Modern Benford's Law: State of the Art Techniques for Audit and Compliance Professionals
暫譯: 現代本福德定律：審計與合規專業人士的最新技術
McCarville, Daniel J.
- 出版商: CRC
- 出版日期: 2026-02-26
- 售價: $6,440
- 貴賓價: 9.8 折 $6,311
- 語言: 英文
- 頁數: 142
- 裝訂: Hardcover - also called cloth, retail trade, or trade
- ISBN: 1032910399
- ISBN-13: 9781032910390
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相關分類:
Data-mining
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相關主題
商品描述
Benford's Law offers a powerful, data-driven approach to anomaly detection. Discovered 150 years ago, it wasn't until the 1990s that auditors began harnessing its potential for identifying irregularities in financial data. Today, the Benford's Law community spans a wide range of professions and academic disciplines.
This book provides the latest research-based techniques packaged for ready usage by auditors and audit analytics professionals. Discover how to use Benford's Law in continuous monitoring and pinpoint non-compliant vendors, accounts or other groups. Visual examples demonstrate how to identify and interpret the most common patterns Benford's Law surfaces.
Auditors and assurance professionals will benefit from clear, practical explanations of advanced methods, making it easier to integrate these techniques into their workflows. Meanwhile, analytics and quantitative experts will find a rich toolkit of new techniques to enhance their capabilities. Whether you're new to Benford's Law or looking to deepen your expertise, this book equips you with the tools to transform how you detect anomalies in data.
商品描述(中文翻譯)
本福德定律（Benford's Law）提供了一種強大的數據驅動異常檢測方法。這一法則在150年前被發現，但直到1990年代，審計師才開始利用其潛力來識別財務數據中的不規則性。如今，本福德定律的社群涵蓋了廣泛的職業和學術領域。
本書提供了最新的基於研究的技術，方便審計師和審計分析專業人士直接使用。了解如何在持續監控中使用本福德定律，並精確找出不合規的供應商、帳戶或其他群體。視覺範例展示了如何識別和解釋本福德定律所顯示的最常見模式。
審計師和保證專業人士將受益於清晰、實用的高級方法解釋，使他們更容易將這些技術整合到工作流程中。同時，分析和定量專家將發現一套豐富的新技術工具，以增強他們的能力。無論您是本福德定律的新手，還是希望深化專業知識，本書都為您提供了轉變數據異常檢測方式的工具。
作者簡介
Daniel J. McCarville is a recognized audit analytics professional, researcher, and speaker with more than a decade of experience developing advanced tools for auditors and compliance teams. He currently leads the audit analytics team at an S&P 500 insurance firm. His statistical expertise spans Benford's Law, machine learning, and simulation, which he applies to detect anomalies and strengthen decision-making.
His peer-reviewed research has introduced novel applications of Benford's Law and new methods for identifying irregularities in standardized test data. He has published in Emerald Open Research and received the National Legislative Program Evaluation Society's Impact Award multiple times.
Daniel has presented at major professional conferences, including IIA events, and frequently speaks at universities to inspire the next generation of data professionals. He holds a master's degree in political science from the University of Kansas, as well as Data Science from Eastern University. He also holds CIA and CRMA designations from the Institute of Internal Auditors and DASM certification from the Project Management Institute.
作者簡介(中文翻譯)
丹尼爾·J·麥卡維爾（Daniel J. McCarville）是一位公認的審計分析專業人士、研究者和演講者，擁有超過十年的經驗，專注於為審計師和合規團隊開發先進工具。他目前在一家標準普爾500指數的保險公司領導審計分析團隊。他的統計專業知識涵蓋本福德定律（Benford's Law）、機器學習和模擬，並應用於檢測異常和加強決策。
他的同行評審研究引入了本福德定律的新應用以及識別標準化測試數據中不規則性的全新方法。他曾在《Emerald Open Research》上發表文章，並多次獲得全國立法計畫評估協會的影響力獎（Impact Award）。
丹尼爾曾在主要專業會議上發表演講，包括IIA活動，並經常在大學演講，以激勵下一代數據專業人士。他擁有堪薩斯大學的政治學碩士學位，以及東方大學的數據科學學位。他還持有內部審計師協會的CIA和CRMA資格，以及項目管理協會的DASM認證。
