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Online Meeting Information

Meeting Information

Date & Time:    Tuesday, December 9, 2019   3:00PM

Location  ZOOM:      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)


 Click here to expand...

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)


Gather feedback on Open Issues and Concerns

Review Survey Questions & FAQ

4:00 pm

Schedule F/U Call?  - Close Meeting

Next meeting:  Monday, January 27, 2020 at 3:00 pm.  

Upcoming Meetings: 2019-2020 CCCApply Sub-Committee Meeting Schedule

Key Take-Aways from the Meeting

The Spam Filter Web Service is evolving and the machine-learning model and prediction service are being updated regularly.  

Our goal is to continue to improve and enhance the service over time until we have a sustainable model with a 99% level of accuracy that is continuously retraining itself on a comfortable cadence for colleges.

Share updates and stats on performance

Encourage colleges to continue to monitor and tag spam


Discuss concerns 

Next meeting:  Monday, January 27, 2020 at 3:00 pm.  

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 %


Notes from Nov 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


  • 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


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 Negatives

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.

SPAM Drop File Information

Please provide bulk fraudulent applications in the format specified below:

  • File Format = .TXT
  • File Naming Convention = CollegeMISCode_Fraud_mmddyy.txt
  • Confirmation #  (only1 confirmation # per line)

Merrie Wales

Patty Donohue

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

Feedback / Issues

Colleges want specific email address domains blocked.  Patty will confirm that this can be done using an Error Message Rule in the Administrator by the college.

We currently block (new) IP Regions if they appear to be used in fraud signatures

Mitch from Santa Rosa College says they no longer give out .edu addresses until the student is fully matriculated and registered for classes or paid

Spammers are committing IDENTITY THEFT - stealing real personal identifiable information for seeking financial aid (fraud).

Becky from Shasta - built in a process to get a report to review apps quickly (includes IP Address in report) - internal   

San Bernardino Valley & Crafton Hills College has implemented - GMail account is restricted until after they register - originally set up to email staff and other students, but found they are phishing other students, so they no longer allow them to email other students.  (look into Gmail registration settings - different set of policies) - and this cut their spam in half. 

Question asked if we could do model updates more frequently than 2-3 weeks - we would like to and will see what's possible. We 

Address Validation > Why are we allowing students to bypass the CASS address validation? This could be looked at - spammers are putting in bad addresses. 

What are spammers going for?

Spammers are specifically going for the FREE Google Drive storage 

Change Enhancements

  • Add a way to search by other data (whatever the columns are) CCCID, Email Address, DOB, etc. 
  • Add the IP Address to the spam filter summary table
  • Add the Country that matches the IP Address or Region to the spam filter summary table
  • Look into a Zip Code / Area Code validation check
  • Create ability to create a rule based on any data that puts the application directly into the Spam Filter (or prevents it/whitelist)  - ask Josh (don't use the model if the app meets the rule logic)  (would have to bypass the prediction service 
  • What's the situation with ReCAPTCHA (is our current version so outdated that it's ineffective?) Is OpenCCC redesign planning to include an updated version?  Which tool and which version?  Why do we not have one in the Application?  Get history on this and inform the group.
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