AI in Financial Fraud Detection: A Machine Learning Perspective
Abstract
Financial fraud has become increasingly sophisticated, necessitating advanced tools for detection and prevention. This paper explores the application of machine learning (ML) techniques in identifying fraudulent activities within financial systems. By analyzing transaction patterns, user behavior, and anomaly detection methods, the study highlights the effectiveness of ML algorithms such as Random Forest, Gradient Boosting, and Neural Networks. Challenges, including data imbalance, interpretability, and real-time processing, are addressed. The research concludes with recommendations for integrating ML models into financial systems to enhance fraud detection accuracy and reduce operational risks.
References
Adusumilli, S., Damancharla, H., & Metta, A. (2020). Artificial Intelligence-Driven Predictive Analytics for Educational Behavior Assessment. Transactions on Latest Trends in Artificial Intelligence, 1(1). Retrieved from https://www.ijsdcs.com/index.php/TLAI/article/view/638
Adusumilli, S., Damancharla, H., & Metta, A. (2020). Machine Learning Algorithms for Fraud Detection in Financial Transactions. International Journal of Sustainable Development in Computing Science, 2(1). Retrieved from https://www.ijsdcs.com/index.php/ijsdcs/article/view/639
Whig, P., & Adusumilli, S. B. K. (2023). Enhancing Healthcare Delivery Through AI-Driven Supply Chain Innovations: A Case Study Perspective. International Transactions in Artificial Intelligence, 7(7).
Adusumilli, S. B. K. Mitigating Cybersecurity Risks in Embedded Systems A Software-First Approach.
Whig, P., & Adusumilli, S. B. K. (2022). Machine Learning Applications in Healthcare Supply Chains: Improving Efficiency, Resilience, and Patient Outcomes. Transactions on Recent Developments in Health Sectors, 5(5).
Adusumilli, S. B. K. (2023). TOWARDS ENERGY-EFFICIENT AIML INFERENCE ON EDGE DEVICES SOFTWARE SOLUTIONS AND CHALLENGES. Journal of Engineering Sciences, 14(11).
Adusumilli, S., Damancharla, H., & Metta, A. (2021). Deep Learning Techniques for Image Recognition in Autonomous Vehicles. (2021). International Meridian Journal, 3(3). https://meridianjournal.in/index.php/IMJ/article/view/94
Adusumilli, S., Damancharla, H., & Metta, A. (2021). Integrating Machine Learning and Blockchain for Decentralized Identity Management Systems. (2021). International Journal of Machine Learning and Artificial Intelligence, 2(2). https://jmlai.in/index.php/ijmlai/article/view/46
Adusumilli, S., Damancharla, H., & Metta, A. (2022). Blockchain-Based Secure Framework for IoT Data Management. International Journal of Sustainable Development in Computing Science, 4(1). Retrieved from https://www.ijsdcs.com/index.php/ijsdcs/article/view/640
Adusumilli, S., Damancharla, H., & Metta, A. (2022). Optimizing Supply Chain Efficiency Through Blockchain and Smart Contracts. (2022). International Numeric Journal of Machine Learning and Robots, 6(6). https://injmr.com/index.php/fewfewf/article/view/183
Adusumilli, S., Damancharla, H., & Metta, A. (2023). Enhancing Data Privacy in Healthcare Systems Using Blockchain Technology. Transactions on Latest Trends in Artificial Intelligence, 4(4). Retrieved from https://www.ijsdcs.com/index.php/TLAI/article/view/637
Adusumilli, S. B. K., Damancharla, H., & Metta, A. R. (2021). AI-Powered Cybersecurity Solutions for Threat Detection and Prevention. International Journal of Creative Research In Computer Technology and Design, 3(3).
Adusumilli, S. B. K., Damancharla, H., & Metta, A. R. (2020). Leveraging AI for Real-Time Sentiment Analysis in Social Media Networks. International Numeric Journal of Machine Learning and Robots, 4(4).
Dhaiya, S., Pandey, B. K., Adusumilli, S. B. K., & Avacharmal, R. (2021). Optimizing API Security in FinTech Through Genetic Algorithm based Machine Learning Model.
Manoharan, G., Mishra, A. B., Adusumilli, S. B. K., Chavva, M., Damancharla, H., & Lenin, D. S. (2024, May). Supervised Learning for Personalized Marketing Strategies. In 2024 International Conference on Advances in Computing, Communication and Applied Informatics (ACCAI) (pp. 1-6). IEEE.
Galla, E. P., Rajaram, S. K., Patra, G. K., Madhavram, C., & Rao, J. (2022). AI-Driven Threat Detection: Leveraging Big Data For Advanced Cybersecurity Compliance. Available at SSRN 4980649.
Vattikuti, M. C. (2023). Real-Time Anomaly Detection in Industrial IoT Systems Using Hybrid AI Models. International Scientific Journal for Research, 5(5).
Vattikuti, M. C. (2023). Ethical AI Framework for Bias Mitigation in Machine Learning Algorithms. International Scientific Journal for Research, 5(5).
Vattikuti, M. C. (2022). Federated Learning for Privacy-Preserving AI in Healthcare Applications. International Transactions in Artificial Intelligence, 6(6).
Vattikuti, M. C. (2022). Generative Adversarial Networks for Data Augmentation in Medical Imaging. International Journal of Sustainable Development in Computing Science, 4(3).
Vattikuti, M. C. (2022). Comparative Analysis of Deep Learning Models for Tumor Detection in Medical Imaging. Research-gate journal, 8(8).
Vattikuti, M. C. (2020). A Comprehensive Review of AI-Based Diagnostic Tools for Early Disease Detection in Healthcare. Research-gate journal, 6(6).
Vattikuti, M. C. (2018). Leveraging Edge Computing for Real-Time Analytics in Smart City Healthcare Systems. International Transactions in Artificial Intelligence, 2(2).
Vattikuti, M. C. (2018). Leveraging AI for Sustainable Growth in AgTech: Business Models in the Digital Age. Transactions on Latest Trends in IoT, 1(1), 100-105.
Vattikuti, M. C. (2017). Ethical Framework for Integrating IoT in Urban Healthcare Systems. International Transactions in Artificial Intelligence, 1(1).
Vattikuti, M. C. (2016). The Rise of Big Data in Information Technology: Transforming the Digital Landscape. International Journal of Sustainable Development in computer Science Engineering, 2(2).
Vattikuti, M. C. (2015). Harnessing Big Data: Transformative Implications and Global Impact of Data-Driven Innovations. International Journal of Sustainable Development in computer Science Engineering, 1(1).
Vattikuti, M. C. (2014). Core Principles and Applications of Big Data Analytics. Transactions on Latest Trends in Health Sector, 6(6).
Davuluri, M. (2023). AI for Healthcare Workflow Optimization: Reducing Burnout and Enhancing Efficiency. International Numeric Journal of Machine Learning and Robots, 7(7).
Davuluri, M. (2023). AI in Surgical Assistance: Enhancing Precision and Outcomes. International Machine learning journal and Computer Engineering, 6(6).
Davuluri, M. (2022). AI in Mental Health: Transforming Diagnosis and Therapy. International Machine learning journal and Computer Engineering, 5(5).
Davuluri, M. (2021). AI for Chronic Disease Management: Improving Long-Term Patient Outcomes. International Journal of Machine Learning and Artificial Intelligence, 2(2).
Davuluri, M. (2021). AI in Personalized Oncology: Revolutionizing Cancer Care. International Machine learning journal and Computer Engineering, 4(4).
Davuluri, M. (2020). AI-Driven Drug Discovery: Accelerating the Path to New Treatments. International Journal of Machine Learning and Artificial Intelligence, 1(1).
Davuluri, M. (2020). AI in Pediatric Healthcare: Transforming Care for Younger Patients. International Numeric Journal of Machine Learning and Robots, 4(4).
Davuluri, M. (2018). AI in Preventive Healthcare: From Risk Assessment to Lifestyle Interventions. International Numeric Journal of Machine Learning and Robots, 2(2).
Davuluri, M. (2017). AI-Enhanced Telemedicine: Bridging the Gap in Global Healthcare Access. International Numeric Journal of Machine Learning and Robots, 1(1).
Davuluri, M. (2022). Comparative Study of Machine Learning Algorithms in Predicting Diabetes Onset Using Electronic Health Records. Research-gate journal, 8(8).
Pindi, V. (2018). NATURAL LANGUAGE PROCESSING(NLP) APPLICATIONS IN HEALTHCARE: EXTRACTING VALUABLE INSIGHTS FROM UNSTRUCTURED MEDICAL DATA. International Journal of Innovations in Engineering Research and Technology, 5(3), 1-10.
Pindi, V. (2019). A AI-ASSISTED CLINICAL DECISION SUPPORT SYSTEMS: ENHANCING DIAGNOSTIC ACCURACY AND TREATMENT RECOMMENDATIONS. International Journal of Innovations in Engineering Research and Technology, 6(10), 1-10.
PINDI, V. (2022). ETHICAL CONSIDERATIONS AND REGULATORY COMPLIANCE IN IMPLEMENTING AI SOLUTIONS FOR HEALTHCARE APPLICATIONS. IEJRD-International Multidisciplinary Journal, 5(5), 11.
Pindi, V. (2021). AI in Dental Healthcare: Transforming Diagnosis and Treatment. International Journal of Holistic Management Perspectives, 2(2).
Pindi, V. (2020). AI in Rare Disease Diagnosis: Reducing the Diagnostic Odyssey. International Journal of Holistic Management Perspectives, 1(1).
Pindi, V. (2018). AI for Surgical Training: Enhancing Skills through Simulation. International Numeric Journal of Machine Learning and Robots, 2(2).
Pindi, V. (2017). AI in Rehabilitation: Redefining Post-Injury Recovery. International Numeric Journal of Machine Learning and Robots, 1(1).
DEEKSHITH, A. (2014). Neural Networks and Fuzzy Systems: A Synergistic Approach. Transactions on Latest Trends in Health Sector, 6(6).
Deekshith, A. (2023). Transfer Learning for Multilingual Speech Recognition in Low-Resource Languages. International Transactions in Machine Learning, 5(5).
Velaga, S. P. (2014). DESIGNING SCALABLE AND MAINTAINABLE APPLICATION PROGRAMS. IEJRD-International Multidisciplinary Journal, 1(2), 10.
Velaga, S. P. (2016). LOW-CODE AND NO-CODE PLATFORMS: DEMOCRATIZING APPLICATION DEVELOPMENT AND EMPOWERING NON-TECHNICAL USERS. IEJRD-International Multidisciplinary Journal, 2(4), 10.
Velaga, S. P. (2017). “ROBOTIC PROCESS AUTOMATION (RPA) IN IT: AUTOMATING REPETITIVE TASKS AND IMPROVING EFFICIENCY. IEJRD-International Multidisciplinary Journal, 2(6), 9.
Velaga, S. P. (2018). AUTOMATED TESTING FRAMEWORKS: ENSURING SOFTWARE QUALITY AND REDUCING MANUAL TESTING EFFORTS. International Journal of Innovations in Engineering Research and Technology, 5(2), 78-85.
Velaga, S. P. (2020). AIASSISTED CODE GENERATION AND OPTIMIZATION: LEVERAGING MACHINE LEARNING TO ENHANCE SOFTWARE DEVELOPMENT PROCESSES. International Journal of Innovations in Engineering Research and Technology, 7(09), 177-186.
Velaga, S. P. R. (2021). AI in Health Monitoring: Continuous Care through Wearable Technology. International Journal of Holistic Management Perspectives, 2(2).
Velaga, S. P. R. (2020). AI in Cardiovascular Care: From Early Detection to Personalized Treatment. International Journal of Holistic Management Perspectives, 1(1).
Velaga, S. P. R. (2018). AI in Healthcare Chatbots: Enhancing Patient Engagement and Support. International Numeric Journal of Machine Learning and Robots, 2(2).
Velaga, S. P. R. (2017). AI in Healthcare Accessibility: Bridging the Urban-Rural Divide. International Numeric Journal of Machine Learning and Robots, 1(1).
