Abstract: Methods and systems for presenting time series for analysis. A method includes presenting a first visualization of summary information for an initial data set of a plurality of batches, presenting a filtered data set of the initial data set having a first batch identifier associated with a first batch and the second batch identifier associated with a second batch, executing a time series connector including transmitting a request to a time series application, the request comprising the first batch identifier, the second batch identifier, and the time series configuration data. The method further includes causing presentation of a user interface comprising a chart including a first plot for first time series data for the first batch identifier and a second plot for second time series data for the second batch identifier, the chart configured to the time series configuration data, and the first plot is aligned to the second plot.

Abstract: Methods and systems for presenting time series for analysis. A method includes presenting a first visualization of summary information for an initial data set of a plurality of batches, presenting a filtered data set of the initial data set having a first batch identifier associated with a first batch and the second batch identifier associated with a second batch, executing a time series connector including transmitting a request to a time series application, the request comprising the first batch identifier, the second batch identifier, and the time series configuration data. The method further includes causing presentation of a user interface comprising a chart including a first plot for first time series data for the first batch identifier and a second plot for second time series data for the second batch identifier, the chart configured to the time series configuration data, and the first plot is aligned to the second plot.

Abstract: Methods and systems for presenting time series for analysis. A method includes presenting a first visualization of summary information for an initial data set of a plurality of batches, presenting a filtered data set of the initial data set having a first batch identifier associated with a first batch and the second batch identifier associated with a second batch, executing a time series connector including transmitting a request to a time series application, the request comprising the first batch identifier, the second batch identifier, and the time series configuration data. The method further includes causing presentation of a user interface comprising a chart including a first plot for first time series data for the first batch identifier and a second plot for second time series data for the second batch identifier, the chart configured to the time series configuration data, and the first plot is aligned to the second plot.

Abstract: Systems and methods are disclosed herein for reducing a risk of associating with a client that may engage in illegal activity. A system accesses data associated with an entity for a given context, applies a plurality of AI models to the data based on the context to generate a plurality of AI assessments. Data for showing risk factors, assessments of the risk factors, and data for evaluating risk factors can be transmitted for rendering in a user interface in a display device. Analyst feedback can be received and used to update the AI models.

Abstract: Systems and methods are disclosed herein for reducing a risk of associating with a client that may engage in illegal activity. A system accesses data associated with an entity for a given context, applies a plurality of AI models to the data based on the context to generate a plurality of AI assessments. Data for showing risk factors, assessments of the risk factors, and data for evaluating risk factors can be transmitted for rendering in a user interface in a display device. Analyst feedback can be received and used to update the AI models.

Abstract: Methods and systems for presenting time series for analysis. A method includes presenting a first visualization of summary information for an initial data set of a plurality of batches, presenting a filtered data set of the initial data set having a first batch identifier associated with a first batch and the second batch identifier associated with a second batch, executing a time series connector including transmitting a request to a time series application, the request comprising the first batch identifier, the second batch identifier, and the time series configuration data. The method further includes causing presentation of a user interface comprising a chart including a first plot for first time series data for the first batch identifier and a second plot for second time series data for the second batch identifier, the chart configured to the time series configuration data, and the first plot is aligned to the second plot.

Abstract: Methods and systems for presenting time series for analysis. A method includes presenting a first visualization of summary information for an initial data set of a plurality of batches, presenting a filtered data set of the initial data set having a first batch identifier associated with a first batch and the second batch identifier associated with a second batch, executing a time series connector including transmitting a request to a time series application, the request comprising the first batch identifier, the second batch identifier, and the time series configuration data. The method further includes causing presentation of a user interface comprising a chart including a first plot for first time series data for the first batch identifier and a second plot for second time series data for the second batch identifier, the chart configured to the time series configuration data, and the first plot is aligned to the second plot.

Abstract: Computer-implemented systems and methods are disclosed for automatically aggregating, analyzing, and presenting probabilities associated with data items. Data items may be associated with probabilities or risks, and the data items may have various characteristics. A grouping of data items may be determined based on these characteristics, and probabilities within groups of data items may be aggregated and analyzed. Aggregated probabilities may be used to determine incremental probabilities for individual data items, to assess cumulative risk associated with a group of data items, and to analyze probabilities associated with a particular data item group. User interfaces may be generated to facilitate selection and grouping of data items, selection of risk models, and analysis of aggregate probabilities.

Abstract: Computer-implemented systems and methods are disclosed for automatically aggregating, analyzing, and presenting probabilities associated with data items. Data items may be associated with probabilities or risks, and the data items may have various characteristics. A grouping of data items may be determined based on these characteristics, and probabilities within groups of data items may be aggregated and analyzed. Aggregated probabilities may be used to determine incremental probabilities for individual data items, to assess cumulative risk associated with a group of data items, and to analyze probabilities associated with a particular data item group. User interfaces may be generated to facilitate selection and grouping of data items, selection of risk models, and analysis of aggregate probabilities.

Abstract: Computer-implemented systems and methods are disclosed for automatically aggregating, analyzing, and presenting probabilities associated with data items. Data items may be associated with probabilities or risks, and the data items may have various characteristics. A grouping of data items may be determined based on these characteristics, and probabilities within groups of data items may be aggregated and analyzed. Aggregated probabilities may be used to determine incremental probabilities for individual data items, to assess cumulative risk associated with a group of data items, and to analyze probabilities associated with a particular data item group. User interfaces may be generated to facilitate selection and grouping of data items, selection of risk models, and analysis of aggregate probabilities.