AI-POWERED RISK MANAGEMENT IN FINTECH: LEVERAGING BIG DATA FOR FRAUD DETECTION
DOI:
https://doi.org/10.53555/ephijse.v10i3.262Keywords:
AI in FinTech, Fraud Detection, Big Data, Machine Learning, Anomaly DetectionAbstract
By allowing actual time analysis of vast amounts of information, AI is transforming risk management in FinTech, particularly in the fraud detection. Often depending on rule-based algorithms, conventional fraud detection methods find it difficult to fit the sophisticated methodologies utilized by the modern fraudsters. Big data analytics is used in AI-driven systems to find the anomalies, identify suspicious patterns & the react to emerging risks with more efficiency. By means of supervised learning for transaction categorization & the unsupervised learning for anomaly detection, ML approaches improves financial institutions' capacity to detect the fraudulent behavior with higher accuracy & the efficiency. Deep learning techniques study complex behavioral patterns across many data sources, hence improving fraud detection. Apart from technical proficiency, AI-driven fraud detection has to solve legal challenges like data security laws, compliance requirements, and ethical problems with bias in artificial intelligence models. Big data and artificial intelligence together are transforming fraud prevention methods, lowering false positives, and allowing proactive threat minimizing. Financial institutions are progressively protecting the consumer transactions, fostering trust & the lowering financial losses by means of AI based risk management solutions. Given the increasing cyberthreats, artificial intelligence's capacity for actual time learning & the flexibility make it a required component of contemporary FinTech security.
References
. Sairamesh Konidala. “What Is a Modern Data Pipeline and Why Is It Important?”. Distributed Learning and Broad Applications in Scientific Research, vol. 2, Dec. 2016, pp. 95-111
. Sairamesh Konidala, et al. “The Impact of the Millennial Consumer Base on Online Payments ”. Distributed Learning and Broad Applications in Scientific Research, vol. 3, June 2017, pp. 154-71
. Sairamesh Konidala. “What Are the Key Concepts, Design Principles of Data Pipelines and Best Practices of Data Orchestration”. Distributed Learning and Broad Applications in Scientific Research, vol. 3, Jan. 2017, pp. 136-53
. Sairamesh Konidala, et al. “Optimizing Payments for Recurring Merchants ”. Distributed Learning and Broad Applications in Scientific Research, vol. 4, Aug. 2018, pp. 295-11
. Sairamesh Konidala, et al. “A Data Pipeline for Predictive Maintenance in an IoT-Enabled Smart Product: Design and Implementation”. Distributed Learning and Broad Applications in Scientific Research, vol. 4, Mar. 2018, pp. 278-94
. Sairamesh Konidala, et al. “The Role of IAM in Preventing Cyberattacks ”. African Journal of Artificial Intelligence and Sustainable Development, vol. 3, no. 1, Feb. 2023, pp. 538-60
. Sairamesh Konidala, and Guruprasad Nookala. “Real-Time Analytics for Enhancing Customer Experience in the Payment Industry”. Journal of Artificial Intelligence Research and Applications, vol. 3, no. 1, Apr. 2023, pp. 950-68
. Sairamesh Konidala. “Analyzing IoT Data: Efficient Pipelines for Insight Extraction”. Journal of AI-Assisted Scientific Discovery, vol. 3, no. 2, July 2023, pp. 683-07
. Sairamesh Konidala. “Key Considerations for IAM in a Hybrid Work Environment ”. Journal of Artificial Intelligence Research and Applications, vol. 4, no. 1, Apr. 2024, pp. 670-93
. Nookala, G., et al. "End-to-End Encryption in Enterprise Data Systems: Trends and Implementation Challenges." Innovative Computer Sciences Journal 5.1 (2019).
. Nookala, Guruprasad, et al. "Automating ETL Processes in Modern Cloud Data Warehouses Using AI." MZ Computing Journal 1.2 (2020).
. Nookala, Guruprasad. "Automated Data Warehouse Optimization Using Machine Learning Algorithms." Journal of Computational Innovation 1.1 (2021).
. Nookala, G., et al. "Unified Data Architectures: Blending Data Lake, Data Warehouse, and Data Mart Architectures." MZ Computing Journal 2.2 (2021).
. Nookala, G., et al. "The Shift Towards Distributed Data Architectures in Cloud Environments." Innovative Computer Sciences Journal 8.1 (2022).
. Nookala, G., et al. "Designing Event-Driven Data Architectures for Real-Time Analytics." MZ Computing Journal 3.2 (2022).
. Nookala, G., et al. "Building a Data Governance Framework for AI-Driven Organizations." MZ Computing Journal 3.1 (2022).
. Nookala, Guruprasad. "Metadata-Driven Data Models for Self-Service BI Platforms." Journal of Big Data and Smart Systems 3.1 (2022).
. Nookala, G., et al. "Zero-Trust Security Frameworks: The Role of Data Encryption in Cloud Infrastructure." MZ Computing Journal 4.1 (2023).
. Nookala, G., et al. "Integrating Data Warehouses with Data Lakes: A Unified Analytics Solution." Innovative Computer Sciences Journal 9.1 (2023).
. Nookala, G., et al. "Evolving from Traditional to Graph Data Models: Impact on Query Performance." Innovative Engineering Sciences Journal 3.1 (2023).
. Nookala, Guruprasad. "Real-Time Data Integration in Traditional Data Warehouses: A Comparative Analysis." Journal of Computational Innovation 3.1 (2023).
. Nookala, G., et al. "Impact of SSL/TLS Encryption on Network Performance and How to Optimize It." Innovative Computer Sciences Journal 10.1 (2024).
. Nookala, G., et al. "Post-quantum cryptography: Preparing for a new era of data encryption." MZ Computing Journal 5.2 (2024): 012077.
. Nookala, Guruprasad. "Adaptive Data Governance Frameworks for Data-Driven Digital Transformations." Journal of Computational Innovation 4.1 (2024).
. Nookala, G., et al. "Governance for Data Ecosystems: Managing Compliance, Privacy, and Interoperability." MZ Journal of Artificial Intelligence 1.2 (2024).
. Nookala, G., et al. "SSL Pinning: Strengthening SSL Security for Mobile Applications." Innovative Engineering Sciences Journal 4.1 (2024).
. Nookala, G., et al. "Building Cross-Organizational Data Governance Models for Collaborative Analytics." MZ Computing Journal 5.1 (2024).
. Gade, Kishore Reddy. "Data Analytics: Data Governance Frameworks and Their Importance in Data-Driven Organizations." Advances in Computer Sciences 1.1 (2018).
. Gade, Kishore Reddy. "Data Analytics: Data mesh architecture and its implications for data management." Journal of Innovative Technologies 2.1 (2019).
. Gade, Kishore Reddy. "Data Governance and Risk Management: Mitigating Data-Related Threats." Advances in Computer Sciences 3.1 (2020).
. Gade, K. R. "Data Mesh Architecture: A Scalable and Resilient Approach to Data Management." Innovative Computer Sciences Journal 6.1 (2020).
. Gade, Kishore Reddy. "Data Mesh: A New Paradigm for Data Management and Governance." Journal of Innovative Technologies 3.1 (2020).
. Gade, Kishore Reddy. "Data-driven decision making in a complex world." Journal of Computational Innovation 1.1 (2021).
. Gade, Kishore Reddy. "Migrations: Cloud Migration Strategies, Data Migration Challenges, and Legacy System Modernization." Journal of Computing and Information Technology 1.1 (2021).
. Gade, Kishore Reddy. "Overcoming the Data Silo Divide: A Holistic Approach to ELT Integration in Hybrid Cloud Environments." Journal of Innovative Technologies 4.1 (2021).
. Gade, K. R. "Data Analytics: Data Democratization and Self-Service Analytics Platforms Empowering Everyone with Data." MZ Comput J 2.1 (2021).
. Gade, Kishore Reddy. "Data Lakehouses: Combining the Best of Data Lakes and Data Warehouses." Journal of Computational Innovation 2.1 (2022).
. Gade, Kishore Reddy. "Cloud-Native Architecture: Security Challenges and Best Practices in Cloud-Native Environments." Journal of Computing and Information Technology 2.1 (2022).
. Gade, Kishore Reddy. "Data Monetization: Turning Data into a Strategic Asset." Journal of Innovative Technologies 5.1
. Gade, Kishore Reddy. "Event-Driven Data Modeling in Fintech: A Real-Time Approach." Journal of Computational Innovation 3.1 (2023).
. Gade, Kishore Reddy. "The Role of Data Modeling in Enhancing Data Quality and Security in Fintech Companies." Journal of Computing and Information Technology 3.1 (2023).
. Gade, Kishore Reddy. "Federated Data Modeling: A Decentralized Approach to Data Collaboration." Journal of Innovative Technologies 6.1 (2023).
. Gade, Kishore Reddy. "Beyond Data Quality: Building a Culture of Data Trust." Journal of Computing and Information Technology 4.1 (2024).
. Gade, K. R. "Data quality in the age of cloud migration: Challenges and best practices." MZ Journal of Artificial Intelligence (2024).
. Komandla, V. Crafting a Clear Path: Utilizing Tools and Software for Effective Roadmap Visualization.
. Komandla, V. (2023). Safeguarding Digital Finance: Advanced Cybersecurity Strategies for Protecting Customer Data in Fintech.
. Komandla, Vineela. "Crafting a Vision-Driven Product Roadmap: Defining Goals and Objectives for Strategic Success." Available at SSRN 4983184 (2023).
. Komandla, Vineela. "Critical Features and Functionalities of Secure Password Vaults for Fintech: An In-Depth Analysis of Encryption Standards, Access Controls, and Integration Capabilities." Access Controls, and Integration Capabilities (January 01, 2023) (2023).
. Komandla, V. Enhancing Security and Fraud Prevention in Fintech: Comprehensive Strategies for Secure Online Account Opening.
. Komandla, Vineela. "Effective Onboarding and Engagement of New Customers: Personalized Strategies for Success." Available at SSRN 4983100 (2019).
. Komandla, Vineela. "Transforming Financial Interactions: Best Practices for Mobile Banking App Design and Functionality to Boost User Engagement and Satisfaction." Available at SSRN 4983012 (2018).
. Komandla, Vineela. "Transforming Customer Onboarding: Efficient Digital Account Opening and KYC Compliance Strategies." Available at SSRN 4983076 (2018).
. Komandla, Vineela. "Navigating Open Banking: Strategic Impacts on Fintech Innovation and Collaboration." International Journal of Science and Research (IJSR) 6.9 (2017): 10-21275.
. Katari, A. "Integrating Machine Learning with Financial Data Lakes for Predictive Analytics." MZ Journal of Artificial Intelligence 1.1 (2024).
. Katari, Abhilash. "Security and Governance in Financial Data Lakes: Challenges and Solutions." Journal of Computational Innovation 3.1 (2023).
. Katari, Abhilash. "Decentralized Data Ownership in Fintech Data Mesh: Balancing Autonomy and Governance." Journal of Computing and Information Technology 3.1 (2023).
. Katari, A. "Performance Optimization in Delta Lake for Financial Data: Techniques and Best Practices." MZ Computing Journal 3.2 (2022).
. Katari, A. "ETL for Real-Time Financial Analytics: Architectures and Challenges." Innovative Computer Sciences Journal 5.1 (2019).
. Katari, A. "Data Quality Management in Financial ETL Processes: Techniques and Best Practices." Innovative Computer Sciences Journal 5.1 (2019).
. Katari, A. "Real-Time Data Replication in Fintech: Technologies and Best Practices." Innovative Computer Sciences Journal 5.1 (2019).
