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Average Ratings 0 Ratings

Total
ease
features
design
support

No User Reviews. Be the first to provide a review:

Write a Review

Description

Introducing an exceptionally user-friendly scoring system specifically designed for small to medium-sized credit institutions, crafted by scoring specialists. This tool delivers precisely what you need for effective real-time scoring, focusing solely on scoring without any outdated, complicated features. It boasts the most favorable cost-to-value ratio available in the industry and can be operational within just a few days. Thanks to its intuitive wizard-based scorecard modeling interface, users find it easy to navigate. You can also monitor and validate scorecards with a selection of pre-defined reports. The system incorporates Reject Inference through both automated and manual methods, alongside automated binning utilizing chi-square techniques and manual binning based on Weight of Evidence (WOE). Additionally, it offers both automatic and manual sampling options, along with graphical statistics to visualize data insights. Users can filter, sort, and reassign portfolio data into “Good” and “Bad” categories, while numeric variables can easily be transformed into categorical forms. Furthermore, it provides correlation coefficients for each variable pair, both before and after the binning process, ensuring comprehensive analysis and understanding of the dataset. With this robust scoring system, credit organizations can enhance their decision-making processes efficiently.

Description

ndCurveMaster, a specialized curve fitting software, is designed to fit curves with multiple variables. It automatically applies nonlinear equations to your datasets. These can be observed or measured values. The software supports curve and surfaces fitting in 2D 3D 4D 5D ..., dimensions. ndCurveMaster is able to handle any data, no matter how complex or how many variables there are. ndCurveMaster, for example, can efficiently derive the optimal equations for a dataset that has six inputs (x1-x6) and a corresponding output Y. For example: Y = a0 - a1 - exp(x1)0.5 + a2 ln(x2)8... + a6 x65.2 to accurately match measured value. ndCurveMaster uses machine learning numerical methods to automatically fit the most suitable nonlinear regression function to your dataset, and discover the relationships between inputs and outputs. This tool supports various curve fitting methods, including linear, polynomial, and nonlinear methods. It also utilizes essential validation and goodness-of-fit tests to ensure accuracy. Additionally, ndCurveMaster provides advanced assessments, such as detecting overfitting and multicollinearity, using tools like the Variance Inflation Factor (VIF) and the Pearson correlation matrix.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

Pascal
Python

Integrations

Pascal
Python

Pricing Details

$9950 one-time payment
Free Trial
Free Version

Pricing Details

€289
Free Trial
Free Version

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Vendor Details

Company Name

Plug&Score

Founded

2005

Country

Netherlands

Website

plug-n-score.com

Vendor Details

Company Name

SigmaLab Tomas Cepowski

Founded

2017

Country

Poland

Website

www.ndcurvemaster.com

Product Features

Statistical Analysis

Analytics
Association Discovery
Compliance Tracking
File Management
File Storage
Forecasting
Multivariate Analysis
Regression Analysis
Statistical Process Control
Statistical Simulation
Survival Analysis
Time Series
Visualization

Product Features

Statistical Analysis

Analytics
Association Discovery
Compliance Tracking
File Management
File Storage
Forecasting
Multivariate Analysis
Regression Analysis
Statistical Process Control
Statistical Simulation
Survival Analysis
Time Series
Visualization

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