Business Intelligence SIG: Detection of Irregularities in Accounting Data



  • The Monthly Meeting of the Business Intelligence SIG


    Presentation Overview

    Large Scale Detection of Irregularities in Accounting Data

    In recent years, there have been several large accounting frauds where a company's financial results have been intentionally misrepresented by billions of dollars. In response, regulatory bodies have mandated that auditors perform analytics on detailed financial data with the intent of discovering such misstatements. For a large auditing firm, this may mean analyzing millions of records from thousands of clients. In this talk, I will discuss techniques for automatic analysis of company general ledgers on such a large scale to identify irregularities -- which may indicate fraud or just honest errors -- for additional review by auditors. These techniques have been implemented in a prototype system, called Sherlock, which combines aspects of classification, anomaly detection, and signature identification.


    About the Presenter

    Stephen Bay, Center for Advanced Research, PricewaterhouseCoopers LLP,

    Stephen Bay is the analytics lead on Project Sherlock at PricewaterhouseCoopers LLP. The goal of Project Sherlock is to detect risks of potential financial statement error or fraud by uncovering anomalous activity in a company's general ledger. Stephen received his Ph.D. from U.C. Irvine in 2001, and Master's and Bachelor's degrees from the University of Waterloo. Prior to joining PricewaterhouseCoopers, Stephen worked at the Center for the Study of Language and Information at Stanford University, and the Institute for the Study of Learning and Expertise.


    Event Logistics


    Cubberley Community Center

    4000 Middlefield Road, Room H-1

    Palo Alto, CA


    6:30 - 7:00 p.m. Registration / Networking / Refreshments (please arrive before 7:00 p.m.)

    7:00 - 8:30 p.m. Presentation and Discussion



    $15 at the door for non-SDForum members

    No charge for SDForum members

    No registration required

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