You will get Real-time fraud detection using XGBoost with fast, accurate decisions
Project details
š Built FraudShield AI ā a real-time fraud detection system powered by machine learning.
This system is designed to detect fraudulent financial transactions instantly by analyzing patterns, identifying anomalies, and assigning risk scores in under 150 milliseconds. It uses XGBoost for high-performance modeling and integrates explainable AI (SHAP) to provide transparency into every prediction.
š Key Results:
ā¢ 94% Accuracy
ā¢ AUC-ROC: 0.97
ā¢ Real-time decisioning (block / flag / approve)
FraudShield AI is scalable and can be deployed as an API, dashboard, or integrated system, making it suitable for fintech, e-commerce, and payment platforms.
š” This project focuses on solving real-world business problems ā reducing fraud, minimizing financial loss, and enabling smarter, faster decision-making through AI.
This system is designed to detect fraudulent financial transactions instantly by analyzing patterns, identifying anomalies, and assigning risk scores in under 150 milliseconds. It uses XGBoost for high-performance modeling and integrates explainable AI (SHAP) to provide transparency into every prediction.
š Key Results:
ā¢ 94% Accuracy
ā¢ AUC-ROC: 0.97
ā¢ Real-time decisioning (block / flag / approve)
FraudShield AI is scalable and can be deployed as an API, dashboard, or integrated system, making it suitable for fintech, e-commerce, and payment platforms.
š” This project focuses on solving real-world business problems ā reducing fraud, minimizing financial loss, and enabling smarter, faster decision-making through AI.
Machine Learning Tools
ChatGPT, Open Neural Network Exchange, pandas, Python, Python Scikit-Learn, PyTorch, scikit-learn, SQL, TensorFlow, XGBoostWhat's included
| Service Tiers |
Starter
$50
|
Standard
$120
|
Advanced
$300
|
|---|---|---|---|
| Delivery Time | 3 days | 5 days | 10 days |
Number of Revisions | 1 | 2 | 4 |
Number of Model Variations | 1 | 2 | 3 |
Number of Scenarios | 1 | 2 | 3 |
Number of Graphs/Charts | 2 | 5 | 8 |
Model Validation/Testing | |||
Model Documentation | - | ||
Data Source Connectivity | - | ||
Source Code |
About Noor
Data Scientist
Ahmedabad, IndiaĀ - 8:14 am local time
I help businesses transform raw data into clear insights, automation, and smart decision-making systems. With strong experience in Data Analysis, Machine Learning, and AI-driven solutions, I focus on delivering results that actually impact business performance.
š What I can do for you:
ā Data Cleaning & Preprocessing (Python, Pandas, NumPy)
ā Data Visualization & Dashboards (Power BI, Tableau)
ā Machine Learning Models (Prediction, Classification, NLP)
ā Web Scraping & Data Automation
ā SQL & Database Analysis
ā API Integration & Data Pipelines
š” Why choose me?
ā¢ I donāt just analyze data ā I solve business problems
ā¢ Clean, efficient, and scalable solutions
ā¢ Strong communication + on-time delivery
ā¢ Experience with real-world datasets and projects
š Tools & Technologies:
Python | Pandas | NumPy | Scikit-learn | TensorFlow | SQL | Power BI | Tableau | Excel | APIs
If you're looking for someone who can turn your data into actionable insights and intelligent systems ā let's work together.
š© Send me a message and letās discuss your project!
Steps for completing your project
After purchasing the project, send requirements so Noor can start the project.
Delivery time starts when Noor receives requirements from you.
Noor works on your project following the steps below.
Revisions may occur after the delivery date.
Requirement Analysis
Review client requirements, dataset, and project goals.
Data Preparation
Clean, preprocess, and explore the data for modeling.