Revolutionizing Credit Risk Assessment AI in Card Transaction Analytics
Author(s): Arunkumar Paramasivan
Publication #: 2412086
Date of Publication: 03.02.2020
Country: India
Pages: 1-9
Published In: Volume 6 Issue 1 February-2020
DOI: https://doi.org/10.5281/zenodo.14551643
Abstract
This Article examines the transformative impact of artificial intelligence (AI) on credit risk assessment within card transaction analytics. By harnessing AI's advanced capabilities in data analysis and pattern recognition, financial institutions can now conduct more nuanced and accurate evaluations of an individual’s creditworthiness, identify potential defaults, and detect early signs of financial distress in real time. Traditional credit scoring models, previously limited by static data and periodic assessments, are significantly enhanced by AI’s ability to analyze vast transactional datasets dynamically. This approach facilitates more precise and personalized credit offers, improves decision-making processes, and mitigates risk, ultimately enabling more inclusive credit opportunities for a diverse consumer base. Through AI-powered analytics, lenders can foster responsible credit practices that support financial stability and expand access to credit.
Keywords: Artificial intelligence, credit risk assessment, card transactions, creditworthiness, predictive analytics, real-time monitoring, financial distress detection, inclusive credit, personalized credit offers, financial institutions.
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