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OALib Journal期刊
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AI and ML Applications in Banking: Ensuring Data Integrity as Code

DOI: -, PP. 1-17

Keywords: AI in Banking, Machine Learning in Finance, Data Integrity, Data Quality Assurance, Anomaly Detection, Predictive Analytics

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Abstract:

The banking industry is undergoing a profound transformation driven by advancements in Artificial Intelligence (AI) and Machine Learning (ML). These technologies are not only reshaping customer experiences but are also playing a pivotal role in ensuring data integrity as code within the financial sector. This paper explores the applications of AI and ML in banking, with a specific focus on their contributions to data integrity. By automating data validation, anomaly detection, and predictive analytics, AI and ML are enhancing the accuracy and reliability of financial data, thereby bolstering trust, compliance, and decision-making in the banking sector. This paper provides insights into key use cases, challenges, and future prospects of AI and ML in ensuring data integrity in banking.

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