Detecting Fraud from Accounting Restatements and Company Filings
A team of researchers in the MSS Department is researching the use of text mining to detect fraud from the EDGAR database. EDGAR -- the Electronic Data Gathering, Analysis, and Retrieval system — performs automated collection, validation, and indexing of submissions by companies who are required by law to file forms with the U.S. Securities and Exchange Commission (SEC).
This retrieval system comes with an API and we would like the incumbent to help with at least (possibly more) the following tasks:
S/He should be willing to attend our research meetings (in-person and zoom) and if desirable help write up results as deemed appropriate.
It may be possible to obtain research credits / independent study credits if so desired.
|Length of commitment||10-12 months|
|In-person, remote, or hybrid?||Hybrid Project|
|Level of collaboration||Individual student project|
|Who is eligible||All undergraduate students with Ability to code in Java, Python, MATLAB; Knowledge and extensive use of databases such as PostGres SQL, SQL; Experience developing visualization software; Prior research experience beyond class projects |
Once you begin the digital badge series, you will have access to all the necessary activities and instructions. Your mentor has indicated they would like you to also complete the specific preparation activities below. Please reference this when you get to Step 2 of the Preparation Phase.
fraud detection; machine learning, accounting , Management Science and Systems, Accounting