A decision support system to optimize debt collection assignments

Sezi Cevik Onar*, Basar Oztaysi, Cengiz Kahraman, Ersan Öztürk

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2 Atıf (Scopus)

Özet

The technological developments let people use mobile phones and benefit from mobile phones in many areas of their lives. People benefit from various services of the operator companies. Therefore, operator companies have an extensive customer base. Yet, collecting the fees of their services from customers can be hard. When the customers regret or delay the payments the operator companies, which serve to millions of customers, face difficulties in legal procedures. The operator companies usually make agreements with the law firms to convey the lawsuits. In this study, a leading GSM operator company wants to know the possibility of finalizing the cases and take prevention on it, when transferring the case files to the law firms. Naive Bayes classifier, decision tree algorithms, k nearest neighbor method, support vector machines, random forest algorithm, and artificial neural network algorithms are examined, and Naive Bayes classification algorithm is used to define the collection difficulty level for the files.

Orijinal dilİngilizce
Ana bilgisayar yayını başlığıIntelligent and Fuzzy Techniques in Big Data Analytics and Decision Making - Proceedings of the INFUS 2019 Conference
EditörlerCengiz Kahraman, Sezi Cevik Onar, Basar Oztaysi, Irem Ucal Sari, Selcuk Cebi, A.Cagri Tolga
YayınlayanSpringer Verlag
Sayfalar178-187
Sayfa sayısı10
ISBN (Basılı)9783030237554
DOI'lar
Yayın durumuYayınlandı - 2020
EtkinlikInternational Conference on Intelligent and Fuzzy Systems, INFUS 2019 - Istanbul, Turkey
Süre: 23 Tem 201925 Tem 2019

Yayın serisi

AdıAdvances in Intelligent Systems and Computing
Hacim1029
ISSN (Basılı)2194-5357
ISSN (Elektronik)2194-5365

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???event.eventtypes.event.conference???International Conference on Intelligent and Fuzzy Systems, INFUS 2019
Ülke/BölgeTurkey
ŞehirIstanbul
Periyot23/07/1925/07/19

Bibliyografik not

Publisher Copyright:
© 2020, Springer Nature Switzerland AG.

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