Capital One Services, LLC

Ajmal Karuthakantakath

Raman Bajaj

Sanjiv Yajnik

Gurmeet Singh

Nicholas Dolle

Vikramaditya Repaka

Chandra Dhandapani

Fredrick Allen Crable

Devi Kiran Gonuguntla

Palak Mathur

Maz Jawed Baig

Raghuram Madiraju

Trent Jones

Jacques Morel

Jordan Donais

Suresh Navayamkunnil Raghavan

Fred Crable

Disclosed embodiments provide systems and techniques for mass execution of analytical models across multiple dimensions of client, collateral, deal structure, third party, and other data relevant to predicting optimal decisions in real-time. In some embodiments, disclosed systems and techniques increase decisioning speed through the reduction of computational loads on disclosed decisioning systems. Further disclosed systems and techniques may scale-out analytical modeling computations through, among other technological solutions, advanced execution environments that are asynchronous and non-blocking in nature so as to allow the execution of a plurality of analytical models in parallel and optimizing the results.

Automated systems for reducing computational loads in the mass execution of analytical models using scale-out computing

Systems and methods are disclosed herein for improving data migration operations including testing and setup of computing environments. In one example, the method may include receiving data for one or more application programming interfaces (APIs). The method may further include generating one or more tests to test the one or more APIs in a first computing environment, testing the APIs, storing the results in a database, and performing a change data capture operation. The method may further include augmenting the one or more tests with the CDC data to generate an updated test. The method may further include testing, using the updated test, a second set of the one or more APIs and comparing the test results. The method may also include outputting a confidence score indicating a correlation between the first environment and the second environment.

Systems and method for testing computing environments

Aspects described herein may allow for the application of dynamically generating APIs using API generator based on database metadata. An API generator may extract metadata associated with store procedures. The API generator may generate a first layer of API that communicates with an enterprise application via a first data format. The API generator may generate a second layer of the API that communicates with a database via a second data format. The API generator may receive a request to invoke a stored procedure in a first data format. In response to receiving the request, the generated API may generate a converted request in the second data format.

Application programming interface generator using database metadata

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Flower Mound, TX, United States of America

Ajmal Karuthakantakath