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PO#
#TBA04700
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PO Created Date
2025-03-20 19:46:54
Paid Date
2025-03-20 22:27:27
Competition
2025
Season
1
Entry ID
TBE105196
Entry Submission Date
2025-03-20 02:21:50
Member's Name
Kedarnath Goud Kothinti
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kothintikedar@gmail.com
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Project Description
Project Description for Judges
Question 1 : Provide a brief description / background of your nominated organizational, departmental, team, or individual circumstance. (Your response to this question will be used for public display if your entry is awarded.)
Description Kedarnath Kothinti serves as an Engineering Team Lead at a leading financial technology enterprise specializing in accounts payable automation. Kedarnath has spearheaded the development of an AI-Driven Fraud Prevention & Risk Management Platform designed to combat rising fraud across digital payment channels. This innovative solution leverages advanced machine learning models, real-time data streaming architecture, and low-latency inference systems to identify fraudulent transactions within milliseconds. Kedarnath's technical leadership has been instrumental in implementing sophisticated fraud detection algorithms including Random Forest, XGBoost, Isolation Forest, and graph-based detection models that continuously learn from both historical and real-time transaction data. His pioneering approach to integrating Delta Live Tables with Online Feature Inference has revolutionized the company's ability to detect and mitigate fraud attempts with minimal latency while maintaining regulatory compliance and governance standards. Kedarnath's expertise in optimizing fraud models with online learning techniques has enabled dynamic detection of emerging fraud patterns in real-time environments. Background With extensive expertise in AI systems and data engineering, Kedarnath proposed and executed an innovative approach utilizing Unity Catalog features and Delta Lake technologies. This architecture enabled ACID-compliant transactions, time travel capabilities for fraud pattern investigation, and schema evolution to support seamless feature updates. Under Kedarnath's direction, the team: Designed end-to-end data pipelines integrating real-time transaction processing with AI-driven fraud detection Developed a real-time feature store reducing fraud detection latency to milliseconds Implemented automated fraud detection workflows cutting investigation efforts by 60% The platform's impact has been substantial, resulting in 40-60% reduction in virtual card fraud losses, 11% growth in customer trust and user base, and quarterly savings exceeding $250,000 in fraud loss prevention. Additionally, the system minimizes false positives, ensuring legitimate customers experience frictionless transactions while maintaining robust security measures. Kedarnath's work on the AI-Driven Fraud Prevention & Risk Management Platform demonstrates exceptional leadership in applying cutting-edge AI technology to solve critical business challenges, making him an outstanding candidate for the AI & Automation award.
Question 2 : Outline your nominated organizational, departmental, team, or individual achievements, dated 1-3 years prior, based on your selected categories.
Professional Profile Kedarnath Kothinti serves as an Engineering Team Lead for a premier financial technology enterprise. He has demonstrated exceptional expertise in cloud architecture through his work on the AI-Driven Fraud Prevention & Risk Management Platform. This sophisticated system leverages advanced cloud computing infrastructure to process financial transactions with unprecedented speed and security. Kedarnath's extensive knowledge of cloud technologies enabled him to design end-to-end data pipelines that ensure seamless integration between real-time transaction processing and AI-driven fraud detection systems. Technical Leadership Kedarnath spearheaded the implementation of Delta Live Tables and Online Feature Inference within a scalable cloud environment. His innovative approach to integrating Unity Catalog features and Databricks Delta Lake concepts significantly enhanced delivery time while maintaining quality standards. This technical foundation enabled ACID-compliant transactions, time travel capabilities, and schema evolution—critical elements for secure financial processing in cloud environments. Key Achievements Kedarnath's implementation of cloud-native fraud detection solutions delivered remarkable results: Reduced fraud detection latency to milliseconds through deployment of real-time inference models using scalable cloud infrastructure Achieved a 40-60% reduction in virtual card fraud losses through implementation of cloud-based machine learning models Cut fraud investigation efforts by 60% through automated cloud-based workflows Developed a real-time feature store for online inference that significantly enhanced fraud prevention capabilities Optimized fraud models with online learning techniques to detect new fraud patterns dynamically Business Impact Under Kedarnath's technical direction, the enterprise experienced quantifiable benefits through his cloud computing innovations. His work saved more than $250,000 in quarterly fraud losses while increasing customer trust and user base by 11%. The cloud-based platform now handles large-scale virtual card transactions with enhanced confidence and security. The real-time data processing capabilities Kedarnath engineered enable instant fraud detection while maintaining data integrity through cloud-native architecture. His cost-efficient storage solutions and scalable design support large-scale fraud detection across the enterprise, ensuring compliance while enabling swift responses to emerging fraud threats.
Question 3 : Provide examples of the strategies / plans you have introduced, in order to attain your nominated organizational, departmental, team, or individual achievements. Explain why the highlighted achievements are significant / unique.
Kedarnath Kothinti's implementation of the AI-Driven Fraud Prevention & Risk Management Platform demonstrates exceptional expertise in automation architecture. Kedarnath pioneered an approach leveraging Unity Catalog and Databricks Delta Lake concepts, which fundamentally transformed fraud detection workflows. This strategy established a foundation for real-time data processing that enables instant fraud detection while maintaining data integrity through ACID transactions. His architectural vision incorporated time travel capabilities and auditability features, allowing analysts to investigate historical fraud patterns with unprecedented precision. Advanced Model Integration Strategy Kedarnath developed a sophisticated strategy for implementing multiple AI models simultaneously, including Random Forest, XGBoost, Isolation Forest, and graph-based detection algorithms. This multi-model approach ensures comprehensive fraud detection across various transaction types. By strategically designing a real-time feature store for online inference, Kedarnath reduced fraud detection latency to mere milliseconds—a critical advancement for preventing financial losses before they occur. His innovative approach included seamless integration of fraud detection APIs with account payable applications, creating a unified ecosystem for comprehensive protection across financial systems. Significance of Technical Innovations The significance of Kedarnath's work becomes evident through quantifiable outcomes. His implementation of automated fraud detection workflows has reduced manual investigation efforts by 60%, enabling fraud analysts to focus on complex cases requiring human expertise. The AI-driven platform has decreased virtual card fraud losses by 40-60%, delivering quarterly savings exceeding $250,000. What makes Kedarnath's achievements particularly noteworthy is his success in balancing robust security with customer experience. While enhancing fraud prevention, his system design minimizes false positives, ensuring legitimate customers transact without unnecessary friction—contributing to an 11% growth in customer trust and user base. The Delta Live Tables implementation automates ETL processes that enhance real-time fraud feature engineering, while optimized ML pipelines improve model training through incremental data updates. These innovations establish a new standard for AI-driven fraud prevention that is both technically sophisticated and business-critical, demonstrating Kedarnath's leadership in applying cutting-edge AI technology to solve significant financial challenges.
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