Abstract: Systems and methods for performing data anomaly detection and/or removal are usable to accurately assess baseline power consumption. According to one embodiment of the invention, a system can be provided. The system can be operable to receive energy consumption data of a location; select, based at least in part on a collection period of the energy consumption data, an algorithm for detecting anomalies in the energy consumption data; perform the algorithm on the energy consumption data to detect the anomalies in the energy consumption data; and determine an energy consumption baseline for the location based at least in part on a result of the algorithm.

Abstract: Systems and methods for performing data anomaly detection and/or removal are usable to accurately assess baseline power consumption. According to one embodiment of the invention, a system can be provided. The system can be operable to receive energy consumption data of a location; select, based at least in part on a collection period of the energy consumption data, an algorithm for detecting anomalies in the energy consumption data; perform the algorithm on the energy consumption data to detect the anomalies in the energy consumption data; and determine an energy consumption baseline for the location based at least in part on a result of the algorithm.

Abstract: A visualization technique for directing the attention of analysts to anomalous values of performance measures associated with a target entity is described. A grid of cells is created where each row represents a particular performance metric, and each column a particular time period. For each cell, an anomaly score is calculated associated with the performance metric and time period corresponding to the row and column of the cell. The anomaly score is based on the value of the performance metric for that particular entity for that time period, as well as context data. The context data is selected to represent the historical values of the performance metric for the target entity or the simultaneous performance of peer entities. The anomaly score is calculated using an exceptional statistical technique, and a display characteristic is associated with the value of the anomaly score based upon the range into which the anomaly score falls.

Abstract: A technique for detecting anomalous values in a small set of financial metrics makes use of context data that is determined based upon the characteristics of the target company being evaluated. Context data is selected to represent the historical values of the financial metric for the target company or the simultaneous performance of peer companies. Using the context data, an anomaly score for the financial metric is calculated representing the degree to which the value of the financial metric is an outlier among the context data. This can be done using an exceptional statistical technique. The anomaly score can be used to evaluate the risks associated with business transactions related to the target company.

Abstract: A method and system for detecting business behavioral patterns related to a business entity is provided. The method comprises determining a model for business behavioral patterns in which the likelihood of a particular business behavioral pattern is associated with the occurrence of a qualitative event and a quantitative metric. The method further comprises extracting a first data set from a first data source and a second data set from a second data source. The first data set represents the occurrence of the qualitative event associated with the business entity. The second data set represents the quantitative metric associated with the business entity. Then a first confidence attribute and a first temporal attribute associated with the qualitative event is determined. Similarly, a second confidence attribute and a second temporal attribute associated with the quantitative metric are determined.

Abstract: Method, system and computer product for analyzing business risk using event information extracted from natural language sources. In this invention, articles each containing qualitative business event information relevant to a target business entity are retrieved. A structured events record of details for the qualitative business event information is extracted from the articles. The structured events record is applied to a business risk model that uses temporal reasoning to map qualitative business event information to business risk. The business risk model determines the business risk of the target business entity based on temporal proximity and order of the qualitative business event information in the structured events record.