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Statements

Subject Item
n2:RIV%2F00216224%3A14310%2F09%3A00036102%21RIV10-MSM-14310___
rdf:type
skos:Concept n16:Vysledek
dcterms:description
For a measurement of partial processes of a financial institution, especially their components like scoring models or other predictive models, it is possible to use quantitative indexes such as Gini index, K-S statistics, Lift and Information statistics. They can be used for comparison of several developed models at the moment of development. It is possible to use them for monitoring of quality of models after the deployment into real business as well. The outcome is then an effective tool to attract new creditworthy customers, and at the same time, control losses. This paper deals with definition of good/bad client, which is crucial for further computations. The main part is devoted to quality indexes based on distribution functions and on density functions. It brings some interesting results connected to Lift in general and for normally distributed data. An application on real data is included too. For a measurement of partial processes of a financial institution, especially their components like scoring models or other predictive models, it is possible to use quantitative indexes such as Gini index, K-S statistics, Lift and Information statistics. They can be used for comparison of several developed models at the moment of development. It is possible to use them for monitoring of quality of models after the deployment into real business as well. The outcome is then an effective tool to attract new creditworthy customers, and at the same time, control losses. This paper deals with definition of good/bad client, which is crucial for further computations. The main part is devoted to quality indexes based on distribution functions and on density functions. It brings some interesting results connected to Lift in general and for normally distributed data. An application on real data is included too.
dcterms:title
Quality indexes of predictive models in risk and portfolio management Quality indexes of predictive models in risk and portfolio management
skos:prefLabel
Quality indexes of predictive models in risk and portfolio management Quality indexes of predictive models in risk and portfolio management
skos:notation
RIV/00216224:14310/09:00036102!RIV10-MSM-14310___
n3:aktivita
n13:S
n3:aktivity
S
n3:dodaniDat
n6:2010
n3:domaciTvurceVysledku
n4:4304373 n4:8918457
n3:druhVysledku
n18:D
n3:duvernostUdaju
n8:S
n3:entitaPredkladatele
n9:predkladatel
n3:idSjednocenehoVysledku
337796
n3:idVysledku
RIV/00216224:14310/09:00036102
n3:jazykVysledku
n17:eng
n3:klicovaSlova
Portfolio management; predictive modelling; credit scoring; quality indexes.
n3:klicoveSlovo
n11:Portfolio%20management n11:credit%20scoring n11:predictive%20modelling n11:quality%20indexes.
n3:kontrolniKodProRIV
[0281A5E8E8FD]
n3:mistoKonaniAkce
Ioannina, Greece
n3:mistoVydani
Ioannina, Greece
n3:nazevZdroje
IMAEF 2009 Proceedings
n3:obor
n14:BB
n3:pocetDomacichTvurcuVysledku
2
n3:pocetTvurcuVysledku
2
n3:rokUplatneniVysledku
n6:2009
n3:tvurceVysledku
Řezáč, Martin Řezáč, František
n3:typAkce
n12:WRD
n3:zahajeniAkce
2009-06-11+02:00
s:issn
1791-9800
s:numberOfPages
12
n10:hasPublisher
Department of Economics, University of Ioannina
n19:isbn
978-960-233-196-5
n20:organizacniJednotka
14310