US 11,810,188 B1
Electronic identification and reporting of errors in credit reports
David Bergida, Las Vegas, NV (US); and Ari Gross, Las Vegas, NV (US)
Assigned to Credit Versio LLC, Las Vegas, NV (US)
Filed by Credit Versio LLC, Las Vegas, NV (US)
Filed on Jul. 30, 2021, as Appl. No. 17/390,323.
Claims priority of provisional application 63/059,922, filed on Jul. 31, 2020.
Int. Cl. G06Q 40/00 (2023.01); G06F 16/215 (2019.01); G06F 16/23 (2019.01); G06F 40/40 (2020.01); G06Q 40/03 (2023.01); G06Q 40/12 (2023.01)
CPC G06Q 40/03 (2023.01) [G06F 16/215 (2019.01); G06F 16/2365 (2019.01); G06F 40/40 (2020.01); G06Q 40/12 (2013.12)] 13 Claims
OG exemplary drawing
 
1. A method for electronically detecting errors in a first credit report of an individual from a first credit agency and a second credit report of the individual from a second credit agency, the method comprising:
electronically receiving, using a computer system with a hardware computer processor, credit reports produced by the first and second credit agency;
using the hardware computer processor to:
identify a first category of errors in the first credit report by finding contradictions contained within each account in the first credit report;
identify a first category of errors in the second credit report by finding contradictions contained within each account in the second credit report;
identify a second category of errors in the first credit report by finding contradictions or duplications by comparing at least two accounts in the first credit report;
identify a second category of errors in the second credit report by finding contradictions or duplications by comparing at least two accounts in the second credit report;
identify a third category of errors by finding discrepancies in at least one account found in both the first and second credit reports;
electronically store previous versions of the first credit report and the second credit report, the previous versions electronically readable by the hardware computer processor;
identify a fourth category of errors in the first credit report by finding discrepancies between the first credit report and at least one previous credit report for the individual from the first agency; and
identify a fourth category of errors in the second credit report by finding discrepancies between the second credit report and at least one previous credit report for the individual from the second agency,
wherein each of the identifying steps is performable by the processor without human intervention;
in response to identifying at least one category of errors, present the errors to a human user together with an electronic display interface for selecting errors to include or omit; and
generating a report of the included errors in a reporting format accepted by at least one of the first and second credit agency.