International Business Machines Corporation

Matthew Daniel Riemer

Elham Khabiri

Aditya Vempaty

Ashish Jagmohan

Vadim Sheinin

Ta-Hsin Li

Swapna Buccapatnam Tirumala

Richard Baxter Hull

Fenno F Heath, Iii

Flavio D Calmon

Techniques for mapping policy documents to regulatory documents to check for compliance between the policies and documents are provided. In one example, a computer-implemented method determining, by a system operatively coupled to a processor, an information input, a control framework, and a document from a first group consisting of a regulatory document and a policy document, wherein the information input is a corpora from a second group consisting of a domain corpora and a global corpora. The computer-implemented method can also comprise mapping, by the system, the received regulatory document or the received policy document to the control framework using a supervised machine learning technique.

Facilitating mapping of control policies to regulatory documents

A method and system are provided to calculate a future behavioral data and identify a relative causal impact of external factors affecting the data. Behavioral data and data for one or more external factors are harvested for a first time period. New behavioral data is harvested for a second time period. New data for the second time period is harvested. Based on a second training algorithm, a forecast time series value of a future behavioral data for a third time period that is after the second time period is calculated. A relative causal impact between each external factor and the predicted time series value of the behavioral data, for the third time period, is identified.

Time series forecasting to determine relative causal impact

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New York, NY, United States of America

Matthew Daniel Riemer