Wells Fargo Bank, N.a.

Bank of America Corporation

Jpmorgan Chase Bank, N.a.

Fernando Cela Diaz

Agus Sudjianto

Harsh Singhal

Ningzhou Zeng

Abhijit Rao

Peter Bordow

William Anthony Nobili

Jie Chen

Sandi Setiawan

Timothy John Breault

Vanio Markov

Kenneth C Wood

Stephen Koch

Bernhard Hientzsch

Zhiqiu Li

Chris Ferraro

Saurabh Shivpuri

Veronica Mejia Bustamante

Ashish Das

Reuben Mathew

Nikhil Mirakhur

Andrea Renee Turner

Bradford Timothy Winkelman

Anupam Sharma

Boyu Wu

Chengchen Qin

Kai Arne Krueger

Karan H Jeswani

Yufeng Ding

Bharat Patel

Harsh Vardhan Tiwari

Ricardo Riguera Arias

Surya Chavali

Ravi K Govindaraju

Ridhi Puppala

A method for valuing one or more cash flow occurrences in an interest rate swap transaction. An example method includes estimating a mean interest rate for each tenor of one or more combinations of two or more tenors of an interest rate swap. The method may include determining a forward interest rate based on the mean interest rate of each tenor of the one or more combinations for the cash flow occurrences. The method may include determining an estimate value, a standard deviation of the estimate value, and a probability or outcome associated with the estimate value. The method may include determining an overall value of the interest rate swap based on one or more determinations of estimate value, standard deviation of the estimate value, and probability or outcome associated with the estimate value.

Systems and methods for valuing an interest rate swap transaction

This disclosure describes techniques that include validation or other assessments of digital systems, such as machine learning models and other statistical models. In one example, this disclosure describes a method that includes receiving, by a validation computing system and from a development system, a request to perform a test on a model configured to execute on the development system; outputting, by the validation computing system to the development system and in response to the request, an instruction; enabling the development system to process the instruction; receiving, by the validation computing system, test response data; evaluating, by the validation system, the test response data.

Model validation as a service

A Foundational Framework ('the Framework') may refer to an apparatus that connects a multiplicity of potentially very complex components, each of which produce different types of information related to financial forecast, while maintaining a distributed and federated model to allow high autonomy to each component. The innovative Framework provides a unified operation of lifecycle of every component and allows the production of unlimited types of forecasts of different dimensions and for different purposes using a common tool that is responsible of coordinating and running the sequence of components for the user's needs.

System and method for implementing a federated forecasting framework

Embodiments of the present invention relate to methods and apparatuses for determining leading indicators and/or for modeling one or more time series. For example, in some embodiments, a method is provided that includes: (a) receiving first data indicating the value of a total income amount for a plurality of consumers over a period of time; (b) receiving second data indicating the value of a total debt amount for a plurality of consumers over a period of time; (c) selecting a consumer leverage time series that compares the total income amount to the total debt amount over a period of time; (d) modeling the consumer leverage time series based at least partially on the first and second data; (e) determining, using a processor, the value of the cycle component for a particular time; and (f) outputting an indication of the value of the cycle component for the particular time.

Determining leading indicators

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Brooklyn, NY, United States of America

Fernando Cela Diaz