Artikel

Model of optimizing correspondence risk-return marketing for short-term lending

The modern credit market is actively changing under the influence of digitalization processes. Some of the drivers of these changes are financial companies that carry out, among other things, online lending. Online lending is objectively focused on short-term small loans, both payday loans (PDL) and short-term loans for SMEs. In our research, we applied a special segmentation of borrowers based on the whale-curve approach. Such segmentation leads to four segments of borrowers (A, B, C, and D) which are characterized by the specific features of profitability, risk, recurrent loan granting, and others. The model of optimal correspondence between "risk-return-marketing efforts" is elaborated in the mentioned segments. Marketing efforts are considered in the context of the optimization of the marketing-budget allocation. Our approach was essentially grounded in special scoring-tools that allow multi-layer assessment. A scheme of assessment of profitability, risk, and marketing-resources allocation for borrower's inflow is constructed. The results can be applied to the customer relationship management (CRM) of online non-banking lenders.

Language
Englisch

Bibliographic citation
Journal: Journal of Risk and Financial Management ; ISSN: 1911-8074 ; Volume: 15 ; Year: 2022 ; Issue: 12 ; Pages: 1-13

Classification
Management
Subject
profitability
marketing
customer relationship management
non-banking lending
payday loans
risk estimation
scoring
segmentation

Event
Geistige Schöpfung
(who)
Kaminskyi, Andrii
Nehrey, Maryna
Babenko, Vitalina
Zimon, Grzegorz
Event
Veröffentlichung
(who)
MDPI
(where)
Basel
(when)
2022

DOI
doi:10.3390/jrfm15120583
Handle
Last update
10.03.2025, 11:45 AM CET

Data provider

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ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. If you have any questions about the object, please contact the data provider.

Object type

  • Artikel

Associated

  • Kaminskyi, Andrii
  • Nehrey, Maryna
  • Babenko, Vitalina
  • Zimon, Grzegorz
  • MDPI

Time of origin

  • 2022

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