graduate student
UDC 004.8
The article investigates marketing tools for personalized banking offer delivery based on artificial intelligence (AI). It traces the evolution of bank marketing strategies from mass-market to individualized approaches and analyzes recommendation system architectures as instruments of customer-centric marketing. Special attention is paid to the Next Best Offer (NBO) model in the context of customer lifecycle management and marketing campaign conversion optimization. The experience of Russian and international banks is reviewed, and the marketing effects and ethical limitations of AI-driven personalization are discussed.
bank marketing, personalization, artificial intelligence, recommendation systems, Next Best Offer, customer experience management, cross-selling
1. Bobkova E.A. Primenenie iskusstvennogo intellekta v bankovskoy sfere: tehnologii i rezul'taty: vypusknaya kvalifikacionnaya rabota. — SPb.: SPbGU, 2025. — URL: https://dspace.spbu.ru/bitstreams/cae08fc1-2d4b-4d89-aaba-2a061195557f/download (data obrascheniya: 15.03.2026).
2. PAO Sberbank. Predvoshischenie zhelaniy klientov Sbera. — 2024. — URL: https://ai-russia.ru/library/sber-predicitve (data obrascheniya: 15.03.2026).
3. T-Bank AI Research. Proryv v personalizacii: metod Sampled Maximal Marginal Relevance (SMMR). SIGIR-2025, Paduya. — 2025. — URL: https://news.mondiara.com/categories/7/posts/136985 (data obrascheniya: 15.03.2026).
4. Accenture. Banking Top 10 Trends for 2024: Banking on AI. — 2024. — URL: https://www.accenture.com/content/dam/accenture/final/industry/banking/document/Accenture-Banking-Top-10-Trends-2024.pdf (data obrascheniya: 15.03.2026).
5. Dawgen Global. Personalization in Banking: Data-Driven Journeys for the Modern Customer. — 2025. — URL: https://www.dawgen.global/personalization-in-banking-data-driven-journeys-for-the-modern-customer/ (data obrascheniya: 15.03.2026).
6. McKinsey & Company. Global Banking Annual Review 2025. — 2025. — URL: https://www.mckinsey.com/industries/financial-services/our-insights/global-banking-annual-review (data obrascheniya: 15.03.2026).
7. McKinsey & Company. The State of Retail Banking: Profitability and Growth in the Era of Digital and AI. — 2024. — URL: https://www.mckinsey.com/industries/financial-services/our-insights/the-state-of-retail-banking-profitability-and-growth-in-the-era-of-digital-and-ai (data obrascheniya: 15.03.2026).
8. Met I., Erkoc A., Seker S.E., Erturk M.A., Ulug B. Product Recommendation System With Machine Learning Algorithms for SME Banking // Hindawi / Wiley. — 2024. — DOI:https://doi.org/10.1155/2024/5585575. EDN: https://elibrary.ru/BZGSMX
9. Pritam A., Pramod D. Recommender System for Banking Industry with Collaborative Filtering and XGBoost Classifier // Science, Education and Innovations in the Context of Modern Problems. — 2025. — Vol. 8. — No. 3. — DOI:https://doi.org/10.56334/sei/8.3.501. EDN: https://elibrary.ru/COZZMH
10. QUALCO. Mastering Cross-Selling with Next Best Product Recommendation. — 2024. — URL: https://www.qualco.eu/hubfs/Whitepapers/2024/D3E/5%20Predictive%20Analytics%20Use%20Cases/Predictive%20Analytics%20Use%20Case%20%7C%20Mastering%20Cross-Selling%20with%20Next%20Best%20Product%20Recommendation.pdf (data obrascheniya: 15.03.2026).
11. Siji V. The Impact of Artificial Intelligence on Personalised Banking Services // Asia-Pacific Journal of Management Research and Innovation. — 2025. — DOI:https://doi.org/10.1177/2319510X251359393. EDN: https://elibrary.ru/TGOJQS
