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How generative AI can impact the world of e-commerce fraud prevention

Online payment fraud is an inevitable bane in the world of e-commerce, retailers, and merchants. This is only made worse by the fact that fraud detection is still an evolving discipline, especially when it comes to the identification of risk indicators that enable accurate fraud forecasting and prevention. There is also a lack of structured data, and historical information when it comes to online transactions, making the task more challenging. Thus, proactively identifying fraud patterns is imperative, and can be facilitated by the correct classification of fraud and non-fraud transactions.

The current economy has witnessed a spike in the need for consumer products and services, which is directly boosting e-commerce sales. As e-commerce sales and online transactions go hand in hand, this has led to a dramatic increase in online payment fraud. Despite the implementation of contemporary fraud prevention methodologies, fraudsters are always a step ahead in spotting loopholes.

In this landscape, the emergence of Generative AI poses a tricky question – how will fraudsters use this technology for criminal activities?

Decoding payment fraud

It is expected that by 2027, online merchants may lose around $ 343 Bn globally due to payment fraud, according to a study by Juniper Research. It’s quite obvious that fraud detection requires extreme precision to avoid false positives. Of course, a key challenge is to distinguish correctly between good and bad transactions.

Additionally, false declines are a major red flag when it comes to customers switching to different platforms, resulting in a loss of $ 600 Bn in global e-commerce in 2020.

The growth of e-commerce fraud has been exponential in the last few years. However, so has been the rise in fraudulent attacks with $ 20 Bn being lost in the year 2021, and almost $ 18 Bn in 2020.

New Technology = New Threats = New Opportunities

Since the introduction of AI models, our view of fraud prevention on e-commerce platforms has been completely redefined. Unfortunately, fraudsters too are exploiting generative AI in many ways such as doctoring images and videos, creating duplicate or fake identities, stealing data, etc.

Thankfully, AI-driven models are very capable when it comes to designing impactful fraud prevention strategies and predicting fraud. In simple terms, generative AI, like ChatGPT, can analyse millions of data points and live transactions, and identify links and patterns that could lead to any kind of fraud. In addition, there’s a possibility of scoring these threats based on pre-determined thresholds and reducing false positives to filter the genuine transactions.

So, what’s in store for the e-commerce space, with the use of Generative AI?

Unlike traditional fraud prevention methods, AI can proactively identify and flag potential fraud by analysing huge volumes of data, interpreting user behaviour, spotting fraud patterns and detecting anomalies. Such in-depth synthesis can enable merchants to conduct a detailed investigation into any instance of fraud and eventually mitigate losses.

There’s an even better use of generative AI – alerting the customer of any potential fraud risk and increasing awareness of different types of scams and frauds; and best practices to follow to safeguard against them. As criminals get tech-savvy, it is obvious that merchants need to harness the power of AI to prevent financial losses and damage to their brand reputation.

Almost every other innovative e-commerce company is looking to adopt the features of AI for fraud detection. Preventing such types of fraud using manual investigation would take forever and flagging them accurately would also consume a lot of time. This is where the intervention of a more accurate AI-driven fraud detection strategy comes into the picture. Advanced features like detecting links and anomalies, accurate analysis, identifying new fraud patterns, understanding behaviours, etc., can help the business in mitigating hidden fraud, and boost conversion rates and customer experience. It also keeps the fraud rates low, especially frauds like COD, which will help the merchants with cash flow and maintain profit margins.

It is no secret that AI can rescue the e-commerce sector from the jaws of murky fraudsters and secure it in a more robust way than traditional fraud prevention methodologies.

Anand Chandrashaker
Senior Domain Principal, Digital Transformation Services
Infosys BPM
Anand Chandrashaker leads the Digital Transformation Services group across Enterprise Services at Infosys BPM. His group is responsible for identifying client needs and deploying transformation levers that bring together technology and business domains – through levers such as analytics, process mining, automation, and implementation of proprietary / COTS solutions. Anand has been with Infosys BPM for the last 16 years and has managed a variety of roles in the past that includes FP&A, Corporate Strategy, M&A, and post-merger Integration.

Santosh Kumar
Senior Lead Analyst, Knowledge Services
Infosys BPM
Santosh is a thorough professional with over 13 years of experience in operations and risk management across different domains, especially retail and e-commerce.

Disclaimer: The views expressed in this feature article are of the author. This is not meant to be an advisory to purchase or invest in products, services or solutions of a particular type or, those promoted and sold by a particular company, their legal subsidiary in India or their channel partners. No warranty or any other liability is either expressed or implied.
Reproduction or Copying in part or whole is not permitted unless approved by author.

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