🛡️ RakshaQuant - AI-powered paper trading for NSE using LangGraph multi-agent orchestration. Features 4 LLM agents, learning feedback loop, LangSmith observability & risk guardrails. Built with Groq, DhanHQ sandbox & PostgreSQL. Paper-first design.
REST API (built using AWS Lambda and Amazon Textract) to extract structured text data from images of Indian OVD(s) (Officially Valid Documents) like Aadhaar card, PAN Card, Driving License, Passport, etc.
Build a response model for predicting the probability of a response from each prospect and target the ones most likely to respond to the telemarketing campaign. The objective is to reduce the cost of the bank by doing a targeted campaign.
End-to-end KYC/AML compliance data analysis using mock datasets. Includes customer risk scoring, suspicious transaction flagging, and compliance reporting in Python (Pandas, Matplotlib).
Production-grade AI observability system for BFSI customer assistance — Dify + Gemini + Langfuse
This project demonstrates a mock QA test case automation and reporting workflow, using simulated data to showcase analysis, visualization, and insights. It highlights how test execution, status, priority, module, and tester performance can be tracked and analyzed for effective QA management.
BFSI & AI LITERACY HINGLISH KNOWLEDGE GRAPH™ HINGLISH COGNITIVE ANCHORING MODEL™
Claude AI Go-To-Market playbook for Indian banking, insurance & financial services. Enterprise use cases, RBI compliance mapping, production prompt templates.
In this project, task is to help banking organization to identify the right customers using predictive models. Using past data of the bank’s applicants, you need to determine the factors affecting credit risk, create strategies to mitigate the acquisition risk and assess the financial benefit of the project.
Computer Vision and OCR pipeline for banking documents — cheque reading (MICR extraction), ID card verification (MRZ parsing, face detection), signature verification (ORB feature matching), fraud detection (ELA, copy-move, noise analysis), and image quality assessment. Built with OpenCV, Azure AI Vision, and GPT-4o.
Docs-only case study of a compliance & anomaly detection platform on Azure + Databricks (Streaming ETL + Batch ELT + ML).
Secure full-stack BFSI banking app with JWT auth, OTP, transactions, and MySQL backend.
GCP-based Regulatory Reporting Lakehouse — Tier-1 Swiss Bank (Simulated Case Study):- Documentation-only repo illustrating a cloud-native data lakehouse architecture for regulatory reporting on Google Cloud Platform (GCS + BigQuery + Dataflow + Composer). Includes ADRs, runbooks, and compliance data contracts.
Comprehensive Kubernetes Zero to Hero course for corporate professionals in Telco, BFSI, and Cloud domains. Complete hands-on training from Git basics to production K8s deployments.
Sanitized ML-based risk scoring pipeline for a Tier-1 UK Retail Bank (GCP + BigQuery ML). Includes Batch/ETL ingestion, feature engineering, BQML training, scoring workflows, governance, lineage, and runbooks. No client code/data.
Multimodal RAG pipeline for banking — upload financial reports with charts and tables, ask questions, get grounded answers with citations. Uses Azure OpenAI GPT-4o, Azure AI Search (hybrid vector + keyword), and Azure AI Vision Florence image embeddings for cross-modal retrieval.
Production-grade banking document processing pipeline using Azure AI Document Intelligence, GPT-4o, and OpenCV. Extracts structured data from cheques, invoices, KYC forms, ID cards, and trade finance documents with KYC/AML compliance validation. Deployable as Azure Web App
Credit risk pipeline on 2M+ loan records — ROC-AUC 0.97, FICO-style scorecard, risk segmentation, and live Streamlit app.
Data Analytics Projects — Excel, Power BI, SQL | Aniket Ingale | MBA Operations
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