetry Gibbs (CS-Gibbs in short), and the Sparse Compound Symmetry Gibbs (Sparse-CS-Gibbs) model. The Full-Gibbs is mainly to remind fully-connected models, and the other structures are useful to show how the model can be reduced in terms of complexity with sparsity and parsimony. All those models have been experimented, and the results arouse interest in those structures, in a sense that different structures help to reach different results in terms of Mean Squared Error (MSE) and Relative Root Mean Squared Error (RRMSE). For the Shallow Gibbs Network model, we have found the perfect learning framework : it is the $(l_1, \boldsymbol{\zeta}, \epsilon_{dbs})-\textbf{DBS}$ configuration, which is a combination of the \emph{Universal Approximation Theorem}, and the DBS optimization, coupled with the (\emph{dist})-Nearest Neighbor-(h)-Taylor Series-Perfect Multivariate Interpolation (\emph{dist}-NN-(h)-TS-PMI) model [which in turn is a combination of the research of the Nearest Neighborhood for a good Train-Test association, the Taylor Approximation Theorem, and finally the Multivariate Interpolation Method]. It indicates that, with an appropriate number $l_1$ of neurons on the hidden layer, an optimal number $\zeta$ of DBS updates, an optimal DBS learnnig rate $\epsilon_{dbs}$, an optimal distance \emph{dist}$_{opt}$ in the research of the nearest neighbor in the training dataset for each test data $x_i^{\mbox{test}}$, an optimal order $h_{opt}$ of the Taylor approximation for the Perfect Multivariate Interpolation (\emph{dist}-NN-(h)-TS-PMI) model once the {\bfseries DBS} has overfitted the training dataset, the train and the test error converge to zero (0). As the Potts Models and many random Partitions are based on a similarity measure, we open the door to find \emph{sufficient} invariants descriptors in any recognition problem for complex objects such as image; using \emph{metric} learning and invariance descriptor tools, to always reach 100\% accuracy. This is also possible with invariant networks that are also universal approximators. Our work closes the gap between the theory and the practice in artificial intelligence, in a sense that it confirms that it is possible to learn with very small error allowed. |
| benford's law analysis: How Many Socks Make a Pair? Rob Eastaway, 2013-02-18 How many socks make a pair? The answer is not always two. And behind this question lies a world of maths that can be surprising, amusing and even beautiful. Using playing cards, a newspaper, the back of an envelope, a Sudoku, some pennies and of course a pair of socks, Rob Eastaway shows how maths can demonstrate its secret beauties in even the most mundane of everyday objects. If you already like maths you’ll discover plenty of new surprises. And if you’ve never picked up a maths book in your life, this one will change your view of the subject forever. |
| benford's law analysis: The Forensics of Election Fraud Mikhail Myagkov, Peter C. Ordeshook, Dimitri Shakin, 2009-04-27 A forensics approach to detecting election fraud -- The fingerprints of fraud -- Russia -- Ukraine 2004 -- Ukraine 2006 and 2007 -- The United States. |
| benford's law analysis: Entropy in Dynamical Systems Tomasz Downarowicz, 2011-05-12 This comprehensive text on entropy covers three major types of dynamics: measure preserving transformations; continuous maps on compact spaces; and operators on function spaces. Part I contains proofs of the Shannon–McMillan–Breiman Theorem, the Ornstein–Weiss Return Time Theorem, the Krieger Generator Theorem and, among the newest developments, the ergodic law of series. In Part II, after an expanded exposition of classical topological entropy, the book addresses symbolic extension entropy. It offers deep insight into the theory of entropy structure and explains the role of zero-dimensional dynamics as a bridge between measurable and topological dynamics. Part III explains how both measure-theoretic and topological entropy can be extended to operators on relevant function spaces. Intuitive explanations, examples, exercises and open problems make this an ideal text for a graduate course on entropy theory. More experienced researchers can also find inspiration for further research. |
Get MAD with the Numbers - Benford Online
Mark J. Nigrini, Ph.D., in his new book, “Digital Analysis Using Benford’s Law” (Global Audit Publications, 2000) suggests the use of Mean Absolute Deviation (MAD) as the best measure …
USING BENFORD’S LAW IN AUDIT
In this research paper, we introduce the Benford’s law phenomenon in simple terms and explain how we can apply it with IDEA or Microsoft Excel. To drive home our point, we have analysed …
Two Digit Testing for Benford’s Law - statistics.gov.hk
test the joint distribution of the first and second digit for conformity to Benford’s law. Additionally, a comparison of power yielded by the original (one-digit) as well as the proposed (two-digit) …
BENFORD’S LAW ANALYSIS - City of Orlando
• In 1999, Mark Nigrini proposed using Benford’s Law as an analysis method to alert users to possible errors, fraud, costly processing inefficiencies or other irregularities
Benford's Law: Theory and Applications - TOC - Princeton …
A Short Introduction to the Mathematical Theory of Benford’s Law. Chapter 3. Fourier Analysis and Benford’s Law. PART II. Chapter 4. Benford’s Law Geometry. Chapter 5. Explicit Error …
BENFORD’S LAW, FAMILIES OF DISTRIBUTIONS AND A TEST …
Abstract. The distribution of first significant digits known as Benford’s Law has been used to test for erroneous and fraudulent data. By testing for confor-mance with the Law, applied …
TheMathematicsofBenford’sLaw-APrimer - arXiv.org
This article provides a concise overview of the main mathematical theory of Benford’s law in a form accessible to scientists and students who have had first courses in calculus and probability.
Benford’s Law and the Risk of Financial Fraud
What is Benford’s Law, and can it be applied to detect financial fraud? Controversies surrounding the integrity of LIBOR setting and reported sovereign economic data serve as examples that …
An Introduction to Benford's Law - Chapter 1
Benford’s law, also known as the First-digit or Significant-digit law, is the em-pirical gem of statistical folklore that in many naturally occurring tables of numerical data, the significant digits …
BENFORD’S LAW: A DETAILED UNDERSTANDING AND ITS …
This paper seeks to explain the definition and formula of Benford’s Law and provides the statistical test used to check for its compliance. The law has also been used to identify the accounting …
benford.analysis: Benford Analysis for Data Validation and …
The Benford Analysis package provides tools that make it easier to validate data using Benford’s Law. The main purpose of the package is to identify suspicious data that need further …
THE POWER OF ONE: BENFORD’S LAW - SciELO
such technique is known as Benford’s law, or the first-digit phenomenon. This paper will attempt to discuss and illustrate the characteristics and application of Benford’s law.
Devising a Model for Accounting Fraud Detection Based on …
Benford law is a phenomenological law related to the frequency distribution of the leading digits in the numerical data of many real life sets. The law states that in many naturally occurring …
Benford's Law: Theory and Applications - Chapter 1
In this chapter we start by stating Benford’s Law of digit bias and describing its history. We discuss its origins and give numerous examples of data sets that follow this law, as well as …
The mathematics of Benford’s law: a primer - Springer
This article provides a concise overview of the main mathematical theory of Ben-ford’s law in a form accessible to scientists and students who have had first courses in calculus and probability.
REPORT ON BENFORD’S LAW ANALYSIS OF 2020 …
We have decades of experience in the theory and application of Benford’s law; this is a mathematical result that describes many data sets and is often used to detect if a data set has …
Benford's Law: Theory and Applications - Preface - Princeton …
•Part I: General Theory I: Basis of Benford’s Law: We begin our study of Benford’s Law with a brief introduction by Miller in Chapter 1. We concen-trate on the history and some possible …
Benford’s Law Made Easy
Performing a Benford’s Law analysis with Excel is actually a five-step process. First, select a population for analysis. Second, assemble the raw data in a format acceptable to Excel. Third, …
Following Benford's Law, or Looking Out for No.
Following Benford's Law, or Looking Out for No. 1 By MALCOLM W. BROWNE DR. THEODORE P. HILL asks his mathematics students at the Georgia Institute of ... analysis of 20,229 sets of …
PENDETEKSIAN FRAUD DENGAN HUKUM BENFORD - UBM
custom value is acceptable or not then a digital analysis vehicle called Benford’s Law as well as a number of statistical test is used. Assessment is done to detect fraudulent data as part of risk …
Was There Any Widespread Fraud in 2020 Presidential
analysis of vote counts of the candidates participating in the election. In this particular instance, the data will be analyzed and compared to Benford’s Law, which is a simple but effective ...
Devising a Model for Accounting Fraud Detection Based on …
2.2 The origin of Benford’s law Benford’s law, given by physicist named Frank Benford, is similar to the observations made by an astronomer and mathematician, Simon Newcomb way back in …
An Effective and Efficient Analytic Technique: A Bootstrap …
(BREG) procedure in the context of Benford’s Law to identify unusual patterns of data using the first two digits of financial data. The BREG procedure is based on simple regression analysis, …
Applying Benford's Law to individual financial reports: An …
errors in accounting data. A possible analytical procedure could be digit analysis or Benford’s Law (Newcomb 1881; Benford 1938). The idea behind is that for many random datasets higher …
Abiding by the Law: Using Benford’s Law to Examine …
taset with the Benford’s Law distribution to test whether the data is naturally generated or made up. Later, accounting scholars began applying Benford’s Law to detect possibly fraudulent …
Forensic Accounting - An Investigative Analysis on Selected …
Forensic Accounting - An Investigative Analysis on Selected Indian Companies Using Benford's Law Ashish M. Chauhan Research Scholar, Gujarat University, Ahmedabad-380009, India …
Detecting money laundering with Benford’s law and machine …
principal components analysis applied to the original features. The rest of the paper is organized as follows: Section 2 reviews fraud detection ap-proaches and the use of Benford’s law in the …
FRAUD DETECTING WITH BENFORD’S LAW: AN …
process of deviation from Benford's law. In Hill's (1998) analysis of a 1995 tax bill that is known to be fraudulent in New York, it was determined that the numbers did not follow Benford's law. …
Using Benford’s Law for Fraud Detection in Accounting …
the Benford’s Law analysis is completed on a “digit-by-digit” basis, as compared to the “test-by-test” basis typically employed by statisticians. The proposed methodology in this paper, “digit …
Breaking Benford’s law: a statistical analysis of COVID-19 …
the present study conforms to Benford’s law at a significant level ofα = 0.05 and 17% at a significant level of 0.01 ≤α <0.05, the remaining 21% shows a deviation from it (p values …
A New Benford Test for Clustered Data with Applications to …
Abstract: A frequent problem with classic first digit applications of Benford’s law is the law’s 1 inapplicability to clustered data, which becomes especially problematic for analyzing election …
Benford's Law and its Application in Auditing
Purpose –Benford's Law is a simple and effective auditor tool that detects fraud. This paper’s purpose is to audit the effi-ciency of Benford's law, which uses a set of strange ob-servations, …
LEVERAGING BENFORD'S LAW FOR IMAGE FORGERY …
applying Benford's Law to image analysis and the statistical tests used to evaluate its effectiveness are discussed. The limitations of the approach and potential future research …
The Application of Benford’s Law in Fraud Detection: A …
such as Benford’s Law analysis that can enable and enhance auditors’ ability to detect fraud is invaluable (Durtschi, Hillison, & Pacini, 2004; Collins, 2017). This paper has a twofold objective …
Applying visual analytics to fraud detection using Benford's law
Benford’s law has been examined as a useful tool for detecting potential accounting fraud. In this article, I provide an introduction to Benford’s law and examine how the first digit, second digit, …
Analyzing Benford s Law s Powerful Applications in Image …
Appl. Sci. 2021, 11, 11482 2 of 15 in Spain in 2015–2016 [6]. Detecting fraud in customs declaration [7] and accounting [8] are two other fields where the NBL was applied.
THE IMPACT AND REALITY OF FRAUD AUDITING - Fraud …
BENFORD’S LAW: WHY AND HOW TO USE IT Benford's Law is used to find abnormalities in large data sets. Examples of the diversity of data sets include currency amounts, time …
Detecting anomalies in the 2020 US Presidential election …
Therefore, it is reinforced that first-digit Benford’s law analysis is best applicable for right-skewed, non-bounded data spanning several orders of magnitude (Deckert et al., 2011; Koch and …
An Overview of Instruments and Tools to Detect Fraudulent …
Sep 30, 2019 · Beneish model and the Benford’s Law. Beneish model is a mathematical method which is based on financial ratios and their analysis, meanwhile Benford’s Law is an …
Effective Use of Benford's Law - ResearchGate
tive use of digital analysis based on Benford’s law. The law is based on a peculiar observation that certain digits appear more frequently than others in data sets. For example, in certain data
Bootstrap Approach to The Application of First-Digits Analysis
a logarithmic distribution (Swanson, 2003). “First-digit analysis” refers to the analysis of expected proportions of leading digits, i.e. proportions of numbers 1 through 9. For example, 399 has a …
BENFORD’S LAW: A DETAILED UNDERSTANDING AND …
3. This law cannot be used to detect fraud when very few transactions that have been manipulated. 4. This law determines if there exists a fraud but does not quantify to what extent …
BENFORD’S LAW, FAMILIES OF DISTRIBUTIONS AND A …
BENFORD’S LAW, FAMILIES OF DISTRIBUTIONS AND A TEST BASIS JOHNMORROWy ThisDraft: October9,2010 FirstDraft: August6,2006 Abstract. The distribution of first …
THE VALIDITY OF SOCIAL SCIENCE DATA APPLYING …
978-1-009-12307-5 — Applying Benford's Law for Assessing the Validity of Social Science Data Michael A. Long , Paul B. Stretesky , Kenneth J. Berry , Janis E. Johnston , Michael J. Lynch …
Analyzing Big Data with Benford’s Law: A Lesson for the …
Benford’s Law, Theodore Hill listed classical explanations (1995b) including “the usual number-theoretic (or Cesaro) ... Phatarfod (2013) provides an excellent statistical analysis of various …
Detecting Problems in Survey Data using Benford’s Law
We conduct an analysis of nine commonly used datasets and find that much data from developing countries is of poor ... Benford’s law also has the nice property that it satisfies a …
BENFORD’S LAW FOR MUSIC ANALYSIS - UMA
BENFORD’S LAW FOR MUSIC ANALYSIS Isabel Barbancho1 Lorenzo J. Tardon´ 1 Ana M. Barbancho1 Mateu Sbert2 1 Universidad de Malaga, ATIC Research Group, ETSI …
Benford’s Law in Appraisal
Benford’s Law but are often too small for statisti cal verification. The individual items listed below will be consistent with Benford’s Law and but can be verified only if included in large …
Benford s Law: A survey of its varied applications
An analysis of the numbers from different sources shows that the numbers taken from unrelated subjects, such as a group of newspaper items, show a similar pattern.” ... Benford’s Law to the …
Liability Claims Audit Report - Garland, TX
Benford’s Law (first digit law) Analysis and Results Benford’s Law states that for many real-life sources of data, the first digit will be “1” about 30% of the time and that small first-digits will …
BENFORD’S LAW APPLIED TO PRECINCT LEVEL …
In human-controlled systems where Benford’s law is applicable, a lack of conformity with Benford’s law may be an indicator of fraud. Benford’s Law is increasingly used by forensic …
Benford's Law for Natural and Synthetic Images
Benford’s Law (also known as the First Digit Law) is well known in statistics of natural phenomena. It states ... cation of Bendford’s Law to image analysis is quite innova-tive. To our …
Numbers Don’t Lie: Decoding Financial Error and Fraud …
(Setyawan, 2020). Moreover, Benford’s law is very useful in terms of detecting irregularities in financial statements (Gorenc, 2019). Benford's Law, also known as the First-Digit Law, is a …
Loi de Benford et implémentation python - franckybox.com
A reminder on Benford’s law simplifications and a simple python implementation. Keywords: Benford’s law, log simplification, python 1. Introduction La loi deFrank Benford[1], également …
BENFORD’S LAW - Williams College
May 20, 2010 · Benford’s law The rst quotation at the beginning of this article is the rst sentence of an 1881 paper, \Note on the Frequency of Use of the Di erent Digits in Natural Numbers,"1 by …
Numbers Don’t Lie: Decoding Financial Error and Fraud …
(Setyawan, 2020). Moreover, Benford’s law is very useful in terms of detecting irregularities in financial statements (Gorenc, 2019). Benford's Law, also known as the First-Digit Law, is a …
Data Analysis Technologies - The Institute of Internal …
GTAG — How Can Data Analysis Help Internal Auditors? Benford’s law definition n Benford’s Law gives the expected frequencies of the digits in tabulated data. The set of expected digit …
Benford’s Law in Forensic Analysis of Income Statements of …
In the analysis of deviations from Benford’s law, in addition to the analysis of the first digit, an analysis of the first two digits can also be used. However, analyses of the first two digits can …
Desempeño del sistema de vigilancia COVID-19 en
For the analysis, Benford's law was used, a widely used statistical phenomenon that allows detecting anomalous data in the surveillance systems of each country. As of December 31, the …
Detecting Problems in Survey Data Using Benford's Law
Building on Benford's monotonie decreasing FSD distribution for naturally occur ring multiplicative data sets, our objective is to exhibit scale-invariant data that may be expected to obey …
Tax evasion detection in Nigeria: Analysis of the specific …
Sep 8, 2020 · Benford’s Law Technique Wells (2012) argued that Benford’s Law is one of the techniques available for fraud investigators and it assist greatly to achieve success in the field …
Fraud examination of Kingfisher Airlines - IJARIIT
Benford’s Law. This study looks for equity crowdfunding initial offerings that deviate from Benford’s Law. The foremost reason for choosing this model is because it aids the detection of frauds …
Benford’s law analysis to evaluate the quality data of COVID …
Benford’s law analysis was used to evaluate the first significant digit distribution of daily confirmed cases and COVID-19 related deaths in Indonesia. 2. METHOD A quantitative method was …
Benford’s Law, data mining, and financial Medicaid data
3.1 Benford’s Law analysis Following the data treatments described in Section 2, descriptive statistics for the data set (mean is greater than median, right skewed) indicate that the dataset …
Severe Testing of Benford's Law - arXiv.org
(non-)conformity with Benford’s law: the idea is that, provided some minimal con-ditions are met, genuine data should obey Benford’s law. Such delicate decisions should be taken using robust …
Detecting and Preventing Fraud with Data Analytics - Temple …
Benford’s Law Data analysis using Benford’s Law is really neat. It states that lists of numbers from many real-life sources of data are dis-tributed in a specific and non-uniform way. Number 1 …
Using Benford’s Law to Detect Suspected Creative …
that are submitted to lenders and tax authorities. In this context, Benford’s law has been presented as an objective tool to analyze large data. 2.1. Benford’s law in assurance and Latin …
