How IT-Related Financial Innovation Influences Bank Risk-Taking: Results from an Empirical Analysis of Patent Applications

Dietzmann, Christian; Alt, Rainer

doi:10.1109/cbi.2019.00059

Cited by 2 publications

(2 citation statements)

References 41 publications

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“…Kilic, Dolata, and Schwabe (2017) find that client profiling should not necessarily be carried out purely digitally, but that joint profiling is much more accepted by clients. If the intelligent system correctly identifies the customer segment based on the joint profiling, risk-accurate investment solutions can be offered, underlining that intelligent financial innovations are advantageous for both customers and bank risk-taking (Dietzmann & Alt, 2019).…”

Section: Existing Research On Robo-advisorymentioning

confidence: 99%

Implications of AI-based robo-advisory for private banking investment advisory

Dietzmann

Jaeggi

Alt

2023

JEBDE

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PurposeAI-based robo-advisory (RA) represents a FinTech application that is already replacing retail investment advisors. In private banking (PB), clients also increasingly expect service provision across different digital channels, but with a higher degree of personalization. Hence, the present study investigates the impact of intelligent RA on the PB investment advisory process to derive both process (re)design knowledge and strategic guidance for artificial intelligence (AI) usage for PB investment advisory.Design/methodology/approachThe present study applies an AI process impact analysis approach by decomposing AI-based RA into three AI application types: conversational agent, customer segmentation and predictive analytics. The analysis results along a reference PB investment advisory process reveal sub-process transformations which are applied for process redesign integrating AI.FindingsThe study results imply that AI systems (1) enable seamless client journeys, (2) increase advisor flexibility, (3) support the client–advisor relationship by applying an omnichannel approach and (4) demand advisor skills to be augmented with technical and statistical knowledge.Originality/valueThe research study contributes (1) an AI process impact analysis approach, (2) derives process (re)design knowledge for AI deployment and (3) develops strategic guidance for AI usage in PB investment advisory.

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Section: Existing Research On Robo-advisorymentioning

confidence: 99%

Implications of AI-based robo-advisory for private banking investment advisory

Dietzmann

Jaeggi

Alt

2023

JEBDE

Self Cite

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“…They showed that overconfident managers are more likely to take higher credit and (2010) showed that overconfidence brings about more risk tolerance. Dietzmann and Alt (2019) proved that technological innovation for the 100 largest US banks between 2005 and 2015 moderates the risk-bearing for 95% of these banks. This is mainly thanks to novel risk management processes and improved algorithms of risk calculation.…”

Section: Literature Reviewmentioning

confidence: 99%

Microfinance's digital transformation for sustainable inclusion

Fersi,

Boujelbéne,

Arous

2023

EJMBE

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PurposeThe purpose of this paper is to evaluate the performance of Microfinance Institutions (MFIs) offering FinTech services. This study contributes to the existing literature on microfinance digitalization, financial inclusion and sustainable development. The study also takes into consideration a behavioral perspective through the efficiency evaluation process of MFIs offering FinTech services.Design/methodology/approachThe following study employs the Stochastic Frontier Analysis approach to estimate the operational and social efficiency scores of the 387 MFIs over the period 2005–2019. Then, it tries to consider factors influencing MFIs' efficiency and assess their effects. Hence, two separate models for operation and social efficiency introducing a set of factors, including FinTech proxies and overconfidence proxies, are tested. The first model for operational efficiency uses a random-effects estimator while the second one for social efficiency uses a fixed-effects estimator.FindingsThe results show that innovative MFIs have weaker averages of operational efficiency than non-innovative ones but higher averages of social efficiency. This was justified by the fact that innovative MFIs are more socially oriented. Further, findings of this study depict that the proxies of FinTech affect negatively the level of operational efficiency of MFIs. They also depict a negative relationship between FinTech proxies and the level of social efficiency. These results hold through robustness tests.Originality/valueThe highlight of this study is that it takes heed of the indirect effect of technological innovation on the efficiency of MFIs. It has been proved that it moderates the impact of managerial overconfidence (manifested by excessive risk-taking, viz., high levels of PAR30, LGR and NIM) on the level of both operational and social efficiencies.

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How IT-Related Financial Innovation Influences Bank Risk-Taking: Results from an Empirical Analysis of Patent Applications

Cited by 2 publications

References 41 publications

Implications of AI-based robo-advisory for private banking investment advisory

Implications of AI-based robo-advisory for private banking investment advisory

Microfinance's digital transformation for sustainable inclusion

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