Name: BNPL and Machine Learning: Decisions That Scale
Start: 2025-10-10T17:30:00+02:00
End: 2025-10-10T19:30:00+02:00

In this presentation, we’ll explore how machine learning models are transforming decision-making in the BNPL (Buy Now, Pay Later) landscape. Focusing on credit scoring, we’ll discuss the unique challenges of this audience—such as lack of credit history, short-term behavior, and high volatility—and how predictive techniques can deliver fast, scalable, and accurate responses.
The talk will cover everything from feature engineering to performance evaluation in dynamic environments, while also addressing ethical considerations and financial inclusion. By the end, participants will gain a clear understanding of how data and algorithms can drive smarter, safer decisions in instant credit.

Federica Gazzelloni

R-Ladies Rome

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Kelly holds a Bachelor's degree in Mathematics from Universidade Estadual Paulista (UNESP), a Master's and PhD in Applied Mathematics from Universidade Estadual de Campinas (UNICAMP), and a postgraduate specialization in Artificial Intelligence from PUC. She has taught engineering courses at FAM (Faculdades de Americana) and FAJ (Faculdades de Jaguariúna), and contributed as a researcher at renowned institutions such as Embrapa-CNPTIA and the GAIA Group for Innovation and Learning in Organizations.
With extensive experience as a Data Scientist and Data Engineer across multiple banks, Kelly now works at Serasa Experian’s Innovation Labs, where she helps develop Reusable Digital Identities (RDIs). She is an active member of Women Leaders in Fintechs and the Strides Tech Community, and also serves as a mentor for the STEM Women Network.

Kelly Marques

BNPL and Machine Learning: Decisions That Scale

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BNPL and Machine Learning: Decisions That Scale

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