STATISTICA Credit Scoring

STATISTICA Credit Scoring is the solution for any company to build in-house models for its various credit products and decision-making. STATISTICA Credit Scoring covers all aspects of the credit scoring needs for your company and has been proved by the testimonials from current customers.

  • In House Model Building: The STATISTICA Credit Scoring software solution enables the development & evaluation of predictive models to evaluate and assign a risk to applications for credit, either for a request for a new account or for requested changes (e.g., balance increase) to the terms of an existing credit account. 
  • Scoring Applications: STATISTICA Live Score enables companies to score credit applications, easily integrated with your existing customer service systems, self-service Websites for customers, etc.
  • Evaluate Performance: STATISTICA Credit Scoring provides built-in monitoring and evaluation of the ongoing performance of the models to enable the evaluation of outcomes and key metrics and to make decisions about when models may need to be updated.

What makes the STATISTICA Credit Scoring solution unique?:

  • The Approach: STATISTICA Credit Scoring includes both traditional methods for developing credit scoring models (such as Scorecards based on logistic regression) as well as more advanced methods for predictive modeling that often provide better accuracy, which translates into decreased risk, increased approval rates, and increased profits.
  • Real-time Scoring: The STATISTICA Credit Scoring solution includes STATISTICA Live Score, the solution for enabling scoring decisions directly from customer applications via Customer Service Agents, Websites, and other line of business systems.
  • Sources of Data: Unlike generic scorecards, STATISTICA Credit Scoring can be tailored to meet your specific needs.  For example, it provide the flexibility to include various data sources such as behavior scoring, utilizing the transactional record of the account to inform recommendations for credit line increases, incentives, cross-sell or up-sell, or other changes in terms.
  • Flexibility and Capabilities: STATISTICA Credit Scoring is specific to building credit scoring models but the same approaches and techniques can also be applied to modeling customer churn, increasing the ability to detect fraud, response modeling for marketing campaigns, and other applications within your company.


STATISTICA Scorecard Testimonials:

Millennium Bank has used STATISTICA effectively for more than ten years to support their data analysis. They find the program to be comprehensive and user friendly. Based on their experience with STATISTICA, the Credit Risk Department decided to extend their analytic capabilities with scorecard development and maintenance solutions using STATISTICA Scorecard. It is a crucial element in effective credit risk management, which is growing in importance throughout the financial industry. STATISTICA Scorecard is a popular and reliable tool that is well known in the Polish market. We are very pleased that Millennium Bank has joined the group of satisfied STATISTICA Scorecard users.

“We consider STATISTICA Scorecard to be highly useful in everyday development of credit risk models. Millennium Bank counts StatSoft Polska among one of its most reliable business partners.”

Louis Paul
Head of Risk Department
Millennium Bank



“We wish to express our thanks and appreciation for the assistance in employing STATISTICA Scorecard to create and validate scoring models.

“For almost four years, we have been using STATISTICA data analysis software. It is needless to say how user-friendly this environment is to our analysts; nonetheless, implementation of the new STATISTICA Scorecard module helped us to discover new opportunities and dig deeper into the software’s functionalities, not only in developing scoring models, but in other functionalities as well.

“While testing the newest version of STATISTICA Scorecard, StatSoft consultants displayed solid knowledge and deep involvement. Our decision to purchase the software and participate in the ‘Credit Scoring in STATISTICA’ workshop was made with little hesitation. Our use of this software significantly reduced the workload in creating scoring charts and implementing their validation and reporting, and greatly increased the quality of such work.”

“At present, Stefczyk Credit Union is using STATISTICA Scorecard. We can confidently recommend this product to any financial institution (and not only those) that intends to reduce its financial risks and improve its sales process.”

Izabela Rutkowska
Risk Assessment Manager
Stefczyk Credit Union



“We would like to thank StatSoft Polska for their aid in implementing software for creating and validating scoring models (STATISTICA Scorecard).

“We must emphasize the fact that our purchase of the software was preceded by a month-long testing period. That period convinced us of the solution’s quality, which unquestionably includes its functionality and ease of use. The implementation of the Scorecard in a quality tool such as STATISTICA undeniably has proved an added asset to our company.

“The STATISTICA Scorecard software not only helps automate the procedures needed to build a scoring model, but also assists in reporting the entire process, which is of particular importance in any financial institution.

“Based on our experience, we can recommend STATISTICA Scorecard by StatSoft to any company for effective credit risk management.”

SKOK im. M. Kopernika
Risk Management Department
Kopernik Credit Union

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About statsoftsa

StatSoft, Inc. was founded in 1984 and is now one of the largest global providers of analytic software worldwide. StatSoft is also the largest manufacturer of enterprise-wide quality control and improvement software systems in the world, and the only company capable of supporting its QC products worldwide, with wholly owned subsidiaries in all major markets (StatSoft has 23 full-service offices, on all continents), and its software is available in more than 10 languages.

Posted on May 24, 2011, in Credit Scoring and tagged , , , , , , , , , , , , , . Bookmark the permalink. Leave a comment.

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