Durga Krishnamoorthy
Product Manager | Retail & FinTech | Driving Innovation, Growth & Monetization
Pittsburgh, Pennsylvania, United States
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Durga Krishnamoorthy is a Digital Product Management Leader with 12 years of experience in Retail, AI and Financial Services. Backed by strong academics from Carnegie Mellon University, she brings her experiences from Fortune 500 Brands such as Cognizant, Kroger, Petco, TikTok and EY to thought leadership at Forbes, IEEE research and alike. She serves as a Board Member for a US-based Product Management Community.
Always love to give back through mentoring, writing, and speaking about the evolving role of Product leadership in shaping business and societal outcomes. Reach out to me at durga.krish33@gmail.com or setup time on https://adplist.org/mentors/durga-krishnamoorthy
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Topics
Safeguarding Personal Finances: A PySpark-Driven Risk Modeling Framework Inspired by Institutional F
This paper explores the application of advanced risk modeling techniques—Monte Carlo, historical, hybrid, and stress testing with economic capital—to personal finance, drawing lessons from the collapses of Lehman Brothers, Barings Bank, and Washington Mutual. Using PySpark, it demonstrates how individuals can mitigate financial risks, such as savings depletion and retirement shortfalls, by accurately estimating Value at Risk (VaR) and preparing for extreme scenarios. The study offers a scalable, data-driven approach to enhance financial resilience and decision-making for individuals.
Dynamic Offer and Payment Personalization (DPP)
Cart abandonment plagues e-commerce, with 69.8% of shoppers ditching carts in 2023 (Statista, 2024), costing $1.2 trillion yearly. This session unveils 'Dynamic Offer and Payment Personalization (DOPP),' a novel system that slashes abandonment by adapting payment options like digital wallets (49% adoption, eMarketer, 2024) or BNPL in real time using behavioral data and machine learning. A pilot with 10,000 transactions cut abandonment by 28%. Join us to explore DPP’s mechanics, see live data, and discuss its potential to transform checkout experiences. Perfect for retailers and tech innovators seeking actionable solutions.
Revolutionizing Homeopathy: Integrating Data Analytics and AI/ML for Precision Remedy Selection
This paper proposes a framework that leverages machine learning algorithms to dynamically adapt and refine homeopathy remedy recommendations based on patient-specific data, integrating feedback loops for continuous improvement and personalized treatment optimization.
Enhancing POS Security: AI-Powered Identity Matching for Transactions
Retail fraud at in-store Point of Sale (POS) terminals remains a pressing challenge, as current systems often process payments without verifying cardholder identity against customer records. This paper examines how artificial intelligence (AI) can enhance fraud prevention by matching credit card holder names with loyalty profile data in real time. With fraudulent transactions outpacing traditional verification, we propose an AI-powered solution for POS environments, employing natural language processing, anomaly detection, and behavioral analysis to validate identity during checkout. The system adapts to emerging fraud patterns, reducing unauthorized payments while ensuring a seamless customer experience. We explore its integration into POS workflows, highlighting benefits like improved transaction security, fewer chargebacks, and operational efficiency. This study provides retailers and payment processors with a practical framework to deploy AI at the POS, strengthening defenses and building trust in digital retail while preserving customer experience.
The Rise of Smart Villages:Connecting Communities through Data Analytics,AI/ML and Cloud Technology
Smart village initiatives harness advanced technologies like data analytics, AI/ML, and cloud computing to enhance rural infrastructure, optimize resource usage, and improve citizen services. These initiatives establish an intelligent, multi-service IoT network tailored for rural communities. This review provides an in-depth analysis of the platform’s components, technologies, and applications, offering insights into the future development of smart villages.
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