Fraud detection and prevention are inevitable as more organizations adopt the online transaction mode to generate invoices, receipts, and e-payments. Fraud is a financial loss and a significant compliance risk, and a dent in the company’s reputation. Thus, it is vital to building a robust risk management mechanism in Organizations to identify and prevent any fraudulent transactions. An increasing market proportion for Fraud Detection software is a valid testimony.
Fraudulent payments in e-commerce marketplaces, counterfeit invoices, receipts haunting various organizations, financial frauds, and money laundering in the BFSI sector make fraud detection one of the biggest emerging challenges. Safe and shady transactions have their specific characteristics based on a typical behavioral pattern.
Rubiscape builds Machine Learning based Fraud Detection models that employ Data Analysis and Pattern Recognition to identify a Fraud.
Rubiscape assists fraud analysts to build and validate a model that can predict whether a payment is fraudulent. This helps them to detect more accurately both fraud and non-fraud transactions. This should help them inculcate an open and flexible mind regarding people’s activities on the internet.
RubiStudio – Data Exploration, Data Joiner, Merger, Statistical Hypothesis, Code Fusion
RubiML – Clustering models, Silhouette Score – Code Fusion
Rubisight – Story and Dashboard.
The given dataset contains information related to the amount involved during each transaction and time.