US 11,995,732 B2
Computer platforms designed for improved electronic execution of electronic transactions and methods of use thereof
James Toffey, Newark, NJ (US); Spenser Huston, Newark, NJ (US); Vijay Mayadas, Newark, NJ (US); William Gartland, Newark, NJ (US); Thomas Duignan, Newark, NJ (US); Rick Montgomery, Newark, NJ (US); Albert John Cass, Newark, NJ (US); Suneel Nallagonda, Newark, NJ (US); and Bryan Moore, Newark, NJ (US)
Assigned to Broadridge Fixed Income Liquidity Solutions, LLC, Newark, NJ (US)
Filed by Broadridge Fixed Income Liquidity Solutions, LLC, Newark, NJ (US)
Filed on Aug. 1, 2023, as Appl. No. 18/363,534.
Application 18/363,534 is a continuation of application No. 17/174,229, filed on Feb. 11, 2021, granted, now 11,810,213.
Application 17/174,229 is a continuation of application No. 16/879,327, filed on May 20, 2020, granted, now 10,922,773, issued on Feb. 16, 2021.
Application 16/879,327 is a continuation of application No. 16/805,401, filed on Feb. 28, 2020, abandoned.
Claims priority of provisional application 62/812,602, filed on Mar. 1, 2019.
Prior Publication US 2023/0377075 A1, Nov. 23, 2023
Int. Cl. G06Q 50/18 (2012.01); G06Q 40/04 (2012.01); G06Q 40/06 (2012.01)
CPC G06Q 50/188 (2013.01) [G06Q 40/04 (2013.01); G06Q 40/06 (2013.01)] 30 Claims
OG exemplary drawing
 
1. A computer-implemented method comprising:
receiving, at a computing device having one or more processors, historical trading data associated with previously executed trade transactions for a financial instrument by a plurality of candidate invitee users;
wherein the historical trading data comprises, for each trade transaction, at least a price and quantity traded of the financial instrument;
receiving, at the computing device, trading intentions from the plurality of candidate invitee users, each trading intention representing a price and a quantity at which its associated candidate invitee user would trade the financial instrument;
modelling, at the computing device, a score for each candidate invitee user based on inputting into a machine learning model:
the trading intentions of each candidate invitee user for the financial instrument and
the historical trading data associated with each candidate invitee user,
wherein the score is representative of a likelihood of successfully trading the financial instrument;
establishing, by a computing device, an electronic communication session configured for trading the financial instrument between an initiating user and a plurality of selected invitee users;
wherein the electronic communication session comprises a stack software object that controls at least one instance of the electronic communication session according to a set of participation levels;
coordinating, by the computing device via the stack software object, communications during the electronic communication session;
wherein a first participation level of the set of participation levels is configured to:
permit each invitee user to submit an offer to trade the financial instrument with the initiating user,
wherein the electronic communication session is configured to:
determine, at the computing device, a plurality of offers from the plurality of invitee users, the plurality of offers, when aggregated, achieve a maximum value for a predetermined position, as communicated by the initiating user, in a target financial instrument; and
transmit, from the computing device, to the plurality of invitee users an acceptance of each offer of the plurality of offers to aggregate the plurality of offers for the trade.