Evaluating the Operational Impact of AI-Based Forecasting and Intelligent Automation in Digital Financial Services

  • Authors

    • Chandran Department of CSE, MAM College of Engineering, India. Author

    DOI:

    https://doi.org/10.67228/30715628/IJMIET-V9I2P103

    Published 04-10-2026

  • Artificial Intelligence, Financial Forecasting, Intelligent Automation, Digital Financial Services, Operational Efficiency, Predictive Analytics, Financial Risk Management, Responsible Ai

    Issue

    Vol. 9 No. 2 (2026)

    Section

    Articles

  • Abstract

    The growing adoption of artificial intelligence (AI), predictive forecasting, and intelligent automation in digital financial services has improved operational efficiency, risk management, and customer service. However, their effectiveness depends on data quality, model reliability, system integration, regulatory compliance, and decision-making capabilities. This paper examines AI-driven forecasting and automation across digital banking, electronic payments, lending, fraud detection, customer service, and transaction processing. A conceptual framework is proposed that integrates financial data collection, quality assessment, predictive analytics, decision support, automated workflows, governance, and performance monitoring. Key evaluation metrics include forecast accuracy, processing time, service availability, error rates, fraud detection, operational costs, customer satisfaction, and regulatory compliance. Using a literature-based research approach, the study establishes a systematic method for evaluating existing records, simulations, and real-world implementations without presenting unverified results. The conceptual analysis highlights the importance of integrating predictions with governed workflows, reliable decision rules, exception handling, and human oversight. This framework supports financial institutions in assessing technology investments, promoting responsible AI adoption, improving service reliability, and enhancing transparency in financial decision-making.

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