Why Evispot

Over the last several years, machine learning has become an integral part of many organizations’ decision-making processes at various levels. With not enough data scientists to fill the increasing demand for data-driven business processes, Evispot offers our AI platform specialized for the finance industry, which automates several time consuming aspects of a typical data science workflow, including data preparation, data visualization, feature engineering, predictive modeling, model documentation, model explanation and model deployment.

Evispot AI platform is a high-performance computing platform for automatic development and rapid deployment of predictive analytics models. It reads tabular data from plain text sources and it automates data visualization and the construction of predictive models.

Evispot AI platform also includes robust Machine Learning interpretability, which incorporates a number of contemporary approaches to increase the transparency and accountability of complex models by providing model results in a human-readable format.

Evispot AI platform targets the finance industry and is used to solve business problems such as application scoring, portfolio analysis, customer churn, campaign response, fraud detection and anti-money-laundering.

Create business value with the Evispot platform 

Commercial value is generated by the Evispot AI platform in a few ways. The platform empowers data scientists and data analysts to work on projects faster and more efficiently by using automation and computing power to accomplish tasks in just minutes or hours instead of the weeks or months that it can take with traditional methods.

Evispot AI platform makes deploying predictive models easy – typically a difficult step in the data science process. In large organizations, value from predictive modeling is typically realized when a predictive model is moved from a data analyst or data scientist’s development environment into a production deployment setting. In this setting, the model is running on live data and making quick, accurate and automatic decisions that make or save money. 

Moreover, the system was designed with interpretability and transparency in mind. Every prediction made by an Evispot AI model can be explained to business users, so the system is viable for all finance specific regulations.

Key Features

Flexibility of Data and Deployment

Evispot AI platform can be deployed everywhere including our own cloud solution, AWS, Azure, Google Cloud and on-premise on any system.

Automatic feature Engineering

Feature engineering is the secret weapon that advanced data scientists use to extract the most accurate results from algorithms. Evispot AI platform employs a library of algorithms and variable transformations to automatically engineer new, high value variables for a given data set. (See preprocessing for more details.) Included in the interface is an easy-to-read variable importance chart that shows the significance of original and newly engineered variables.

Automatic Model Documentation

To explain models to business users and regulators, data scientists and data engineers must document the data, algorithms, and processes used to create machine learning models. Evispot AI platform provides an editable autoreport (Autodoc) for each experiment, relieving the user from the time-consuming task of documenting and summarizing their workflow used when building machine learning models. The autoreport includes details about the data, why variables were chosen to the model and and metrics and interpretability charts about the chosen model and finally information about the risk converter (see risk converter for more details). With this capability in Evispot AI platform, practitioners can focus more on drawing actionable insights from the models and save weeks or even months in development, validation, and deployment process.

Explainable AI

Evispot AI platform provides a robust interpretability of machine learning models to explain modeling results in a human-readable format. In the ‘Evaluation view’, Evispot AI employs a host of different techniques and methodologies for interpreting and explaining the results of its models. A number of charts are generated automatically including Shapley values, variable importance, Decision Tree Surrogate, Sensitivity analysis and more. (See Evaluation for more information.)

Automatic Reason Codes

In regulated industries such as the finance industry, an explanation is often required for significant decisions relating to customers. Reason codes show the key positive and negative factors in a model’s scoring decision in a simple language.

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Machine learning in credit decisions

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