Utsav Porwal

Credit Risk Modeling: Conducted credit risk modeling project using ML and NLP for fraud detection. Employed advanced ML techniques to analyze transactional data and enhance detection accuracy. Achieved measurable reductions in fraudulent activities.

Credit Card Prediction: In this project, I utilized ML techniques to predict and identify potential users who are more likely to be interested in obtaining a credit card, allowing targeted marketing efforts, and got improvement in 30% more leads. Churn Prediction Model: Developed churn prediction model using NLP and ML algorithms, to predict churn and identify at-risk customers. Successfully achieved a remarkable 25% reduction in churn rates. User Affinity Model: Developed and implemented a user affinity model using ML and NLP techniques to improve user engagement and retention. Analyzed user behavior and preferences using text data from product reviews and from user data to predict user preferences and suggest personalized recommendations. Stock Prediction Model: Designed and developed an innovative Stock Prediction Model using LSTM, a powerful deep learning technique. The model accurately forecasts stock prices, enabling smarter investment decisions for traders and investors. Freshdesk API Automation: Built an automated report for Customer support (CRM) to check every Information available to the User, also built certain checks to see if a user is showing any fraud behavior.

Google Dialogflow: Built Small Chatbot using Google Dialogflow, a powerful natural language processing (NLP) platform. Leveraged its capabilities to create user-friendly and interactive chat experiences, streamlining processes and increasing user satisfaction. Sentiment Analysis: Developed a sentiment analysis model to analyze Twitter reviews and provide insights on public opinions. Applied NLP techniques to classify reviews as positive, negative, or neutral.