Analysis of clustering algorithms for credit risk evaluation using multiple correspondence analysis

Jadwal, Pankaj Kumar; Pathak, Sunil; Jain, Sonal

doi:10.1007/s00542-022-05310-y

Cited by 5 publications

(2 citation statements)

References 31 publications

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“…The clustering is performed by a GA based on k-means clustering. Jadwal et al (2022) use MCA as feature preprocessing and segment the customers of a bank use case with an segmentation approach based on k-means and hierarchical clustering.…”

Section: Tablementioning

confidence: 99%

A review on customer segmentation methods for personalized customer targeting in e-commerce use cases

Gomes

Meisen

2023

Inf Syst E-Bus Manage

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The importance of customer-oriented marketing has increased for companies in recent decades. With the advent of one-customer strategies, especially in e-commerce, traditional mass marketing in this area is becoming increasingly obsolete as customer-specific targeting becomes realizable. Such a strategy makes it essential to develop an underlying understanding of the interests and motivations of the individual customer. One method frequently used for this purpose is segmentation, which has evolved steadily in recent years. The aim of this paper is to provide a structured overview of the different segmentation methods and their current state of the art. For this purpose, we conducted an extensive literature search in which 105 publications between the years 2000 and 2022 were identified that deal with the analysis of customer behavior using segmentation methods. Based on this paper corpus, we provide a comprehensive review of the used methods. In addition, we examine the applied methods for temporal trends and for their applicability to different data set dimensionalities. Based on this paper corpus, we identified a four-phase process consisting of information (data) collection, customer representation, customer analysis via segmentation and customer targeting. With respect to customer representation and customer analysis by segmentation, we provide a comprehensive overview of the methods used in these process steps. We also take a look at temporal trends and the applicability to different dataset dimensionalities. In summary, customer representation is mainly solved by manual feature selection or RFM analysis. The most commonly used segmentation method is k-means, regardless of the use case and the amount of data. It is interesting to note that it has been widely used in recent years.

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Section: Tablementioning

confidence: 99%

A review on customer segmentation methods for personalized customer targeting in e-commerce use cases

Gomes

Meisen

2023

Inf Syst E-Bus Manage

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“…To achieve our goal, we will also apply correspondence analysis, which will allow us to graphically change our outputs into a more legible and understandable format. D'Ambra et al ( 2022), Jadwal et al (2022), Turmaine et al (2022), Hsu et al (2022), andChampahom et al (2022) employed this analysis to compare and research numerous facts that occurred in the world. We were interested in the results of our study, so we decided to use correspondence analysis to make a graph of them.…”

Section: Handling Company 25mentioning

confidence: 99%

CEO monitoring and accounting record manipulation: Evidence from Slovak agriculture companies

Klieštik¹,

Blazek²,

Belás³

2022

Economics &Amp; Sociology

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Many authors focus on detecting accounting record manipulation using various models and investigating the reasons of accounting falsification and alteration. In general, the tax base is changed because its optimization benefits the business. Various research studies show that the CEO is the one who commences the process of updating accounting data. As a result, we'd like to show the gender of persons that initiate manipulation the most frequently. By recognizing inventive accounting, Beneish's methodology is utilized to identify organizations that have cheated. As a result, organizations are categorized as having a female, male, or mixed management team. Based on the Beneish model, statistical approaches (such as contingency tables and establishing the link between variables), and correspondence analysis, we established that gender influences how a company's accounting is managed: if a woman is a director, the company is regarded non-manipulative. In contrast, if a male keeps control of the corporation, the company has a strong incentive to falsify its financial reports.

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Credit Risk Assessment System Based on Deep Learning: A Systematic Literature Review

Hoyos Gutiérrez,

Santos López

2024

Lecture Notes in Networks and Systems

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Analysis of clustering algorithms for credit risk evaluation using multiple correspondence analysis

Cited by 5 publications

References 31 publications

A review on customer segmentation methods for personalized customer targeting in e-commerce use cases

A review on customer segmentation methods for personalized customer targeting in e-commerce use cases

CEO monitoring and accounting record manipulation: Evidence from Slovak agriculture companies

Credit Risk Assessment System Based on Deep Learning: A Systematic Literature Review

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