Modern Tools for Fraud Detection: Insights from the V4 and Ukraine

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21460%2F25%3A00385288" target="_blank" >RIV/68407700:21460/25:00385288 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/68407700:21460/25:00385289

Výsledek na webu

<a href="https://dbc.wroc.pl/publication/175556#description" target="_blank" >https://dbc.wroc.pl/publication/175556#description</a>

DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Modern Tools for Fraud Detection: Insights from the V4 and Ukraine

Popis výsledku v původním jazyce

This book highlights the lessons learned from the V4 countries and Ukraine, offering a comparative perspective on regulatory frameworks, enforcement mechanisms, and technological advancements in fraud detection. Each chapter examines a specific aspect of fraud detection, offering theoretical insights, empirical research and case studies that illustrate both the challenges and best practices in combating fraudulent activities. Chapter 1 explores the role of artificial intelligence (AI) in tax fraud detection. Chapter 2 investigates tax security and its vulnerabilities. In Chapter 3 the author focuses on occupational fraud, a major issue affecting both private and public sectors. Chapter 4 scrutinizes creative accounting practices, a deceitful technique used by businesses to manipulate financial statements. Chapter 5 studies Ukraine’s regulatory framework, the war’s effects on financial reporting, and the barriers to achieving accounting transparency. In Chapter 6 the author addresses the controversial issue of bank account blocking by tax authorities. Chapters 7 and 8 explore VAT fraud, particularly carousel fraud, one of the most damaging types of tax fraud in the EU. Chapter 9 shifts the focus to corporate anti-corruption efforts through non-financial reporting. Chapter 10 provides recommendations for fighting corruption, CIT fraud, PIT fraud, VAT fraud, money laundering and using AI and modern tools for preventing fraud. By bringing together academic research, policy analysis, and real-world case studies, this book aims to bridge the gap between theory and practice in fraud detection.] Publisher:

Název v anglickém jazyce

Modern Tools for Fraud Detection: Insights from the V4 and Ukraine

Popis výsledku anglicky

This book highlights the lessons learned from the V4 countries and Ukraine, offering a comparative perspective on regulatory frameworks, enforcement mechanisms, and technological advancements in fraud detection. Each chapter examines a specific aspect of fraud detection, offering theoretical insights, empirical research and case studies that illustrate both the challenges and best practices in combating fraudulent activities. Chapter 1 explores the role of artificial intelligence (AI) in tax fraud detection. Chapter 2 investigates tax security and its vulnerabilities. In Chapter 3 the author focuses on occupational fraud, a major issue affecting both private and public sectors. Chapter 4 scrutinizes creative accounting practices, a deceitful technique used by businesses to manipulate financial statements. Chapter 5 studies Ukraine’s regulatory framework, the war’s effects on financial reporting, and the barriers to achieving accounting transparency. In Chapter 6 the author addresses the controversial issue of bank account blocking by tax authorities. Chapters 7 and 8 explore VAT fraud, particularly carousel fraud, one of the most damaging types of tax fraud in the EU. Chapter 9 shifts the focus to corporate anti-corruption efforts through non-financial reporting. Chapter 10 provides recommendations for fighting corruption, CIT fraud, PIT fraud, VAT fraud, money laundering and using AI and modern tools for preventing fraud. By bringing together academic research, policy analysis, and real-world case studies, this book aims to bridge the gap between theory and practice in fraud detection.] Publisher:

Druh

O - Ostatní výsledky

CEP obor

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OECD FORD obor

50206 - Finance

Projekt

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Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2025

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů