  Banks publish daily a list of available securities/assets (axe list) to
selected clients to help them effectively locate Long (buy) or Short (sell)
trades at reduced financing rates. This reduces costs for the bank, as the list
aggregates the bank's internal firm inventory per asset for all clients of long
as well as short trades. However, this is somewhat problematic: (1) the bank's
inventory is revealed; (2) trades of clients who contribute to the aggregated
list, particularly those deemed large, are revealed to other clients. Clients
conducting sizable trades with the bank and possessing a portion of the
aggregated asset exceeding $50\%$ are considered to be concentrated clients.
This could potentially reveal a trading concentrated client's activity to their
competitors, thus providing an unfair advantage over the market.
  Atlas-X Axe Obfuscation, powered by new differential private methods, enables
a bank to obfuscate its published axe list on a daily basis while under
continual observation, thus maintaining an acceptable inventory Profit and Loss
(P&L) cost pertaining to the noisy obfuscated axe list while reducing the
clients' trading activity leakage. Our main differential private innovation is
a differential private aggregator for streams (time series data) of both
positive and negative integers under continual observation.
  For the last two years, Atlas-X system has been live in production across
three major regions-USA, Europe, and Asia-at J.P. Morgan, a major financial
institution, facilitating significant profitability. To our knowledge, it is
the first differential privacy solution to be deployed in the financial sector.
We also report benchmarks of our algorithm based on (anonymous) real and
synthetic data to showcase the quality of our obfuscation and its success in
production.
