Credit Scoring Made Simple and Transparent with The New Version of Plug&Score Solutions

Top Quote The updated solutions from Scorto provide simple, effective and transparent way to integrate scoring models into decisioning & risk management processes. End Quote
  • (1888PressRelease) November 20, 2012 - Plug&Score, a business division of Scorto Corporation, is announcing the release of the updated version of the Plug&Score credit scoring and risk management solutions.

    The Plug&Score solutions family consists of scorecard development software Plug&Score Modeler, credit scoring system Plug&Score, and loan origination system Plug&Score Loan Origination.

    «We've been most thorough at analyzing feedback from Plug&Score users. - says Dmitry Krivonosov, Technical Developments Director at Plug&Score's R&D Centre. - Our vision was to go beyond increasing performance speed and adding to scorecard modeling capabilities. We have designed the whole set of new features to provide a simple, robust and efficient way of dealing with data insights. »

    Lenders, especially microfinance organizations, are facing the strong need for a reliable risk evaluation tool. Being intuitive and affordable, Plug&Score solutions allow financial organizations to improve credit portfolio quality and deliver swift and confident service to their customers.

    The updated versions of Plug&Score are already rolled out to the current 250+ users. The updates have been delivered at no cost.

    About Plug&Score
    Plug&Score solutions provide simple, effective and transparent way to integrate scoring models into decisioning & risk management processes. Scorecard development software Plug&Score Modeler, credit scoring system Plug&Score and loan origination system Plug&Score Loan Origination allow users to make informed credit decisions and optimize their risk exposure.

    More features of the updated version of Plug&Score solutions include:

    • New mode is added to the workflow: Raw Data Processing;
    • Data anomalies (missing values, wrong type values, numeric outliers) are detected automatically;
    • Numeric columns with few values (e.g. 1, 2, 3) are automatically transformed to categorical ones;
    • Results of raw data processing are displayed: anomaly values, detected columns, distributions, data statistics;
    • Data analysis options can be defined by user;
    • User can merge several categories to a single one;
    • User can delete certain categories (all rows that contain the deleted category will be excluded);
    • User can rename categories and columns;
    • User can change the type of a column manually (e.g., transform numeric column to categorical one);
    • Dataset can be abridged to a lower amount of rows while keeping data distribution same as in the original dataset;

    Further information is available at http://www.plug-n-score.com/.

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