Accenture Global Solutions Limited

Arati Deo

Kishore P Durg

Bhaskar Ghosh

Mahesh Venkataraman

Mallika Fernandes

Gopali Raval Contractor

Subhashini Lakshminarayanan

Parag Rane

Maria Lopes

Prasanna S R

Teresa Escrig

Azimullah Shahzad

Vallinath Sriramula

A device may receive transaction data associated with transactions. The transaction data may be associated with transaction entries that are associated with the transactions. The device may process, using a matching model, the transaction entries to classify the transaction entries into a set of matched transaction entries and a set of unmatched transaction entries. The device may update a transaction grouping model based on the set of matched transaction entries to create an updated transaction grouping model. The device may determine, using the updated transaction grouping model, that a subset of the set of unmatched transaction entries are associated with a same transaction. The device may classify the subset of the set of unmatched transaction entries as grouped transaction entries. The device may provide an indication that the grouped transaction entries and the set of matched transaction entries are reconciled transactions.

Machine learning system for transaction reconciliation

A device identifies training data and scoring data for a model, and removes bias from the training data to generate unbiased training data. The device trains the model with the unbiased training data to generate trained models, and processes the trained models, with the scoring data, to generate scores for the trained models. The device selects a trained model, from the trained models, based on model metrics and the scores, and processes a training sample, with the trained model, to generate first results, wherein the training sample is created based on the unbiased training data and production data. The device processes a production sample, with the trained model, to generate second results, wherein the production sample is created based on the production data and the training sample. The device provides the trained model for use in a production environment based on the first results and the second results.

Training, validating, and monitoring artificial intelligence and machine learning models

Growing community of inventors

Bengaluru, India

Arati Deo