A non-parametric-based computationally efficient approach for credit scoring using non-traditional data

Afshin Ashofteh; Jorge Miguel Bravo

A non-parametric-based computationally efficient approach for credit scoring using non-traditional data

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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Original language	English
Title of host publication	8th International Conference on Risk Analysis and Design of Experiments
Subtitle of host publication	book of abstratcts
Editors	Karl Moder, Bernhard Spange
Pages	9
Number of pages	1
Publication status	Published - Nov 2019
Event	8th International Conference on Risk Analysis and Design of Experiments - University of Natural Resources and Life Sciences, Viena, Austria Duration: 23 Apr 2019 → 26 Apr 2019 Conference number: 8

Conference

Conference	8th International Conference on Risk Analysis and Design of Experiments
Country/Territory	Austria
City	Viena
Period	23/04/19 → 26/04/19

Keywords

Credit scoring
Neural network
Non-traditional data sources
Default

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A Non-parametric_based_computationally_efficient_ApproachFinal published version, 4.2 MBLicence: Unspecified

First Prize for the presentation of "A non-parametric-based computationally efficient approach for credit scoring using non-traditional data", at the 8th International Conference on Risk Analysis and Design of Experiments
Ashofteh, Afshin (Recipient), 26 Apr 2019
Prize: Prize (including medals and awards)

Cite this

@inproceedings{8ba26ce3152a428eb08fb9b400ddde94,

title = "A non-parametric-based computationally efficient approach for credit scoring using non-traditional data",

keywords = "Credit scoring, Neural network, Non-traditional data sources, Default",

author = "Afshin Ashofteh and Bravo, {Jorge Miguel}",

note = "Ashofteh, A., & Bravo, J. M. (2019). A non-parametric-based computationally efficient approach for credit scoring using non-traditional data. In K. Moder, & B. Spange (Eds.), 8th International Conference on Risk Analysis and Design of Experiments: book of abstratcts (pp. 9); 8th International Conference on Risk Analysis and Design of Experiments ; Conference date: 23-04-2019 Through 26-04-2019",

year = "2019",

month = nov,

language = "English",

isbn = "976-3-900932-64-0",

pages = "9",

editor = "Karl Moder and Bernhard Spange",

booktitle = "8th International Conference on Risk Analysis and Design of Experiments",

}

A non-parametric-based computationally efficient approach for credit scoring using non-traditional data. / Ashofteh, Afshin ; Bravo, Jorge Miguel.
8th International Conference on Risk Analysis and Design of Experiments: book of abstratcts. ed. / Karl Moder; Bernhard Spange. 2019. p. 9.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - A non-parametric-based computationally efficient approach for credit scoring using non-traditional data

AU - Ashofteh, Afshin

AU - Bravo, Jorge Miguel

N1 - Conference code: 8

PY - 2019/11

Y1 - 2019/11

KW - Credit scoring

KW - Neural network

KW - Non-traditional data sources

KW - Default

M3 - Conference contribution

SN - 976-3-900932-64-0

SP - 9

BT - 8th International Conference on Risk Analysis and Design of Experiments

A2 - Moder, Karl

A2 - Spange, Bernhard

T2 - 8th International Conference on Risk Analysis and Design of Experiments

Y2 - 23 April 2019 through 26 April 2019

ER -

A non-parametric-based computationally efficient approach for credit scoring using non-traditional data

Conference

Keywords

Access to Document

Prizes

First Prize for the presentation of "A non-parametric-based computationally efficient approach for credit scoring using non-traditional data", at the 8th International Conference on Risk Analysis and Design of Experiments

Cite this