{"product_id":"using-analytics-to-detect-possible-fraud-isbn-9781118585627","title":"Using Analytics to Detect Possible Fraud","description":"\u003cb\u003eDetailed tools and techniques for developing efficiency and effectiveness in forensic accounting\u003c\/b\u003e  \u003cp\u003e\u003ci\u003eUsing Analytics to Detect Possible Fraud: Tools and Techniques\u003c\/i\u003e 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.\u003c\/p\u003e \u003cul\u003e \u003cli\u003eShows how to develop both efficiency and effectiveness in forensic accounting\u003c\/li\u003e \u003cli\u003eProvides information in such a way that non-practitioners can easily understand\u003c\/li\u003e \u003cli\u003eWritten in plain language: advanced mathematical skills are not required\u003c\/li\u003e \u003cli\u003eFeatures actual case studies using analytical tests\u003c\/li\u003e \u003c\/ul\u003e \u003cp\u003eEssential reading for every investor who wants to prevent financial fraud, \u003ci\u003eUsing Analytics to Detect Possible Fraud\u003c\/i\u003e allows practitioners to focus on areas that require further investigative techniques and to unearth deceptive financial reporting before it's too late.\u003c\/p\u003e \u003cp\u003ePreface xi\u003c\/p\u003e \u003cp\u003eAcknowledgments xv\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 1: Overview of the Companies 1\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eThe Four Companies 2\u003c\/p\u003e \u003cp\u003eCompany 1 2\u003c\/p\u003e \u003cp\u003eCompany 2 5\u003c\/p\u003e \u003cp\u003eCompany 3 8\u003c\/p\u003e \u003cp\u003eCompany 4 10\u003c\/p\u003e \u003cp\u003eSummary 16\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 2: The “Norm” and the “Forensic” Preliminary Analytics: Basics Everyone Should Know 19\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eLiquidity Ratios 20\u003c\/p\u003e \u003cp\u003eWorking Capital 21\u003c\/p\u003e \u003cp\u003eWorking Capital Index 21\u003c\/p\u003e \u003cp\u003eWorking Capital Turnover 22\u003c\/p\u003e \u003cp\u003eCurrent Ratio 22\u003c\/p\u003e \u003cp\u003eCase Studies: Liquidity Ratios 22\u003c\/p\u003e \u003cp\u003eProfitability Ratios 25\u003c\/p\u003e \u003cp\u003eGross Profit 26\u003c\/p\u003e \u003cp\u003eGross Profit Margin 26\u003c\/p\u003e \u003cp\u003eStock Sales 26\u003c\/p\u003e \u003cp\u003eReturn on Equity 27\u003c\/p\u003e \u003cp\u003eCase Studies: Profitability Ratios 27\u003c\/p\u003e \u003cp\u003eCompany 1 31\u003c\/p\u003e \u003cp\u003eHorizontal Analysis 36\u003c\/p\u003e \u003cp\u003eCompany 1 36\u003c\/p\u003e \u003cp\u003eCompany 2 43\u003c\/p\u003e \u003cp\u003eCompany 3 50\u003c\/p\u003e \u003cp\u003eCompany 4 61\u003c\/p\u003e \u003cp\u003eVertical Analysis 66\u003c\/p\u003e \u003cp\u003eCompany 1 66\u003c\/p\u003e \u003cp\u003eCompany 2 70\u003c\/p\u003e \u003cp\u003eCompany 3 73\u003c\/p\u003e \u003cp\u003eCompany 4 79\u003c\/p\u003e \u003cp\u003eSummary 79\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 3: The Importance of Cash Flows and Cash Flow Statements 83\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eCash Flows and Net Income 85\u003c\/p\u003e \u003cp\u003eCompany 1 87\u003c\/p\u003e \u003cp\u003eCompany 2 89\u003c\/p\u003e \u003cp\u003eCompany 3 92\u003c\/p\u003e \u003cp\u003eCompany 4 97\u003c\/p\u003e \u003cp\u003eOther Cash Flow Techniques 100\u003c\/p\u003e \u003cp\u003eCompany 1 101\u003c\/p\u003e \u003cp\u003eCompany 2 104\u003c\/p\u003e \u003cp\u003eCompany 3 107\u003c\/p\u003e \u003cp\u003eCompany 4 114\u003c\/p\u003e \u003cp\u003eSummary 117\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 4: The Beneish M-Score Model 119\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eCompany 1 124\u003c\/p\u003e \u003cp\u003eCompany 2 133\u003c\/p\u003e \u003cp\u003eCompany 3 143\u003c\/p\u003e \u003cp\u003eIndices of the Primary Government 145\u003c\/p\u003e \u003cp\u003eIndices of the Governmental Funds 151\u003c\/p\u003e \u003cp\u003eCompany 4 158\u003c\/p\u003e \u003cp\u003eSummary 166\u003c\/p\u003e \u003cp\u003eNotes 170\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 5: The Accruals 171\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eDechow–Dichev Accrual Quality 173\u003c\/p\u003e \u003cp\u003eThe Four Companies: Dechow–Dichev Model 175\u003c\/p\u003e \u003cp\u003eSloan’s Accruals 184\u003c\/p\u003e \u003cp\u003eThe Four Companies: Sloan’s Model 185\u003c\/p\u003e \u003cp\u003eJones Nondiscretionary Accruals 191\u003c\/p\u003e \u003cp\u003eThe Four Companies: Jones Model 192\u003c\/p\u003e \u003cp\u003eSummary 196\u003c\/p\u003e \u003cp\u003eNotes 198\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 6: Analysis Techniques Using Historical Financial Statements and Other Company Information 199\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eThe Piotroski F-Score Model 200\u003c\/p\u003e \u003cp\u003eCompany 1 203\u003c\/p\u003e \u003cp\u003eCompany 2 205\u003c\/p\u003e \u003cp\u003eCompany 3 207\u003c\/p\u003e \u003cp\u003eCompany 4 212\u003c\/p\u003e \u003cp\u003eLev–Thiagarajan’s 12 Signals 215\u003c\/p\u003e \u003cp\u003eCompany 1 220\u003c\/p\u003e \u003cp\u003eCompany 2 222\u003c\/p\u003e \u003cp\u003eCompany 3 225\u003c\/p\u003e \u003cp\u003eCompany 4 230\u003c\/p\u003e \u003cp\u003eSummary 233\u003c\/p\u003e \u003cp\u003eNotes 235\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 7: Benford's Law, and Yes—Even Statistics 237\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eBenford’s Law 239\u003c\/p\u003e \u003cp\u003eCompany 1 243\u003c\/p\u003e \u003cp\u003eCompany 2 249\u003c\/p\u003e \u003cp\u003eCompany 3 255\u003c\/p\u003e \u003cp\u003eCompany 4 267\u003c\/p\u003e \u003cp\u003eSimple Statistics 272\u003c\/p\u003e \u003cp\u003eCompany 1 277\u003c\/p\u003e \u003cp\u003eCompany 2 281\u003c\/p\u003e \u003cp\u003eCompany 3 284\u003c\/p\u003e \u003cp\u003eCompany 4 289\u003c\/p\u003e \u003cp\u003eSummary 290\u003c\/p\u003e \u003cp\u003eNote 292\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 8: Grading the Four Companies 293\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eCompany 1 294\u003c\/p\u003e \u003cp\u003eCompany 2 302\u003c\/p\u003e \u003cp\u003eCompany 3 310\u003c\/p\u003e \u003cp\u003eCompany 4 320\u003c\/p\u003e \u003cp\u003eSummary 326\u003c\/p\u003e \u003cp\u003eBibliography 329\u003c\/p\u003e \u003cp\u003eAbout the Author 331\u003c\/p\u003e \u003cp\u003eIndex 333\u003c\/p\u003e  \u003cp\u003e\u003cb\u003ePAMELA S. MANTONE, CPA, CFF, CITP, CGMA, CFE, FCPA,\u003c\/b\u003e is a Senior Assurance Manager at Joseph Decosimo \u0026amp; Company, PLLC, practicing in the areas of audit and attestation with a focus on forensic accounting, fraud examination and audits of financial institutions, nonprofit organizations, publicly traded companies and governments. She provides forensic accounting services, with an emphasis on embezzlement and fraudulent financial information for multiple organizations, as well as consulting services regarding the implementation of fraud prevention and fraud protection internal control systems.   \u003c\/p\u003e\u003cp\u003e\u003cb\u003eUSING ANALYTICS TO DETECT POSSIBLE FRAUD\u003c\/b\u003e\u003cbr\u003e Tools and Techniques \u003c\/p\u003e\u003cp\u003eForensic accounting is the hot new field in accounting, involving essential investigative techniques that uncover accounting fraud and enable practitioners to be effective in covering the needs of the engagement. \u003c\/p\u003e\u003cp\u003e\u003ci\u003eUsing Analytics to Detect Possible Fraud: Tools and Techniques\u003c\/i\u003e presents a plain-English guide to forensic accounting, providing analytical tools and techniques that allow professionals analyzing financial statements to zero in on anomalies. Certified Fraud Examiner Pamela Mantone introduces a variety of techniques starting from the very basic, simple analytics to more advanced analytical tools that equip forensic accountants, forensic investigators, and fraud investigators to develop further investigative work. \u003c\/p\u003e\u003cp\u003eFeaturing case studies throughout from four companies, illustrating the application of tools included in the book, \u003ci\u003eUsing Analytics to Detect Possible Fraud\u003c\/i\u003e demonstrates how to interpret the results of the testing in each case study, with techniques including: \u003c\/p\u003e\u003cul\u003e \u003cli\u003eLiquidity ratios\u003c\/li\u003e \u003cli\u003eProfitability ratios\u003c\/li\u003e \u003cli\u003eHorizontal analysis\u003c\/li\u003e \u003cli\u003eVertical analysis\u003c\/li\u003e \u003cli\u003eCash realized from operations\u003c\/li\u003e \u003cli\u003eAnalyzing cash realized from operations to net income from operations\u003c\/li\u003e \u003cli\u003eThe Beneish M-Score Model\u003c\/li\u003e \u003cli\u003eDechow-Dichev Accrual Quality\u003c\/li\u003e \u003cli\u003eSloan's Accruals\u003c\/li\u003e \u003cli\u003eJones Non-discretionary Accruals\u003c\/li\u003e \u003cli\u003eThe Piotroski F-Score Model\u003c\/li\u003e \u003cli\u003eLev-Thiagarajan's 12 Signals\u003c\/li\u003e \u003cli\u003eBenford's Law\u003c\/li\u003e \u003cli\u003eZ-Score Analysis\u003c\/li\u003e \u003cli\u003eCorrelation\u003c\/li\u003e \u003cli\u003eRegression Analysis\u003c\/li\u003e \u003c\/ul\u003e \u003cp\u003eEssential reading for every financial investigator, \u003ci\u003eUsing Analytics to Detect Possible Fraud\u003c\/i\u003e allows practitioners to focus on areas that require further investigative techniques and to unearth deceptive financial reporting.\u003c\/p\u003e","brand":"Wiley","offers":[{"title":"Default Title","offer_id":47990442328293,"sku":"NP9781118585627","price":95.0,"currency_code":"USD","in_stock":false}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/1842\/7735\/files\/9781118585627.jpg?v=1761787847","url":"https:\/\/k12savings.com\/products\/using-analytics-to-detect-possible-fraud-isbn-9781118585627","provider":"K12savings","version":"1.0","type":"link"}