US 2026/0064522 A1Published application

Machine Learning Based Reconciliation Error Detection And Correction

AssigneeOracle International Corporation

InventorsJohn D. Clark, JR., Pathanjali Malay, Tim Gaumont

Life of this patent

Estimating the term…

Loading patent…

Abstract

Techniques for applying a generative artificial intelligence (AI) model to identify and correct anomalies in remediation records are disclosed. A system trains and applies a generative AI model to displayed datasets to predict remediation record anomalies. If the system detects the generation of a remediation record in a dataset to reconcile the displayed datasets, the system generates a generative AI prompt that includes the remediation record. The generative AI model generates an output that identifies anomalies in the remediation record and the datasets being reconciled. The generative AI model further generates recommendations for remediating errors in the remediation record.

Claims20

Dependent claims

One or more non-transitory computer readable media comprising instructions which, when executed by one or more hardware processors, cause performance of operations comprising:

presenting, in a graphical user interface (GUI) a first set of event records and a second set of event records;
detecting generation of a first remediation record in the second set of event records to reconcile a first discrepancy associated with the first set of event records and the second set of event records;
in response to the generation of the first remediation record, evaluating, in real-time, the first remediation record at least by:
generating a set of prompt content comprising:
the first remediation record;
and
contextual data associated with at least one of the first set of event records and the second set of event records;
and
providing the prompt content to a generative artificial intelligence (AI) model trained to detect anomalies in remediation records;
obtaining, from the generative AI model, a first output identifying a first anomaly associated with the first remediation record;
remediating the first anomaly associated with the first remediation record to generate a second remediation record;
and
modifying the second set of event records to include the second remediation record.

10 more elements

A method comprising:

presenting, in a graphical user interface (GUI) a first set of event records and a second set of event records;
detecting generation of a first remediation record in the second set of event records to reconcile a first discrepancy associated with the first set of event records and the second set of event records;
in response to the generation of the first remediation record, evaluating, in real-time, the first remediation record at least by:
generating a set of prompt content comprising:
the first remediation record;
and
contextual data associated with at least one of the first set of event records and the second set of event records;
and
providing the prompt content to a generative artificial intelligence (AI) model trained to detect anomalies in remediation records;
obtaining, from the generative AI model, a first output identifying a first anomaly associated with the first remediation record;
remediating the first anomaly associated with the first remediation record to generate a second remediation record;
and
modifying the second set of event records to include the second remediation record,
wherein the method is performed by at least one device including a hardware processor.

11 more elements

Dependencies are inferred from the claim text.