TY - JOUR
T1 - Lending Business Models and FinTechs Efficiency
AU - Pampurini, Francesca
AU - Annagiulia, Pezzola
AU - Anna Grazia, Quaranta
PY - 2024
Y1 - 2024
N2 - The aim of the study is to analyse which managerial issues can be considered the main efficiency drivers for all Italian FinTechs engaged in lending. We measure their efficiency in the period 2020-2022 via Stochastic Data Envelopment Analysis. The main determinants seem to be ROA and cost-to-income ratio; this means that the ability to control both the business risk level and costs is crucial for FinTechs’ managers and other players interested in M&A deals in this industry. The results are useful for FinTechs, other financial players, regulators and supervisors in defining homogeneous rules in the lending sector.
AB - The aim of the study is to analyse which managerial issues can be considered the main efficiency drivers for all Italian FinTechs engaged in lending. We measure their efficiency in the period 2020-2022 via Stochastic Data Envelopment Analysis. The main determinants seem to be ROA and cost-to-income ratio; this means that the ability to control both the business risk level and costs is crucial for FinTechs’ managers and other players interested in M&A deals in this industry. The results are useful for FinTechs, other financial players, regulators and supervisors in defining homogeneous rules in the lending sector.
KW - Efficiency
KW - FinTech
KW - Lending business models
KW - Stochastic Data Envelopment Analysis
KW - Efficiency
KW - FinTech
KW - Lending business models
KW - Stochastic Data Envelopment Analysis
UR - http://hdl.handle.net/10807/278036
U2 - 10.1016/j.frl.2024.105519
DO - 10.1016/j.frl.2024.105519
M3 - Article
SN - 1544-6123
SP - 1
EP - 8
JO - Finance Research Letters
JF - Finance Research Letters
ER -