Consideration of the possibilities of applying machine learning methods for data analysis when promoting services to bank's clients
Year of publication: |
2022
|
---|---|
Authors: | Bulhakova, Olha ; Ulianovska, Yuliia ; Kostenko, Victoria ; Rudyanova, Tatyana |
Published in: |
Technology audit and production reserves. - Kharkiv : SPC PC Technology center, ISSN 2706-5448, ZDB-ID 2943943-7. - Vol. 4.2022, 2/66, p. 14-18
|
Subject: | artificial intelligence | machine learning methods | banking services | credit scoring | credit risk | Künstliche Intelligenz | Artificial intelligence | Kreditwürdigkeit | Credit rating | Kreditrisiko | Credit risk | Bankgeschäft | Banking services |
Type of publication: | Article |
---|---|
Type of publication (narrower categories): | Aufsatz in Zeitschrift ; Article in journal |
Language: | English |
Other identifiers: | 10.15587/2706-5448.2022.262562 [DOI] hdl:11159/12779 [Handle] |
Source: | ECONIS - Online Catalogue of the ZBW |
-
A survey of machine learning in credit risk
Breeden, Joseph L., (2021)
-
Machine learning in credit risk : measuring the dilemma between prediction and supervisory cost
Alonso, Andrés, (2020)
-
Is algorithmic credit scoring a "high risk"?
Milkau, Udo, (2023)
- More ...
-
Study of the process of identifying the authorship of texts written in natural language
Ulianovska, Yuliia, (2024)
-
Analysis of approaches for identification the ontological model components of the searching system
Kostenko, Victoria, (2021)
-
Rudyanova, Tatyana, (2021)
- More ...