Bank of America Corporation

Bibhudatta Jena

David Joa

Naveen Gururaja Yeri

Timothy J Bendel

Thayer S Allison

Yanghong Shao

Deepak Verma

Vikas Mishra

David Neil Joffe

Om Purushotham Akarapu

Jade Michelle Le Vo-Dinh

Srihari Rao Gatpa

Rudraraju Ramakrishnamraju

Arya Kumar Vedabrata

Chandrashekar Katuri

Ragala Manoj Sivaram

Rajashekar Gangaram Basarveni

Kaushik Kumar Akula

Nunna Venkata Sri Satya Mounika

Parul Bajaj

Kunal Makin

Aspects of the disclosure relate to computing hardware and software for dynamic control limit configuration. A computing platform may receive and format historical data. The computing platform may input the formatted data into a control limit prediction model, which may output predicted control limits by weighting, using an ensemble model, outputs from a plurality of other models to produce predicted control limits. The computing platform may adjust existing control limits based on predicted control limits to create actual control limits. The computing platform may receive real time data, and may identify, using the actual control limits and the real time data, a deviation score for the real time data. The computing platform may compare the deviation score to the actual control limits. Based on detecting that the deviation score breaches the actual control limits, the computing platform may send an indication of the breach.

Dynamically providing real-time configuration of data research control limits

Systems and methods for monitoring trigger data quality are provided herein. The systems and methods detect and report whether the current trigger counts are normal or flawed in real time. The systems and methods monitor the triggers to determine the accuracy, completeness, domain of values, and format of the trigger data. In the system and methods, account data associated with the one or more accounts is received and stored in a storage device; the account data is segregated into one or more periods of time; triggers associated with the one or more periods of time are identified based on transactions that occur during the one or more periods of time; a total transaction count for each of the triggers is calculated; and control limits are determined based on the transaction count for each of the triggers.

Trigger data quality monitor

Systems and methods for producing and maintaining account related triggers are provided herein. The systems and methods may be utilized for risk mitigation. Account triggers may be executed to determine account activity indicative of a risk event. Once a risk event is identified, the financial institution may determine an appropriate action to mitigate foreseeable risk due to the risk event.

Financial account related trigger feature for risk mitigation

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Hyderabad Telangana, India

Bibhudatta Jena