Patents by Inventor Vikramaditya Repaka
Vikramaditya Repaka has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).
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Patent number: 11935002Abstract: The system and methods described herein allow users to apply for a purchase of a good from multiple providers using provider specific methodologies for generating offers for the product. For example, the system described herein may include a multi-layer architecture that includes interactive micro-services that communicate together in a bi-directional manner to create a normalized process for the purchase of a good, such as commercial goods/products (e.g. a vehicle) or real property. The micro-services may assess prequalification for a loan or financing for a good, followed by determining eligibility of the good for financing, and further followed by calculating pricing details for loans (e.g. for financing purchase of the good) that would be offered for a consumer's particular financial credentials, for each of a plurality of lenders. Prequalification and pricing may be performed on a good by good basis, or for a plurality of goods near or substantially simultaneously.Type: GrantFiled: May 22, 2020Date of Patent: March 19, 2024Assignee: Capital One Services, LLCInventors: Dinesh Sundaram, Rajaboopathy Vijayaraghavan, Sanjiv Yajnik, Raman Bajaj, Jacques Morel, Trent Jones, Thomas Sickert, Jacob Creech, Alan Ilango, Alex Baird, Vikramaditya Repaka, Hala Salim El-Ali
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Publication number: 20230359986Abstract: 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.Type: ApplicationFiled: May 12, 2023Publication date: November 9, 2023Applicant: Capital One Services, LLCInventors: Chandra DHANDAPANI, Raman BAJAJ, Gurmeet SINGH, Ajmal KARUTHAKANTAKATH, Frederick CRABLE, Nicholas DOLLE, Vikramaditya REPAKA, Sanjiv YAJNIK
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Patent number: 11694156Abstract: 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.Type: GrantFiled: December 28, 2020Date of Patent: July 4, 2023Assignee: Capital One Services, LLCInventors: Chandra Dhandapani, Raman Bajaj, Gurmeet Singh, Ajmal Karuthakantakath, Fredrick Crable, Nicholas Dolle, Vikramaditya Repaka, Sanjiv Yajnik
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Publication number: 20210192437Abstract: 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.Type: ApplicationFiled: December 28, 2020Publication date: June 24, 2021Applicant: Capital One Services, LLCInventors: Chandra Dhandapani, Raman Bajaj, Gurmeet Singh, Ajmal Karuthakantakath, Fredrick Crable, Nicholas Dolle, Vikramaditya Repaka, Sanjiv Yajnik
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Publication number: 20210073683Abstract: Systems, methods, and computer readable media are disclosed for generating, modifying, and using machine learning models to predict and evaluate differences between groups. Methods disclosed herein may include identifying variables that characterize members of a first group, generating shift indicators using the identified variables, generating a machine learning model using the shift indicators and the first group, using the machine learning model and the group to predict shifts between the first group and a predicted second group, determining an aggregate population shift and an aggregate performance shift between the first group and an actual second group, and identifying an impact of one or more of the shift indicators on the aggregate population shift or performance shift. Systems and methods disclosed herein may be configured to receive requests to predict and evaluate differences between group, and to return such predictions and evaluations to one or more users.Type: ApplicationFiled: November 16, 2020Publication date: March 11, 2021Applicant: Capital One Services, LLCInventors: Ruoyu Shao, Fenglin Yan, Vikramaditya Repaka
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Patent number: 10878375Abstract: 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.Type: GrantFiled: November 15, 2018Date of Patent: December 29, 2020Assignee: CAPITAL ONE SERVICES, LLCInventors: Chandra Dhandapani, Raman Bajaj, Gurmeet Singh, Ajmal Karuthakantakath, Fredrick Crable, Nicholas Dolle, Vikramaditya Repaka, Sanjiv Yajnik
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Publication number: 20200372519Abstract: The system described herein provides a secure unified system for users to get prequalified for a loan based on a link provided by a seller. The link may include seller identification information. A user can use a user device to launch a website by actuating a link. The user device may receive input corresponding to the user's personal information on the website. The user may transmit a prequalification request using the website, to a central system. The central system may generate prequalification results. The central system may ensure the pricing structures generated for a given product are consistent with the generated prequalification results within a specified time period.Type: ApplicationFiled: May 22, 2020Publication date: November 26, 2020Applicant: Capital One Services, LLCInventors: Vikramaditya REPAKA, David GILLAM, Shiv SOMASHEKHAR, Russel COVEY, Gurucharan Manadavadi PRAKASH, Jameskutty MONY, Satish KESIBOYANA, Nag Prajval Bindumalyam CHANDRASHEKAR, Gerardo FANG
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Publication number: 20200372499Abstract: The system and methods described herein allow users to apply for a purchase of a good from multiple providers using provider specific methodologies for generating offers for the product. For example, the system described herein may include a multi-layer architecture that includes interactive micro-services that communicate together in a bi-directional manner to create a normalized process for the purchase of a good, such as commercial goods/products (e.g. a vehicle) or real property. The micro-services may assess prequalification for a loan or financing for a good, followed by determining eligibility of the good for financing, and further followed by calculating pricing details for loans (e.g. for financing purchase of the good) that would be offered for a consumer's particular financial credentials, for each of a plurality of lenders. Prequalification and pricing may be performed on a good by good basis, or for a plurality of goods near or substantially simultaneously.Type: ApplicationFiled: May 22, 2020Publication date: November 26, 2020Applicant: Capital One Services, LLCInventors: Dinesh Sundaram, Rajaboopathy Vijayaraghavan, Sanjiv Yajnik, Raman Bajaj, Jacques Morel, Trent Jones, Thomas Sickert, Jacob Creech, Alan Ilango, Alex Baird, Vikramaditya Repaka, Hala Salim El-Ali
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Patent number: 10839318Abstract: Systems, methods, and computer readable media are disclosed for generating, modifying, and using machine learning models to predict and evaluate differences between groups. Methods disclosed herein may include identifying variables that characterize members of a first group, generating shift indicators using the identified variables, generating a machine learning model using the shift indicators and the first group, using the machine learning model and the group to predict shifts between the first group and a predicted second group, determining an aggregate population shift and an aggregate performance shift between the first group and an actual second group, and identifying an impact of one or more of the shift indicators on the aggregate population shift or performance shift. Systems and methods disclosed herein may be configured to receive requests to predict and evaluate differences between group, and to return such predictions and evaluations to one or more users.Type: GrantFiled: December 12, 2018Date of Patent: November 17, 2020Assignee: Capital One Services, LLCInventors: Ruoyu Shao, Fenglin Yan, Vikramaditya Repaka
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Publication number: 20200233932Abstract: Various embodiments are generally directed to a simulation platform. The simulation platform may capture, audit, and/or store production data associated with a current production system. A virtual replica or copy of the of the current production system may be generated based on the production data. The simulation platform may receive one or more proposed modifications or changes to the current production system. Based on the proposal, a modified production system may be generated. Parallel simulations may be run on the virtual replica of the current production system and the modified production system, where analysis is performed on the simulations (and their respective outputs) and a result of the analysis is output to a user.Type: ApplicationFiled: January 23, 2019Publication date: July 23, 2020Applicant: Capital One Services, LLCInventors: Vikramaditya REPAKA, Andrew BALDWIN, Renu RAI, Mohammed ISHAQ
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Publication number: 20200193321Abstract: Systems, methods, and computer readable media are disclosed for generating, modifying, and using machine learning models to predict and evaluate differences between groups. Methods disclosed herein may include identifying variables that characterize members of a first group, generating shift indicators using the identified variables, generating a machine learning model using the shift indicators and the first group, using the machine learning model and the group to predict shifts between the first group and a predicted second group, determining an aggregate population shift and an aggregate performance shift between the first group and an actual second group, and identifying an impact of one or more of the shift indicators on the aggregate population shift or performance shift. Systems and methods disclosed herein may be configured to receive requests to predict and evaluate differences between group, and to return such predictions and evaluations to one or more users.Type: ApplicationFiled: December 12, 2018Publication date: June 18, 2020Applicant: Capital One Services, LLCInventors: Ruoyu SHAO, Fenglin YAN, Vikramaditya REPAKA
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Publication number: 20190087773Abstract: 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.Type: ApplicationFiled: November 15, 2018Publication date: March 21, 2019Applicant: Capital One Services, LLCInventors: Chandra Dhandapani, Raman Bajaj, Gurmeet Singh, Ajmal Karuthakantakath, Fredrick Crable, Nicholas Dolle, Vikramaditya Repaka, Sanjiv Yajnik
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Patent number: 10163072Abstract: 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.Type: GrantFiled: April 17, 2018Date of Patent: December 25, 2018Assignee: CAPITAL ONE SERVICES, LLCInventors: Chandra Dhandapani, Raman Bajaj, Gurmeet Singh, Ajmal Karuthakantakath, Fredrick Crable, Nicholas Dolle, Vikramaditya Repaka, Sanjiv Yajnik
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Publication number: 20180232691Abstract: 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.Type: ApplicationFiled: April 17, 2018Publication date: August 16, 2018Inventors: Chandra Dhandapani, Raman Bajaj, Gurmeet Singh, Ajmal Karuthakantakath, Fredrick Crable, Nicholas Dolle, Vikramaditya Repaka, Sanjiv Yajnik
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Patent number: 9978038Abstract: 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.Type: GrantFiled: September 19, 2017Date of Patent: May 22, 2018Assignee: Capital One Services, LLCInventors: Chandra Dhandapani, Raman Bajaj, Gurmeet Singh, Ajmal Karuthakantakath, Fredrick Crable, Nicholas Dolle, Vikramaditya Repaka, Sanjiv Yajnik
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Patent number: 9965741Abstract: 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.Type: GrantFiled: December 16, 2016Date of Patent: May 8, 2018Assignee: Capital One Services, LLCInventors: Chandra Dhandapani, Raman Bajaj, Gurmeet Singh, Ajmal Karuthakantakath, Fred Crable, Nicholas Dolle, Vikramaditya Repaka, Sanjiv Yajnik
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Publication number: 20180005179Abstract: 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.Type: ApplicationFiled: September 19, 2017Publication date: January 4, 2018Inventors: Chandra Dhandapani, Raman Bajaj, Gurmeet Singh, Ajmal Karuthakantakath, Fred Crable, Nicholas Dolle, Vikramaditya Repaka, Sanjiv Yajnik
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Publication number: 20170178063Abstract: 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.Type: ApplicationFiled: December 16, 2016Publication date: June 22, 2017Inventors: Chandra Dhandapani, Raman Bajaj, Gurmeet Singh, Ajmal Karuthakantakath, Fred Crable, Nicholas Dolle, Vikramaditya Repaka, Sanjiv Yajnik