A practical guide to combining pre-churn scoring with uplift modelling for smarter retention. The post How to Improve Customer Retention in FinTech appeared first on Towards Data Science .
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The article discusses how model validation standards are evolving for large language model (LLM) based systems, particularly in the banking sector. It examines what aspects of traditional validation break down, what elements remain applicable, and how to effectively test the quality of LLM outputs. The piece offers practical insights into adapting validation playbooks for generative AI applications.
arXiv:2607. 10260v1 Announce Type: new Abstract: Customer churn is a major challenge for telecommunication companies, directly eroding revenue and long term customer relationships.
How unit economics should set your classification cutoff, and why they rarely do. The post Your Churn Threshold Is a Pricing Decision appeared first on Towards Data Science .
arXiv:2608.30364v1 Announce Type: new Abstract: Retail banking attrition is usually represented as a terminal binary event, even though client relationships often weaken earlier through partial movem...
The paper audits the IBM Telco Customer Churn benchmark, revealing that common practices inflate performance metrics. It shows that pre‑split SMOTE boosts churn‑class F1 by 13.1 points, that isotonic regression is the best calibration method while temperature scaling fails on tree ensembles, and that the cost‑optimal decision threshold is 5–10 times lower than the F1‑optimal one, saving about $77,000 per 1,000 customers. The authors also test generalisation on Iranian Telecom and Bank churn datasets, and propose a four‑component reporting checklist with reproducible code.
arXiv:2608.20447v1 Announce Type: new Abstract: Feature selection is a highly relevant task in a data-driven knowledge discovery project. Several techniques have been developed aiming at finding the...