Credit Card Fraud Detection Using AI
An MNC FinTech client from an online payments background requested AI-based solutions to detect real-time credit card fraud. The case study identified collaboration opportunities, industry trends, emerging technologies, and vital players. Detailed analyses emerged from the findings, which included product development, strategic edge, technical trends, acquisition of companies, mergers, and comprehensive research on competitors. It helped the client develop better strategies for the domain with R&D guidance.
Client Background:
The client is a multinational financial technology company operating an online payments system in the majority of countries that support online money transfers, and serves as an electronic alternative to traditional paper methods such as checks and money orders.
Engagement Objective:
The study was conducted to find the AI-based solutions available on the market to detect credit card fraud in real-time.
The study included the –
- Identification of various machine learning models used for fraud detection
- Identification of relevant trends or new technologies
- Identification of key players
- Identification of various collaboration opportunities
Client Impact:
Several business insights from this technology research were generated. The problem/ technologies on which competitors were focusing and having innovative solutions for the same, i.e., the technical edge, were the points of attraction.
- A detailed white space analysis helped in further planning of the business.
- Outputs like mergers, acquisitions, and product development gave direction to the research and development team of the client.
A detailed bibliographic summary of all the assignees of interest, including filing pattern, geographical distribution, legal status, technical distribution, technical focus, etc., helped the client to understand the technical trends and strategies opted by competitors in the technology domain.
