Powerful Advanced Features
Minimize or eliminate the need for hard-to-find and keep talent by providing auto features in each step of the Time Series model development cycle. Designed to be used by functional and non-technical users.
Delivers a novel approach to incorporate business insight into decision making during the development cycle.
Transparent Time Series Model Development guide that helps with model risk governance and regulatory compliance.
A Practical, Agile Path to Robust & Efficient Time Series Forecasting
Time Series Models forecast future values based on past values and other exogenous series and are among the traditional novel modeling techniques used in Banking and Finance with a wide range of applications. Few examples of prevalent Time Series Models include segment level credit loss forecasting for any credit portfolio, Property Price Index (PII) Forecasting, Net Operating Income Index Forecasting (NOI), and Operational Loss Forecasting for Comprehensive Capital Review and Analysis (CCAR), Current Expected Credit Loss (CECL), and Business as Usual (BAU) purposes.
STSA platform is designed to guide time series model development. It simplifies and automates many aspects of the complex model development life cycle. It is augmented with functionalities to allow users to integrate needed business inputs and decisions during the development process. The intuitive and feature-rich UI is designed for use by non-technical as well as technical resources. STSA outputs all statistical analysis results and related performance metrics for documentation in support of internal and federal regulatory compliance.
Augmented Machine Learning (ML) Model Development & Enhancement Platform
Machine Learning Application areas are continuously increasing across many industries where accurate data-driven decision support is sustenance and a necessity for achieving or maintaining competitive advantage and growth. These algorithms are able to provide more business insights from the data and are capable of capturing complex signals that cannot be represented by closed functions and hence provide superior accuracy for predictive modeling. MLWay platform is designed to guide ML Model Development and narrows the gap between complex model development and business oversight and review by providing agile and transparent functionality for informed decision making. It enables users to integrate necessary business inputs and decisions during the development process. MLWay outputs all analysis results and related performance metrics for documentation and support of internal and external compliance.
MLWay is an innovative Augmented Machine Learning (ML) Model Development and Enhancement platform for building and developing robust Machine Learning Models. MLWay simplifies and automates many aspects of a complex model development life cycle that require data verification, feature engineering, model design, model technique selection, statistical diagnostics, model fitting and selection, performance evaluation, and implementation while keeping the decision-making control in the hands of the user.
Enables easier and faster exploration and testing of choices and decisions made in all phases of development for outstanding Accuracy, Scalability & Repeatability.
Includes ARIMA and all other top-tier common Time Series Model Techniques: SARIMA, VAR, ECM, and VECM to facilitate comprehensive Statistical analyses.
Eliminates the need for complex coding while providing extensive flexibility in conducting debt analysis, performance evaluation, and candidate model selection. It is estimated to cut Time Series Model Development, Calibration, and Implementation by 10X.