The I4C and RBIH collaboration aims to enhance fraud detection in India's digital banking ecosystem using AI. The partnership focuses on improving the sharing of fraud risk intelligence and ...

Cybersecurity researchers have discovered a new Lua-based malware created years before the notorious Stuxnet worm that aimed to sabotage Iran's nuclear program by destroying uranium enrichment ...

Before you begin, it is recommended to create a new Google Cloud project so that the activities from this lab do not interfere with other existing projects. If you are using a provided temporary ...

This week we`re taking a look at how a modern bank rebuilds fraud detection for scale, speed, and complexity. Welcome back, and thanks to everyone who continues to read each week. Let`s dive in. Monzo ...

In today’s data-rich environment, business are always looking for a way to capitalize on available data for new insights and increased efficiencies. Given the escalating volumes of data and the ...

The threat actor behind the malware-as-a-service (MaaS) framework and loader called CastleLoader has also developed a remote access trojan known as CastleRAT. "Available in both Python and C variants, ...

This repository contains the open-source implementation of a financial transaction risk simulation tool. The system is designed to generate large-scale synthetic datasets for modeling and evaluating ...

In the digital-first world of fintech, trust is currency. Every day, billions of dollars move through digital contracts, scanned IDs, and mobile-captured receipts. But what if the documents you rely ...

The proliferation of technology throughout modern business has created novel opportunities for financial statement fraud. But technology tools can also be leveraged to help detect and prevent fraud.

Java users can integrate ML into their Spring applications with Spring Boot Starter for Deep Java Library. Apply these frameworks to integrate ML capabilities into microservices for deep learning.