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Fraud Analytics Using Descriptive, Predictive, and Social Network Techniques : A Guide to Data Science for Fraud Detection
Published by Wiley & Sons, Incorporated, John, 2015
ISBN 10: 1119133122 ISBN 13: 9781119133124
Language: English
Condition: Very Good. Former library book; may include library markings. Used book that is in excellent condition. May show signs of wear or have minor defects.
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hardcover. Condition: Good. 1st Edition. Ships in a BOX from Central Missouri! May not include working access code. Will not include dust jacket. Has used sticker(s) and some writing or highlighting. UPS shipping for most packages, (Priority Mail for AK/HI/APO/PO Boxes).
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Condition: good. May show signs of wear, highlighting, writing, and previous use. This item may be a former library book with typical markings. No guarantee on products that contain supplements Your satisfaction is 100% guaranteed. Twenty-five year bookseller with shipments to over fifty million happy customers.
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hardcover. Condition: Good. Ships Out Tomorrow!
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hardcover, Condition: Very Good, Wiley, NY, c.2015, 1st., 8vo., hardcover, 367pp., VG+/VG+ $.
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Fraud Analytics Using Descriptive, Predictive, and Social Network Techniques A Guide to Data Science for Fraud Detection
Published by John Wiley & Sons, Incorporated, 2015
ISBN 10: 1119133122 ISBN 13: 9781119133124
Language: English
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Hardback or Cased Book. Condition: New. Fraud Analytics Using Descriptive, Predictive, and Social Network Techniques: A Guide to Data Science for Fraud Detection 1.3. Book.
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Fraud Analytics Using Descriptive, Predictive, and Social Network Techniques (Hardcover)
Published by John Wiley & Sons Inc, New York, 2015
ISBN 10: 1119133122 ISBN 13: 9781119133124
Language: English
Hardcover. Condition: new. Hardcover. 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 dataUtilize labeled, unlabeled, and networked dataDetect fraud before the damage cascadesReduce 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. 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. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
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Fraud Analytics Using Descriptive, Predictive, and Social Network Techniques : A Guide to Data Science for Fraud Detection
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Fraud Analytics Using Descriptive, Predictive, and Social Network Techniques: A Guide to Data Science for Fraud Detection (Wiley and SAS Business Series)
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Fraud Analytics Using Descriptive, Predictive, and Social Network Techniques: A Guide to Data Science for Fraud Detection
Published by John Wiley & Sons Inc, 2015
ISBN 10: 1119133122 ISBN 13: 9781119133124
Language: English
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Add to basketCondition: New. Series: Wiley and SAS Business Series. Num Pages: 400 pages. BIC Classification: JKVK; KJM; UNF. Category: (P) Professional & Vocational. Dimension: 167 x 237 x 34. Weight in Grams: 614. . 2015. 1st Edition. Hardcover. . . . .
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Fraud Analytics Using Descriptive, Predictive, and Social Network Techniques : A Guide to Data Science for Fraud Detection
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
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Add to basketCondition: good. May show signs of wear, highlighting, writing, and previous use. This item may be a former library book with typical markings. No guarantee on products that contain supplements Your satisfaction is 100% guaranteed. Twenty-five year bookseller with shipments to over fifty million happy customers.
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Fraud Analytics Using Descriptive, Predictive, and Social Network Techniques: A Guide to Data Science for Fraud Detection
Published by John Wiley & Sons Inc, 2015
ISBN 10: 1119133122 ISBN 13: 9781119133124
Language: English
Seller: THE SAINT BOOKSTORE, Southport, United Kingdom
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Fraud Analytics Using Descriptive, Predictive, and Social Network Techniques : A Guide to Data Science for Fraud Detection
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
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Condition: New. pp. 384.
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Fraud Analytics Using Descriptive, Predictive, and Social Network Techniques: A Guide to Data Science for Fraud Detection
Published by John Wiley & Sons Inc, 2015
ISBN 10: 1119133122 ISBN 13: 9781119133124
Language: English
Condition: New. Series: Wiley and SAS Business Series. Num Pages: 400 pages. BIC Classification: JKVK; KJM; UNF. Category: (P) Professional & Vocational. Dimension: 167 x 237 x 34. Weight in Grams: 614. . 2015. 1st Edition. Hardcover. . . . . Books ship from the US and Ireland.
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Fraud Analytics Using Descriptive, Predictive, and Social Network Techniques A Guide to Data Science for Fraud Detection
Published by John Wiley & Sons Inc, 2015
ISBN 10: 1119133122 ISBN 13: 9781119133124
Language: English
US$ 61.79
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Add to basketHardcover. Condition: Brand New. 1st edition. 400 pages. 9.06x6.38x1.42 inches. In Stock.
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Add to basketBuch. Condition: Neu. Neuware - Detect fraud earlier to mitigate loss and prevent cascading damageFraud 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 securityThe 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.
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Fraud Analytics Using Descriptive, Predictive, and Social Network Techniques (Hardcover)
Published by John Wiley & Sons Inc, New York, 2015
ISBN 10: 1119133122 ISBN 13: 9781119133124
Language: English
US$ 44.47
Convert currencyUS$ 49.18 shipping from United Kingdom to U.S.A.Quantity: 1 available
Add to basketHardcover. Condition: new. Hardcover. 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 dataUtilize labeled, unlabeled, and networked dataDetect fraud before the damage cascadesReduce 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. 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. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
