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The lending environment has become significantly more risk-sensitive over the past two decades.
Competitors are using new ways to ensure borrowers are a good bet. We want our clients to have the latest
fintech capabilities for their credit score assessments.
That’s why we developed Praexia, a toolkit that allows our decision scientists
to interactively model credit scores and offer companies dealing with financial risk cutting-edge fintech
solutions.
Formerly known as Constrata Core Credit, Praexia is “a cloud-native toolset that provides a complete credit modelling lifecycle for large and small datasets using a suite of graphical tools that empowers decision scientists to leverage the Python ecosystem”.
Employ user-friendly features to build, evaluate, test and deploy credit scorecards using familiar concepts such as logistic regression for binary classification, clustering and information values.
Reduce thousands of potential variables down to a selection that fits our client’s requirements and maximises our predictive power.
Evaluate our model performance and stability using different datasets and out-of-time samples to ensure everything runs as well in production as it does during development.
Praexia gives us a great vantage point to monitor our models with functionality to understand and visualise every application outcome and model decision.
Praexia allows us to improve on all aspects of risk management by providing a single toolkit for data analysis and preparation, modelling, deployment, monitoring and reporting. It allows us to use the latest techniques without sacrificing the transparency, robustness, customisation and efficiency we expect.
We leverage our partnership with Praexia in order to supply our clients with high-performance credit-scoring solutions. The following businesses would benefit from these services:
Praexia’s state-of-the-art tools along with access to alternative datasets
and our innovative use of data, allow for our expert engineering of credit data solutions. Read more in
this Insights article. Alternative datasets from
non-traditional sources can compensate for the shortcomings in traditional credit bureau data. It
identifies payment behaviour trends over different periods.
If you’d like to find out more about Praexia, get in touch to schedule a call.