US 12,223,391 B1
Systems and methods for quantum based optimization of a personalized portfolio
Ramanathan Ramanathan, San Francisco, CA (US); Andrew J. Garner, IV, State Road, NC (US); Abhijit Rao, Irvine, CA (US); Pierre Arbajian, Matthews, NC (US); Michael Erik Meinholz, Charlotte, NC (US); Ramesh Yarlagadda, Charlotte, NC (US); Bradford A. Shea, Mint Hill, NC (US); and Adam Sanders, Huntersville, NC (US)
Assigned to Wells Fargo Bank, N.A., San Francisco, CA (US)
Filed by Wells Fargo Bank, N.A., San Francisco, CA (US)
Filed on Dec. 8, 2022, as Appl. No. 18/063,466.
Application 18/063,466 is a continuation of application No. 16/886,327, filed on May 28, 2020, granted, now 11,551,132.
Int. Cl. G06N 10/00 (2022.01); G06N 5/02 (2023.01)
CPC G06N 10/00 (2019.01) [G06N 5/02 (2013.01)] 20 Claims
OG exemplary drawing
 
1. A system for quantum computing (QC) based optimization of an efficient frontier determination, the system comprising:
QC optimization factor filtering circuitry configured to identify a plurality of filtered portfolio optimization factor data based on a risk level and one or more of a set of portfolio optimization factor data related to a portfolio, a set of QC algorithms, and algorithm performance information;
algorithm selection circuitry configured to select, automatically, one QC algorithm from the set of QC algorithms for each filtered portfolio optimization factor data of the plurality of filtered portfolio optimization factor data;
QC optimization circuitry configured to utilize the selected QC algorithm to optimize the efficient frontier determination for each identified filtered portfolio optimization factor data; and
processing circuitry configured to rebalance the portfolio based on the efficient frontier determination.