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Board Meeting 10:00 a.m. Tuesday, April 23<sup>rd</sup>Board Meeting 10:00 a.m. Tuesday, April 23rd The Board  will be meeting at 10:00 a.m. on Tuesday, April 23rd. Members of the public will not be allowed inside the building. Members of the public who are interested have 2 options to listen to the Board meeting: By phone  1-202-599-1426  conference ID: 624 061 844#,One-touch Dial: 1-202-599-1426,624061844#
          By browser Board Meeting Tuesday, April 23rd
Click the above button and choose 'Continue on this browser' Attendees using the Teams link will be able to listen to the meeting and view the materials
          being discussed. Their lines will be muted.


Federal Retirement Thrift Investment Board
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Data Governance
Artificial Intelligence (AI) Use Case Inventory Content start
          Artificial Intelligence (AI) Use Case Inventory

In accordance with Section 5(e) of Executive Order 13960, FRTIB has reviewed and prepared its Inventory of Artificial Intelligence (AI) use cases. FRTIB is committed to upholding the principles outlined in EO 13960, and will review and update the public AI Use Case inventory as needed in the future.


Use Cases

FRTIB Artificial Intelligence (AI) Use Cases:


AVA Chatbot
AVA Chatbot
FRTIB’s virtual assistant (AVA) uses artificial intelligence and natural language processing (NLP) to answer common retirement-related questions and help participants get information about their TSP plan through tsp.gov. Through natural language processing, AVA has the ability to refine and increase the accuracy of responses from the virtual assistant bot as more participants utilize the virtual assistant. For participants who are logged into their TSP Account, AVA also offers the ability to connect to a human representative via chat to augment any situations where AVA is unable to provide answers directly.

Birdeye
Anti-Fraud platform
FRTIB’s Anti-Fraud platform uses machine learning (ML) based supervised/unsupervised models and rules to detect and prevent fraudulent activity by scoring risk and generating alerts on participant conducted transactions. Alerts are worked by fraud investigators to do further investigation and provide final ruling. The platform utilizes reinforcement learning techniques to improve the accuracy of the platform over time, learning from confirmed fraud alerts to update its model and improve fraud detection and reduce the occurrence of false positives. Overall, the use of machine learning and modeling helps FRTIB to detect and prevent fraudulent transactions.


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