Forensic Finance
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Forensic Finance SOLVED PAPERS AND GUESS
Product Details: PUNE UNIVERSITY Forensic Finance
Format: BOOK
Pub. Date: NEW EDITION APPLICABLE FOR Current EXAM
Publisher: MEHTA SOLUTIONS
Edition Description: 2019-20
RATING OF BOOK: EXCELLENT
ABOUT THE BOOK
FROM THE PUBLISHER
If you find yourself getting fed up and frustrated with other INDRAPRASTHA UNIVERSITY book solutions now mehta solutions brings top solutions for INDRAPRASTHA UNIVERSITY Forensic Finance REPORT book contains previous year solved papers plus faculty important questions and answers specially for INDRAPRASTHA UNIVERSITY .questions and answers are specially design specially for INDRAPRASTHA UNIVERSITY students .
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Forensic Finance
Unit I
Introduction to Forensic Accounting, Role of Forensic Auditor/ Forensic Accountants. Fraud triangle, motivation for manipulation of financial statement: measurement of risk and reward by perpetuator of financial frauds. Legal requirement for independent investigation in case of frauds. Recording of evidence, disposition and testimony. Guidelines for professional standards and conduct relating to Forensic Engagement. (12 Hours)
Unit II
Planning and preparing financial forensic investigation. Defining terms of engagement, working with legal professionals. Overview of evidence identification and collection for legal matters. Techniques of investigation in case of electronically stored information. Process to examine electronically stored data. (10 Hours)
Unit III
Computation of economic damage and assessment of legal issues. Impact of fraud on business and society. Types of fraud schemes. Fraud risk assessment and process control. Measurement of financial stress and degree of internal controls. Common types of internal & external assets misappropriation. (10 Hours)
Unit IV
Modelling for Fraud prediction, use of data science, artificial intelligence, machine learning Investigating massive amount of data for detecting fraudulent transaction, classification problems Spam Detectors, Loan Default prediction, bankruptcy prediction. Prediction of misuse of Credit card & Debit card. Use of random Forests Classifier to predict fraudulent transactions
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