Wells Fargo Bank, N.a.

Rameshchandra Bhaskar Ketharaju

Ramanathan Ramanathan

Chris Theodore Kalaboukis

Joon Maeng

Abhijit Rao

Andrew J Garner, Iv

Andres J Saenz

Shanmukeswara Rao Donkada

Abhijit Shetti

Naveen Gururaja Yeri

Ashutosh Verma

Saipavan K Cherala

Vamsi Krishna Geda

Ajay Kumar Rentala

Rama Rao Yadlapalli

Sumanth Kumar Charugundla

Nikolai Stroke

Uma Meyyappan

Darius A Miranda

Laura Marie Fontana

Duc M Trinh

Rajiv Ranjan

Todd Biggs

Sudheendranath R Bhatt

Mabel Oza

Ananth Kendapadi

Chandramouli Subramanian

Prasanna Kumar Ammiraju

Joel Eric Boeder

Makarand Shivadevuni

Parul Ghosh

Chandrasekaran Sivaraman

Sitara Kumbale

Sarath Chava

Vinayak Sodar

Manak Suri

Mayuri Chaubey

Yang Yang

Pradeep R Kumar

Vinothkumar Venkataraman

Rahul N Jain

Paul Davis

Matt Hord

Ramya Balasubramanian

Madhu V Vempati

Hemakumar Madabathula

Mohammed Arif

Sajeev Philip

Aditya Kishore Jonnalagadda

Jayasree Iyer

Mathewbabu Edappilly Antony

Ramakrishna Bejjanki

Amit Tripathi

Arun Raj

Shuvam Sengupta

Sai Krishna Madhavi Chitta

Tyler Case

Damaraju P Vittal

Ravi Babu Bandla

Hem Shankar Karlapalem

Daniel S Sumner

Suresh Parpatakam Reddy

Dinakar Channakal Krishnappa

Srinivas Vengala

Sri Rajesh Rayudu

Santosh Nichani

Manish Pandey

Srivathsan Sridharan

Gothandapani Krishnan

Niraj Kumar

Rajesh Padincharekkara Mannachery

Madeshwaran Mohanraj

Jayakrishna Nair

Kalyan Chandra Kothamasu

Parthasarathy Venkatesan

Mushnuri Veera Venkata Kiran Kumar

Sridhara Rao Sidhu

Swati Bose

Arshad A Shaik

Gail Elizabeth Stuart

Dibyendu Chatterjee

Kshitindra Kumar Jain

Ravindar Rao Perala

Poornima Mahabaleshwarappa

Dinesh Sangtani

Mohan Gopal Kanala

Prashanth Kumar Merugu

Naveen Saichand Palle

Vasudev Tumkur Umapathi

Ramesh Chinnasamy

Prabal Nandi

Sathya K Balakrishnan

Madhu Gumballi

Lakshmi Sowrirajan

Dennis Emmanuel Montenegro

Debashis Ghosh

Pankaj Parekh

Himanshu Baral

Suhas Dattatreya Sankolli

Chloe D Cangardel

Systems, apparatuses, methods, and computer program products are disclosed for regulating data communication. An example method includes receiving, by transaction circuitry, a communication request and identifying, by data collection engine and based on the communication request, a set of security parameters. The example method further includes determining, by security analysis engine and based on the set of security parameters, a security score associated with the communication request and in an instance in which the security sore fails to satisfy a security requirement, determining, by the security analysis engine, one or more security actions based on the security score and performing, by the transaction circuitry, the one or more security actions. The example method further includes routing, by data regulation engine and based on a configuration table, a transaction associated with the communication request to a compliant communication channel.

Systems and methods for regulating data communication

The innovation discloses systems, methods and computer program products that reduce complexity and associated measures that are taken to ensure trust in secured transactions as necessitated by requirements present only in an ecommerce environment that do not have a parallel with traditional bricks and mortar commercial transactions. The innovation enables a multitude of mobile wallet applications to engage and obtain services from ecommerce applications wherein backend processing by a mobile wallet server obtains and delivers funds to ecommerce applications without sharing a subset of sensitive data, associated with a mobile wallet application user for the secured transactions. The innovation further provides for a wallet network to be initiated and engaged in which the secured transactions can take place, adopting and adapting social network application connectivity.

Trust-based application to application connectivity

Dynamic allocation of cash. Dispensing of cash by an automatic teller machine (ATM) can be prioritized, e.g., for customers of the financial institution that operate the ATM over non-customers. A request by a customer to hold cash at an automatic teller machine (ATM) for future withdrawal is analyzed using an architecture of artificial intelligence. If the cash hold request is approved, in some examples the requested amount of cash is moved from a first cash rack of the ATM to a second cash rack of the ATM. The requested amount of cash cannot be moved from the second cash rack unless the customer withdraws it from the ATM or unless a time limit for the customer to withdraw the requested amount from the ATM is exceeded.

Dynamic allocation and dispensing of cash

Systems, methods, and computer program products are disclosed for issuing one or more blockchain tokens for property rights. An example method includes receiving an indication of user input including attributes of a property and, and generating a primary blockchain token, where the primary blockchain token includes metadata that correspond to the attributes of the property. The example method further includes broadcasting, over a blockchain network, a transfer of the primary blockchain token to the primary party, and generating one or more secondary blockchain tokens, where each of the one or more secondary blockchain tokens includes respective secondary metadata that correspond to unique subdivided property rights regarding the property, where the secondary metadata include a link to the primary blockchain token. The example method further includes broadcasting, over the blockchain network, transfer of the one or more secondary blockchain tokens to one or more secondary parties.

Systems and methods for issuing blockchain tokens for property rights

A method for preventing the double-spending of digital currency that transfers between multiple distributed ledger technology (DLT) networks. The method includes receiving a message including a smart contract and executing the smart contract. The method further includes detecting a transaction request to transfer the first digital currency from the first DLT network to the second DLT network. The method further includes destroying the digital currency and creating, based on the unit of fiat currency, a second digital currency of a second type on the second DLT network. The method further includes transferring, responsive to detecting the transaction request, the first digital currency from the first DLT network to the second DLT network.

Bank-driven model for preventing double spending of digital currency transferred between multiple DLT networks using a trusted intermediary

Systems, apparatus, and computer program products are disclosed for generating a verification non-fungible token. An example method includes receiving an event generation request and in response to receiving the event generation request, capturing an asset position and a timestamp. The method further includes performing one or more authentication operations on the event generation request based on the asset identifier and the one or more authentication credentials. The method further includes, in an instance in which the one or more authentication operations authenticates the event generation request, generating the verification non-fungible token for the asset identifier and storing the verification non-fungible token in an associated distributed ledger.

Proof of presence using non-fungible tokens

Systems, apparatuses, methods, and computer program products are disclosed for mitigating threats using artificial intelligence. An example method includes: obtaining, via communications hardware of a threat manager, a piece of data; determining, by a threat identification engine of the threat manager, that the piece of data is a threat; and causing, by a remediation engine of the threat manager and in response to the determination, execution of a threat remediation action. The threat remediation action comprises at least one of: publishing an emergency remediation statement addressing the threat, transmitting a takedown request to remove the threat from a threat source, or ignoring the threat.

Systems and methods for threat mitigation using artificial intelligence

Systems, apparatuses, methods, and computer program products are disclosed for dynamically generating a new data rule. An example method includes receiving a data rule including an operation to be applied to a data entry and determining regarding whether the data rule belongs to a set of previously-reviewed data rules. The example method further includes, when the data rule does not belong to the set of previously-reviewed data rules, providing the data rule to a user for human validation and receiving human validation. The example method further includes, causing an update, by rule generation circuitry, of an element of a machine learning model, where the element corresponds to the data rule where the update changes a weight value based on the validation and generating the new data rule based on the updated machine learning model. The example method further includes replacing the data rule with the new data rule.

Systems and methods for dynamically generating new data rules

An example method includes receiving and preprocessing a query request prior to execution of a query. Through preprocessing, a probability that execution of the query would yield a result set similar to at least a portion of results stored in a repeated query result repository is obtained. In response to the probability satisfying a probability threshold, a portion of results is retrieved from the repository. The example method further includes causing transmission of a response to the query request, the response comprising the portion of results.

Systems and methods for reducing computational resource usage in a query-based data access system via a repeated query results repository

Systems, apparatuses, methods, and computer program products are disclosed for managing operation of a distributed system that provides computer-implemented services. An example method includes collecting, via an out-of-band stream, sensor data from a plurality of temperature sensors positioned to infer temperatures of components of a distributed system. The example method further includes inferring, using the inferred temperatures, power consumption rates for performing respective actions with each of the components. The method further includes obtaining an action request and selecting, based on the inferred power consumption rates, a particular component of the components to perform an action to service the action request, the selection being made with a preference to reduce power consumption for performance of the action. The method further includes performing, with the particular component, the action to service the action request, the action resulting in updated computer-implemented services being provided by the distributed system.

Systems and methods for managing power consumption of a distributed system

Embodiments are generally directed to techniques for query-based binarized point decisions, such as with a system that can provide end-to-end decision making support. Some embodiments are particularly directed to a system that makes point decisions, with traceable reasoning, for queries while factoring in a variety of influences. In many embodiments, the traceable reasoning may refer to the generation and collection of metadata associated with various aspects of the decision making process. For example, the metadata may include, or be used to create, a decision lineage and/or reasoning summary that is generated for each point decision. Some embodiments may ensure various influences do not derail the query from the overall objective. In several such embodiments, the point decisioner may confirm or deny that a decision was made with aspect to a certain objective.

Query-based binarized point decisions

A distributed computing system includes a blockchain comprising a plurality of blockchain services comprising an oracle service, a predictive analytics service, a loan service, and a consensus service. The oracle service configured to receive input data comprising at least one of financial data associated with at least one of the plurality of syndicate participants, macroeconomic data, geo-location data, disaster data, or public health data. The predictive analytics service configured to utilize the input data to determine whether a first syndicate participant of the plurality of syndicate participants has an excess of funds and whether a second syndicate participant of the plurality of syndicate participants has a lack of funds where the first syndicate participant is different than the second syndicate participant. The loan service configured to facilitate a loan agreement between the first syndicate participant and the second syndicate participant. The consensus service enabling a consensus process used to agree on a validity of data transactions that are recorded by the blockchain such that the consensus service maintains a replicating ledger within the distributed computing system.

Geolocation-based mesh automatic lending network

A system and methods include a negative certificate authority for distributed management of negative certificates. An authorization restriction is associated with an untrusted user. A negative certificate generated for the untrusted user includes a public key associated with the untrusted user and an authorization restriction. The authorization restriction includes at least one global restriction, which is applicable to each consortium member that subscribes to the negative certificate. The authorization restriction includes at least one local restriction, which allows individual consortium members to further define their own locally applicable restrictions using the negative certificate authority. The negative certificate is accessible to each member of the consortium to enforce the authorization restriction against a transaction request. A secure contributor record including a unique cryptographically generated address is generated for each contributor. In some embodiments, the transaction request is a blockchain-based value exchange transaction, such as a payment transaction using fiat or math-based currency.

Systems and methods for distributed management of negative certificates for blockchain-based value exchange transactions

In one example, a method includes at a first network infrastructure computing device of a plurality of networked infrastructure computing devices receiving, from a user computing device, an authentication token indicating a user using the user computing device is authenticated with respect to an electronic service, based on the user being authenticated, executing a computing task associated with the electronic service for the user computing device, the computing task including computing task data, predicting a set of possible future locations of the user based on an output of a movement prediction model executing on the first network infrastructure computing device, identifying a set of network infrastructure computing devices correlated with the set of possible future locations, and transmitting the authentication token and the computing task data to the set of network infrastructure computing devices.

Computing task transfers between cellular infrastructure devices

An example method includes detecting, by context analysis circuitry, occurrence of a triggering condition. The example method also includes scheduling, by context analysis circuitry and based on the occurrence of the triggering condition, retraining of a model. The example method also includes generating, by data grafting circuitry and in response to scheduling the retraining of the model, a context-relevant training data set based on a target context vector. The example method also includes retraining, by model training circuitry, the model using the context-relevant training data set to mitigate deterioration of performance of the model.

Systems and method for data grafting to enhance model robustness

Growing community of inventors

Hyderabad Telangana, India

Rameshchandra Bhaskar Ketharaju