ENHANCING DATA QUALITY IN CREDIT PROCESSING PIPELINES: A TECHNICAL DEEP DIVE
Keywords:
AI Observability, Credit Processing Pipelines, Data Quality Management, Real-Time Error Detection, Regulatory ComplianceAbstract
Credit processing pipelines represent a critical infrastructure in modern financial institutions, handling increasingly complex data streams and decision-making processes. This technical article examines the challenges and solutions in maintaining data quality across credit processing operations, focusing on implementing AI observability and advanced monitoring systems. Let’s explore how financial institutions leverage pattern recognition algorithms, automated validation frameworks, and machine learning models to enhance data quality management. The article presents a comprehensive analysis of real-time error detection mechanisms, advanced data profiling techniques, and the integration of AI observability solutions. Through a detailed case study of a major credit institution, we demonstrate these technologies' practical implementation and measurable impacts. The article also evaluates various open-source tools and emerging best practices while providing insights into future credit pipeline data quality management trends.
References
Samuel Aderemi, David Olutimehin. et al., "Big data analytics in the financial services industry: Trends, challenges, and future prospects: A review." 23 March, 2024. [Online]. Available: https://sciresjournals.com/ijstra/sites/default/files/IJSTRA-2024-0036.pdf
Scott Beaver, "30 Financial Metrics and KPIs to Measure Success in 2023” 22 March, 2023[Online]. Available: https://www.netsuite.com/portal/resource/articles/accounting/financial-kpis-metrics.shtml
Helen Moges, Bart Baesens et al., "Data Quality for Credit Risk Management: New Insights and Challenges proceedings," ResearchGate Publication, 2023. January 2011. [Online]. Available: https://www.researchgate.net/publication/286811120_Data_quality_for_credit_risk_management_New_insights_and_challenges_proceedings
Aneesh Shah and Keyley Davis, "Credit Data Solutions, 2024", 30 October, 2024. [Online]. Available:https://www.moodys.com/web/en/us/site-assets/chartis-credit-data-solutions-2024-quadrant-update-external.pdf
Yunchuan Sun, Lu Liu et al., "Alternative data in finance and business: emerging applications and theory analysis" Journal of Financial Innovation, vol. 5, no. 1, 2 December, 2024. [Online]. Available: https://jfin-swufe.springeropen.com/articles/10.1186/s40854-024-00652-0
Jerry Elig, "Regulatory Impact Analysis for Financial Regulations," CFPB Symposium Report, 2024. 21, July, 2020 [Online]. Available: https://files.consumerfinance.gov/f/documents/cfpb_ellig_written-statement_symposium-cost-benefit-analysis.pdf
Mohammad Douroudyan, Seyed Niaki et al., "Pattern recognition in financial surveillance with the ARMA-GARCH time series model using support vector machine," Expert Systems with Applications, vol. 186, 2022. 15 November, 2021. [Online]. Available: https://www.sciencedirect.com/science/article/abs/pii/S0957417421007636
Lei Zhang, Sean Howard. et. al, "Automated data validation: An industrial experience report," Journal of Systems and Software, vol. 194, 2022. March, 2023. [Online]. Available: https://www.sciencedirect.com/science/article/abs/pii/S0164121222002497
Geetesh Sanodia, "Enhancing CRM Systems with AI-Driven Data Analytics for Financial Services," ResearchGate Publication, 2024. July, 2024 [Online].Available: .https://www.researchgate.net/publication/383979015_Enhancing_CRM_Systems_with_AI-Driven_Data_Analytics_for_Financial_Services
S. Kumar and R. Singh, "AI and observability: The indispensable role of observability and artificial intelligence in managing modern IT environment," International Journal of Artificial Intelligence and Machine Learning, vol. 3, no. 1, pp. 89-102, June 2024. [Online]. Available: https://iaeme.com/MasterAdmin/Journal_uploads/IJAIML/VOLUME_3_ISSUE_1/IJAIML_03_01_008.pdf
Michael Brown., "Influence of Artificial Intelligence on Credit Risk Assessment in Banking Sector," ResearchGate Publication, June 2024. [Online]. Available:https://www.researchgate.net/publication/381183872_Influence_of_Artificial_Intelligence_on_Credit_Risk_Assessment_in_Banking_Sector
Venkata Pulla, Murat AL. et al., "Open Source Data Quality Tools Revisited," ResearchGate Publication, 2023. April, 2016. [Online]. Available:https://www.researchgate.net/publication/301632848_Open_Source_Data_Quality_Tools_Revisited
Seth Rao, "Data Quality Management: Framework and Metrics for Successful DQM Model" First Eigen Technical Blog, 2024. 28 November, 2024. [Online]. Available: https://firsteigen.com/blog/data-quality-management-the-complete-guide/
