Tenny Enoch Devadas
Biography
Tenny Enoch Devadas is a Lead Engineer and Architect with over 18 years of experience driving innovation across fintech, banking, agriculture, and healthcare domains. He specializes in building scalable, cloud-native solutions across various technologies. With deep expertise in AI and data science, Tenny has published scholarly articles on machine learning applications and served as a reviewer and judge for international conferences and global award programs.
He is a recipient of multiple prestigious honors, including Titan Business and Innovation Awards, the Stevie Awards for Technology Leadership, the Aureum International Award for Excellence in Innovation, and the Globee Leadership and Technology Awards. Tenny is also a Senior Member of IEEE, IETE, and Sigma Xi, and a member of BCS.
Beyond his technical leadership, he is passionate about applying AI for social good?addressing challenges in financial wellness, food distribution, and healthcare. Currently based in Dallas, Texas, Tenny continues to architect next-generation solutions that integrate data engineering, AI, and user empowerment, helping organizations build trust and resilience while delivering measurable business and social impact.
Research Interest
Artificial Intelligence and Machine Learning to domains such as FinTech, healthcare, agriculture, and urban systems. He focuses on scalable cloud-native architectures, predictive analytics, and smart automation for real-world impact.
Abstract
AI and Data Engineering: Transforming Debt Recovery into Financial Wellness
Global debt challenges demand innovative, scalable, and human-centered solutions. Traditional financial recovery systems are often reactive and impersonal, addressing issues only after individuals face severe distress. By combining Artificial Intelligence (AI) and Data Engineering, we can transform this approach into proactive financial empowerment.
AI models?such as risk classification, sentiment analysis, and personalized recommendation engines?work alongside real-time data pipelines powered by Kafka, Spark, and BigQuery to detect early warning signs, create unified financial profiles, and deliver tailored guidance. These insights enable personalized outreach, digital coaching, and long-term planning tools that help individuals achieve stability and resilience.
With privacy, transparency, and ethical AI practices at the core, this approach reduces debt burdens, increases early interventions, and promotes preventive financial education. Ultimately, AI and Data Engineering empower people to move beyond recovery, achieve financial wellness, and progress toward lasting financial freedom.
