Logo do repositório
 
Publicação

FinTech valuation: developing a structured approach to growth estimation and regulatory risk integration in DCF models

authorProfile.emaillennart.erd@gmail.com
datacite.subject.fosCiências Sociais::Economia e Gestão
dc.contributor.advisorHabib, Nadim
dc.contributor.authorErdmann, Lennart
dc.date.accessioned2026-06-08T10:34:37Z
dc.date.available2026-06-08T10:34:37Z
dc.date.issued2025-06-25
dc.date.submitted2025-06-02
dc.description.abstractThis paper proposes an enhanced DCF valuation framework tailored to FinTech firms by addressing two key limitations: unrealistic growth assumptions and the exclusion of regulatory risk. It introduces an empirically fitted S-curve to capture nonlinear growth and a Regulatory Risk Premium (RRP) scorecard to adjust the cost of equity based on jurisdiction-specific regulation. Applied to Klarna, Revolut, and Nexi, the model improves valuation accuracy and realism. Results show that traditional models can significantly misprice FinTechs, especially in early-stage or high-risk regulatory environments. The framework offers a transparent, data-driven approach for valuing innovation-driven financial firms.eng
dc.identifier.tid204131170
dc.identifier.urihttp://hdl.handle.net/10362/203697
dc.language.isoeng
dc.relationUID/ECO/00124/2013
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.subjectValuation
dc.subjectCorporate finance
dc.subjectFintech
dc.subjectRegulation
dc.subjectCEMS MIM
dc.titleFinTech valuation: developing a structured approach to growth estimation and regulatory risk integration in DCF modelseng
dc.typemaster thesis
dspace.entity.typePublication
thesis.degree.nameA Work Project, presented as part of the requirements for the Award of a Master’s degree in Finance from the Nova School of Business and Economics

Ficheiros

Principais
A mostrar 1 - 1 de 1
Miniatura indisponível
Nome:
SPRING25_58193_Jan_Erdmann.pdf
Tamanho:
778.48 KB
Formato:
Adobe Portable Document Format
Licença
A mostrar 1 - 1 de 1
Miniatura indisponível
Nome:
license.txt
Tamanho:
348 B
Formato:
Item-specific license agreed upon to submission
Descrição: