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Why Choose Xeno
Xeno is a powerful and user-friendly predictive analytics platform that facilitates the discovery of critical business insights and the development of predictive models and strategies, while addressing the unique operational, regulatory and data requirements of the credit risk and marketing industry. Built for analysts by analysts with 250+ years of accumulated credit scoring experience, Xeno allows users around the globe to readily develop a wide range of predictive models and strategies for credit acquisition risk and marketing, portfolio management, loss forecasting, fraud detection and Basel-driven “internal ratings-based” (IRB) minimum capital calculation. Xeno’s unique analytic methodology, coupled with its innovative optimization technologies, cuts weeks out of the analytic development cycle, while providing greater data insight, better models, ease of use, project collaboration, and more impactful analytics. Request this white paper to learn more about Xeno and how it can benefit your organization.top >>>
Multiple outcome optimization in Xeno: Risk and marketing case studies
Managing retail credit risk and marketing requires decisioning that profitably balances competing consumer behaviors such as revenue and risk, or response and risk. To address these competing objectives, InfoCentricity has pioneered the use of multiple outcome optimization in a single score, which allows an analyst using Xeno to opportunistically improve results on a second objective, while maintaining optimal model performance on a primary objective of interest. Xeno users have utilized this ability to find “free money” in many creative ways, two of which are presented as case studies in this white paper.top >>>
Sophisticated sample bias correction: A Xeno reject inference case study
Data modelers who use observational data, rather than designed data, are frequently hampered in their model development efforts by the sample selection bias injected into their data samples. Acquisition credit risk modelers have been faced with sample bias, introduced by the rejection of non-creditworthy applicants, for decades. Existing custom and credit bureau scores and policies are used to reject non-creditworthy applicants, while uncompetitive pricing policy drives accepted applicants to seek credit elsewhere. The remaining booked applicants reflect a biased observed risk outcome, which is not representative of the credit applicant population as a whole. Xeno’s packaged performance inference module, and the accompanying engineering capabilities, provides the modeler with a sophisticated general purpose sample selection bias correction tool. Learn about Xeno's sample selection bias correction capabilities and the results of applying them in a reject inference case study in this white paper.top >>>