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Modeling Customer Behavior of Non-Maturity Deposits
KTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Mathematical Statistics.
2019 (English)Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesisAlternative title
Modellering av kundbeteende för icke tidsbunden inlåning (Swedish)
Abstract [en]

The modeling of non-maturity deposits has become a highly relevant subject in the financial sector since these instruments constitute a significant portion of banks’ funding. A non-maturity deposit may look relatively simple, however, it has features that complicate the handling of these products. This thesis has the purpose of building a model based on the identification, integration and significance level of factors that influence customer behavior related to non-maturity deposits. Moreover, a mathematical approach based on a selection of these factors is made with the aim to analyze client behavior related to these products. The developed model uses simple linear regression and multiple linear regression with dummy variables to model long-term behavior. In contrast to the statistical methods that banks typically apply in this context, this thesis can contribute to the modeling of non-maturity deposits by highlighting customer behavior. Although, the evaluation of the mathematical approach indicates that the model might not be appropriate to use in real practice, it may arise ideas of alternative methods for the handling of non-maturity deposits.

Abstract [sv]

Modellering av icke tidsbunden inlåning har blivit ett väldigt aktuellt ämne i den finansiella sektorn eftersom dessa instrument utgör en betydande del av bankers finansiering. Icke tidsbunden inlåning kan verka simpelt, dock finns det egenskaper hos denna som visat sig komplicera hanteringen av dessa produkter. Syftet med denna avhandling är att bygga en modell baserat på identifikation, integration och signifikansnivå av faktorer som påverkar kundbeteende relaterat till icke tidsbunden inlåning. Därtill, en matematisk modell baserat på ett urval av dessa faktorer är konstruerad med målet att analysera kunders beteende relaterat till dessa produkter. Den utvecklade modellen använder enkel linjär regression och multipel linjär regression med dummy variabler för att modellera långsiktigt beteende. I kontrast till de statistiska metoder som banker oftast tillämpar i detta sammanhang, kan denna studie bidra till modelleringen av icke tidsbunden inlåning genom att belysa kundbeteende. Trots att resultaten indikerar att den matematiska modellen kanske inte är lämplig att använda i praktiken, kan detta ge idéer på alternativa metoder för hanteringen av icke tidsbunden inlåning.

Place, publisher, year, edition, pages
2019.
Series
TRITA-SCI-GRU ; 2019::091
National Category
Probability Theory and Statistics
Identifiers
URN: urn:nbn:se:kth:diva-252567OAI: oai:DiVA.org:kth-252567DiVA, id: diva2:1319672
External cooperation
Handelsbanken
Subject / course
Financial Mathematics
Educational program
Master of Science - Applied and Computational Mathematics
Supervisors
Examiners
Available from: 2019-06-04 Created: 2019-06-03 Last updated: 2019-06-04Bibliographically approved

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CiteExportLink to record
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