US 2020/0052975 A1 · ADAPTIVE LEARNING SYSTEM WITH A PRODUCT CONFIGURATION ENGINE

Abstract

The adaptive learning systems described herein may include machine-learning engines, product configuration engines, and/or various other components configured to improve the efficiency of processing transactions. The systems described herein may detect and/or predict declined transactions, token deficiencies, insufficient system capacities, and/or other system anomalies. As such, the system may perform operations to generate additional tokens associated with assets, provision various bin ranges, and/or share reserve capacities, and/or other operations. Thus, the system may improve system efficiencies, ensure reliability and operability across the system, and optimize the operations for successfully processing transactions.

Claims20

Dependent claims

A system comprising:

a non-transitory memory;
and
one or more hardware processors coupled to the non-transitory memory and configured to read instructions from the non-transitory memory to cause the system to perform operations comprising:
determining one or more declined transactions in a network;
identifying a plurality of anomalous transactions in the network based at least on the one or more declined transactions;
identifying one or more issuer systems associated with the plurality of anomalous transactions in the network;
modifying product-policy data of a product configuration engine based at least on the one or more identified issuer systems associated with the plurality of anomalous transactions;
and
learning one or more system operations based at least on the one or more identified issuer systems associated with the plurality of anomalous transactions.

6 more elements

A method, comprising:

determining, by one or more hardware processors, one or more declined transactions in a network;
identifying, by the one or more hardware processors, a plurality of anomalous transactions in the network based at least on the one or more declined transactions;
identifying, by the one or more hardware processors, one or more issuer systems associated with the plurality of anomalous transactions in the network;
modifying, by the one or more hardware processors, product-policy data of a product configuration engine based at least on the one or more identified issuer systems associated with the plurality of anomalous transactions;
and
learning, by the one or more hardware processors, one or more system operations based at least on the one or more identified issuer systems associated with the plurality of anomalous transactions.

3 more elements

A non-transitory machine-readable medium having stored thereon machine-readable instructions executable to cause a machine to perform operations comprising:

determining one or more declined transactions in a network;
identifying a plurality of anomalous transactions in the network based at least on the one or more declined transactions;
identifying one or more issuer systems associated with the plurality of anomalous transactions in the network;
modifying product-policy data of a product configuration engine based at least on the one or more identified issuer systems associated with the plurality of anomalous transactions;
and
learning one or more system operations based at least on the one or more identified issuer systems associated with the plurality of anomalous transactions.

3 more elements

Dependencies are inferred from the claim text.

Adaptive learning system with a product configuration engine

Life of this patent

Adaptive learning system with a product configuration engine

Life of this patent

Abstract

Claims20