PRIME-RE: A Parallel and Recursive Requirements Elicitation Approach for ML-Based Financial Decision Systems
By: Cosmin COJOCARU and Sorin IONESCU
References
- Basel Committee on Banking Supervision. (2013). Principles for effective risk data aggregation and risk reporting. Bank for International Settlements.
- Board of Governors of the Federal Reserve System. (2011). Supervisory guidance on model risk management (SR 11-7). Federal Reserve, Washington, DC.
- Cerchiello, P., Giudici, P., & Nicola, G. (2017). Twitter data models for bank risk contagion. Neurocomputing, 264, 50–56.
- Cojocaru, C., & Ionescu, S. (2025). A Supervised Framework for Document Processing at Scale with Large Language Models in Credit-Risk Research. International Conference of Management and Industrial Engineering, 12. https://doi.org/10.56177/12icmie2025.196.
- Doshi-Velez, F., et al. (2017).Towards a rigorous science of interpretable machine learning.arXiv preprint arXiv:1702.08608.
- Dumas, M., La Rosa, M., Mendling, J., & Reijers, H. A. (2018). Fundamentals of business process management (2nd ed.). Springer.
- European Parliament and Council. (2024). Artificial Intelligence Act. Proposed regulation, Brussels.
- Fayyad, U., et al. (1996). From data mining to knowledge discovery in databases. AI Magazine, 17(3), 37–54.
- Guidotti, R., et al. (2018). A survey of methods for explaining black box models. ACM Computing Surveys, 51(5), 93.
- Horkoff, J., et al. (2016). Goal-oriented requirements engineering: An extended systematic mapping study. Requirements Engineering, 21(2), 133–160.
- Kotonya, G., & Sommerville, I. (1998). Requirements engineering: Processes and techniques. John Wiley & Sons.
- Loughran, T., & McDonald, B. (2011). When is a liability not a liability? Textual analysis, dictionaries, and 10-Ks. The Journal of Finance, 66(1), 35–65.
- Pohl, K. (2010). Requirements engineering: Fundamentals, principles, and techniques. Springer.
- Power, D. J. (2002). Decision support systems: Concepts and resources for managers. Greenwood Publishing Group.
- Rolland, C., & Prakash, N. (2001). Matching ERP system functionality to customer requirements. Proceedings of the Fifth IEEE International Enterprise Distributed Object Computing Conference, 66–75.
- Shearer, C. (2000). The CRISP-DM model: The new blueprint for data mining. Journal of Data Warehousing, 5(4), 13–22.
- Sommerville, I., & Sawyer, P. (1997). Requirements engineering: A good practice guide. John Wiley & Sons.
- van Lamsweerde, A. (2001). Goal-oriented requirements engineering: A guided tour. Proceedings of the Fifth IEEE International Symposium on Requirements Engineering, 249–262.
- Vogelsang, A., et al. (2019). Requirements engineering for machine learning: Perspectives from data scientists. Proceedings of the IEEE/ACM International Workshop on Requirements Engineering for Machine Learning, 1–8.
DOI: https://doi.org/10.2478/picbe-2026-0047 | Journal eISSN: 2558-9652
Language: English
Page range: 584 - 594
Published on: Jul 24, 2026
Published by: Bucharest University of Economic Studies
In partnership with: Paradigm Publishing Services
Publication frequency: 1 issue per year
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© 2026 Cosmin COJOCARU, Sorin IONESCU, published by Bucharest University of Economic Studies
This work is licensed under the Creative Commons Attribution 4.0 License.