Shah Ali Newaj Topu
Executive Vice President
KONA Software Lab
Director, Secure Link Services Ltd
Title
Use of ML for Financial fraud detection
Abstract
A key challenge for financial services firms is to detect fraudsters before they can commit their crimes. This is particularly difficult in a world where data is at the heart of everything businesses do. By using machine learning, fraud detection can become much more accurate and effective.
Fraud prevention starts with the right processes and controls in place to assess all possible risks from system, performance, and productivity scenarios. The first step is to identify any potential issues that could lead to fraudulent activity. These should be investigated closely to determine whether they are genuine or not.
If there are any concerns about potential fraudsters, the next step is to analyze the data that they access. This allows you to check whether any suspicious patterns exist — such as unusual transactions or unusual user behavior — which might indicate fraud attempts or other security breaches.
Biography
Shah Ali Newaj Topu has 22 years of professional software development experience with substantial experience in very large-scale software development. He is currently working as Executive VP, Tech at Kona Software Lab, A Korean Multinational Software company focusing on Fintech, Crypto, and ML. As Senior VP, tech at Shohoz, one of the most promising startups in Bangladesh, he migrated a legacy monolith to modern cloud-based microservice architecture serving daily 20M API calls with 5M API calls per hour at peak. As CTO of Secure Link Services Ltd, a Swiss Multinational for 8 years, he built a company from 4 to 300 developers, expanded to 4 countries, and made over $100M in sales. He has developed and led outsourcing projects from UK, USA, Netherlands, and Switzerland over the last 2 decades.