This study explores the use of Generative Adversarial Networks (GANs) to detect AI deepfakes and fraudulent activities in online payment systems. With the growing prevalence of deepfake technology, which can manipulate facial features in images and videos, the potential for fraud in online transactions has escalated. Traditional security systems struggle to identify these sophisticated forms of fraud. This research proposes a novel GAN-based model that enhances online payment security by identifying subtle manipulations in payment images. The model is trained on a dataset consisting of real-world online payment images and deepfake images generated using advanced GAN architectures, such as StyleGAN and DeepFake. The results demonstrate that the proposed model can accurately distinguish between legitimate transactions and deepfakes, achieving a high detection rate above 95%. This approach significantly improves the robustness of payment systems against AI-driven fraud. The paper contributes to the growing field of digital security, offering insights into the application of GANs for fraud detection in financial services. Keywords- Payment Security, Image Recognition, Generative Adversarial Networks, AI Deepfake, Fraudulent Activities

Shopping online has become more and more popular for consumers, especially during the pandemic. With online shopping, customers cannot only buy necessities but also enjoy shopping at home. And the quick shipping speed and free return policy also make the shopping experience more reasonable and enjoyable. To provide a better online shopping experience, AI plays an important role in improving online payments. In brief, the use of AI in online payments serves consumers who need to pay. The purpose of AI applications is to provide an easier, safer, and more enjoyable payment process, thus encouraging online shopping.

In a world where all technologies are constantly evolving, online payment follows the trends. So, the big question is how artificial intelligence impacts online payment in the short term. Online shopping has expanded greatly beyond our computers and our phones with the help of AI on payments, and it will continue to grow as we may see new devices with better capabilities. Consumers are looking for a payment experience that doesn't sacrifice safety, and they expect this technology to be at reach. While still might make us humans feel a bit uncomfortable and puzzled, chatbots are a tool to provide buyers with relevant content and suggestions to automate the back-end.

Enhanced customer experience has become a non-negotiable for businesses that want to attract and retain customers. As the world continues to move into the digital space, new communication channels and advanced data platforms have created opportunities for organisations to improve their customers' experience and adapt to new ways of doing business. With more people and businesses moving online, what will 2021 hold when it comes to digital communication? And what can companies do to prepare for what's coming? Businesses are starting to take notice of how easy it is to connect with customers through mobile platforms and apps.

There are many approaches to determining whether a particular transaction is fraudulent. From rule-based systems to machine learning models - each method tends to work best under certain conditions. Successful anti-fraud systems should reap the benefits of all the approaches and utilize them where they fit the problem best. The notion of networks and connection analysis in the world of anti-fraud systems is paramount since it helps uncover hidden characteristics of transactions that are not retrievable any other way. In this blog post, we will try to shed some light on the way networks are created and then used to detect fraudulent transactions.

Fintech represents a powerful synergy of these industries and promise to bring out modern banking to a new level. Being in a firm embrace with each other, financial services and technology innovations will provide institutions with new opportunities that expand far beyond traditional banking services. Fintech can considerably improve customer experience, combining new data processing and storage strategies with advanced analytics and new capabilities of cybersecurity. Here we will overview six global trends that will disrupt the banking industry in the upcoming year. In 2019, the buzz around artificial intelligence applications in fintech was huge.

Your mother's maiden name – the name of your first pet – the city you were born in. What do these all have in common? Not only are they popular security questions for online authentication but given the culture and our tendency to overshare on social media, they are no longer the most "secure" security questions. With sites like Facebook growing in popularity with the over 55s, are our loving parents actually the weakest line of defence in protecting our digital identities? If they insist on posting personal information on our behalf, says Callsign CMO and go-to-market strategy head Sarah Whipp, have we exposed ourselves more than we realise?

Online payment providers have been servicing customers all over the world since CyberCash opened its virtual doors in 1995. Unfortunately, the growing number of companies relying on online payment providers has created an epidemic of fraud. According to one recent report, the rate of fraud has increased 45%, to nearly $60 billion in recent years. In Australia alone, online payment fraud has exploded to $476 million. Online payment providers like PayPal have started turning to machine learning, as they strive to tackle the growing number of cybercriminals seeking to exploit their customers.

Starting September 2019 in the European Union, a large portion of online payments greater than €30 (currently about $35) will require multifactor authentication. Consumers will need to use two of three things to verify transactions: something they know, like a password; something they have, like a digital device, perhaps a USB token, that identifies them; or something they are: biometric data. Proofs based on physical characteristics, like fingerprints and faces, are slowly becoming more common. This legislation will likely cause them to surge. Most consumers using biometrics will likely do so on their phones, many of which already have technology that payment-service providers will use to verify payments--such as Apple Inc.'s Touch ID fingerprint sensors or Face ID facial-recognition software on its iPhones.

As the number of e-commerce customers is rising, so are the instances of consumer frauds, causing huge loss to online retailers. But, the founders of Gurugram-based start-up ThirdWatch Data Pvt Ltd say their fraud analytics product is bringing down frauds by 30-40 per cent since its launch in December 2017. In recent times, arrests have been made in Hyderabad and Rajasthan for defrauding Flipkart of products worth a few lakhs. Amazon India too has faced consumer frauds. Shashank Agarwal, Co-founder, ThirdWatch, said customer frauds can happen at two levels -- return to origin (RTO) and abuse of promo codes.