Online Meeting Information
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Date & Time: Tuesday, December 9, 2019 3:00PM Location ZOOM: https://cccconfer.zoom.us/j/6770513851 MEETING ID: 677-051-3851 Use VoiP or Call TOLL Telephone: Dial: +1 408 638 0968 (US Toll) or +1 646 876 9923 (US Toll) |
Agenda
| TIME | DESCRIPTION |
| 3:00pm | Introductions: - (Attendees, please add your Name, College, and your Title in the chat window when you enter into the me |
Status update (stats on incoming fraud and model overview) | |
| Roadmap: Upcoming changes to Model and UI) | |
| Communication | |
| Gather feedback on Open Issues and Concerns | |
| Review Survey Questions & FAQ | |
4:00 pm | Schedule F/U Call? - Close Meeting |
Upcoming Meetings: 2019-2020 CCCApply Sub-Committee Meeting Schedule
Key Messages:
Share updates and stats on performance
Encourage colleges to continue to monitor and tag spam
Survey
Discuss concerns
College Survey
Help us to better understand fraud coming in at your college. Please complete the survey
CCCApply Spam Filter College Survey
Spam Filter Project Update
Speakers: Machine-Learning Data Analysts: Harsha Gopianandan, Ananth Gopalakrishnan
Despite spikes in spam over the six weeks or so, the performance of the spam filter service is netting a 95-98% accuracy. Below are the stats from Nov 23 - 27, 2019.
November 23 - 27
Total applications: 19,943
True Positive 938
True Negative 18,965
False Positive 13
False Negative 22
Accuracy 99.7994283709 %
Precision 98.6330178759 %
Recall 97.7083333333 %
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Notes from PPTNov 12 meeting:
Harsha Gopianandan from the Spam Filter Machine Learning team explained about false positives and false negatives and why we are seeing both across the system.
He explained how the model works and encouraged colleges to keep tagging diligently so that model can learn from all new signatures.
Getting ready to update the model again with the Model with PII (December 2019).
We talked about sending false negatives to the Tech Center and we will bulk tag them and upload to the model, so the model can benefit from the identified false negatives
Roadmap
- August 24 - Last Model Update
- November 22 - Pii Data Added to Model and Other Enhancements (IP Region, Email Domain)
- December 12 - Manual Retraining Model with Updated Data
Ongoing
Update the model every 2-3 weeks.
Update with the latest data.
Update the model with new features.
*Note: Derived data from PII data is used.
Taking that info and transforming it in a way that is useful to the model.
We can't automatically block domains, because the spammers keep changing their tactics.
Top 10 Criteria
College ID
Email domain
Major Code
Communication Issues
FAQ is finished and will be sent to your contact list.
Send Us False Positives
If your college identifies a quantity (20 or more) of fraud applications that were NOT caught and suspended by the spam filter, please send them to us using the instructions below.
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SPAM Drop File Information Please provide bulk fraudulent applications in the format specified below:
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We ask that all colleges follow the file format below. If you would like to include any information other than confirmation #, please provide that information in a separate file. For ease of input in the model