Search results for: CREDIT SCORING, RETAIL LOANS, CONSUMER FINANCE, PRICING, SIMULATIONS - Bridge of Knowledge

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Search results for: CREDIT SCORING, RETAIL LOANS, CONSUMER FINANCE, PRICING, SIMULATIONS

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Search results for: CREDIT SCORING, RETAIL LOANS, CONSUMER FINANCE, PRICING, SIMULATIONS

  • Katedra Nauk Społecznych i Filozoficznych

    * społeczne i polityczne otoczenie biznesu * społeczne i polityczne aspekty globalizacji * społeczno-polityczne i prawne aspekty integracji europejskiej * wybrane zagadnienia z historii filozofii i filozofii kultury * public relations i komunikacji społeczna * etyka równoważnego rozwoju * zarządzanie edukacją i problematyką reform bolońskich

  • Katedra Analizy Ekonomicznej i Finansów

    * analizy finansowej przedsiębiorstwa, * prognozowania upadłości przedsiębiorstwa, * bankowości, * zarządzania finansami przedsiębiorstw, * zarządzania finansami publicznymi, * zarządzania finansami gospodarstw domowych, * inwestycji alternatywnych, * funkcjonowania rynków finansowych w tym w warunkach kryzysu.

  • Architektura Systemów Komputerowych

    Główną tematyką badawczą podejmowaną w Katedrze jest rozwój architektury aplikacji i systemów komputerowych, w szczególności aplikacji i systemów równoległych i rozproszonych. "Architecture starts when you carefully put two bricks together" - stwierdza niemiecki architekt Ludwig Mies von der Rohe. W przypadku systemów komputerowych dotyczy to nie cegieł, a modułów sprzętowych lub programowych. Przez architekturę systemu komputerowego...

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Search results for: CREDIT SCORING, RETAIL LOANS, CONSUMER FINANCE, PRICING, SIMULATIONS

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Search results for: CREDIT SCORING, RETAIL LOANS, CONSUMER FINANCE, PRICING, SIMULATIONS

  • A Simulation Model for Risk and Pricing Competition in the Retail Lending Market

    We propose a simulation model of the retail lending market with two types of agents: borrowers searching for low interest rates and lenders competing through risk-based pricing. We show that individual banks observe adverse selection, even if every lender applies the same pricing strategy and a credit scoring model of comparable discrimination power. Additionally, the model justifies the reverse-S shape of the response rate curve....

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  • Economics of credit scoring management

    Publication

    - Year 2019

    Credit scoring models constitute an inevitable element of modern risk and profitability management in retail financial lending institutions. Quality,or separation power of a credit scoring model is usually assessed with the Gini coefficient. Generally, the higher Gini coefficient the better, as in this way a bank can increase number of good customers and/or reject more bad applicants. In...

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  • Which Curve Fits Best: Fitting ROC Curve Models to Empirical Credit-Scoring Data

    Publication

    - Risks - Year 2022

    In the practice of credit-risk management, the models for receiver operating characteristic (ROC) curves are helpful in describing the shape of an ROC curve, estimating the discriminatory power of a scorecard, and generating ROC curves without underlying data. The primary purpose of this study is to review the ROC curve models proposed in the literature, primarily in biostatistics, and to fit them to actual credit-scoring ROC data...

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  • How to model ROC curves - a credit scoring perspective

    Publication

    - Year 2018

    ROC curves, which derive from signal detection theory, are widely used to assess binary classifiers in various domains. The AUROC (area under the ROC curve) ratio or its transformations (the Gini coefficient) belong to the most widely used synthetic measures of the separation power of classification models, such as medical diagnostic tests or credit scoring. Frequently a need arises to model an ROC curve. In the biostatistical...

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  • Bifractal receiver operating characteristic curves: a formula for generating receiver operating characteristic curves in credit-scoring contexts

    This paper formulates a mathematical model for generating receiver operating characteristic (ROC) curves without underlying data. Credit scoring practitioners know that the Gini coefficient usually drops if it is only calculated on cases above the cutoff. This fact is not a mathematical necessity, however, as it is theoretically possible to get an ROC curve that keeps the same Gini coefficient no matter how big a share of lowest...

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