Fraud Retail

Reducing fraud in retail and e-commerce with automation

Retail and e-commerce businesses took a giant leap during the pandemic and so did the frauds. According to a study, losses in online payment came close to $20 billion in 2021, a 14% increase in one year. Of all the sales outlets, 54% of customers encountered frauds in online transactions, followed by spam calls, door-to-door sales, postal mail, and in-store sales.

With these statistics in hindsight, business owners are looking for robust systems to help them detect frauds and prevent revenue loss. Consequently, the global fraud prevention and detection market will grow from $20.9 billion to $38.2 billion between 2020 and 2025. With more buyers finding their comfort in online shopping, the rate of fraudulent activities will grow and companies need robust systems to counter-attack.*

Types of retail and e-commerce business frauds

The average consumer is actively shopping in both online and offline modes. And, when shopping offline, the transactions are still online. The vulnerabilities arising out of this are hotspots for fraudster activity. The most common frauds in the online retail space include:

  • Clean fraud:
  • This refers to any fraudulent transaction that bypasses the merchant’s regular checks.

  • ID theft:
  • These types of frauds happen when a fraudster uses the identity of another buyer and scams businesses.

  • Friendly fraud:
  • This involves an intentional malpractice of ordering an item and then claiming a chargeback after receiving the goods. In such cases, customers often deny that they received the goods.

  • Phishing:
  • This refers to emails that con people into clicking on a link that reveals confidential information to a fraudster. The fraudster can then use it to carry on online transactions.

  • Botnets:
  • Fraudsters hijack and remotely control a network of computers that become nodes to carry out further fraudulent activities.

It is clear that one cannot depend on manual fraud detection methods for such a wide range of challenges over millions of orders. Take the case of false positives wherein a system that is not mature triggers an alarm even for a legitimate transaction. This can cause customer dissatisfaction who may switch over to your competitors.

Manual detection of e-commerce frauds

Many companies rely on a manual review of their orders. However, this process is extremely inefficient. It consumes both time and human resources and does not guarantee good results. According to a report, merchants spend 52% of their fraud management budget on manual reviews.

eCommerce is a highly competitive market. Customers switch from one company to another quickly. Businesses are not only vying to provide best offers but also gain customer loyalty and retention. Companies need to simplify fraud detection and prevention to make better decisions and increase revenue.

Automation through online identity verification

One of the most efficient and low-cost online verification methods is IP intelligence (geolocation). It automatically calculates the location of the device and combines it with other order acceptance rules to calculate the fraud risk associated with that transaction.

Automation through AI/ML

Retailers that use traditional methods run the risk of hitting high false positives. Legacy systems detect only known frauds. On the contrary, AI-based systems use predictive algorithms to proactively detect anomalies and raise red flags. This helps retailers identify weak spots and anticipate potential issues before they happen.

Deep learning and AI algorithms analyse vast amount of historical data and isolate millions of data points to keep your transactions secure. AI-driven systems can either block the transaction or raise an alert for the company to investigate. Sophisticated systems

self-learn and optimise algorithms based on past transactions.

Here is how a typical AI-/ML-based system works. As the system matures, it becomes better at each of these steps:

  • Input the data
  • Extract the data points to analyse
  • Train the algorithm and continuously improvise
  • Create a fraud detection and prevention model

How can Infosys BPM help?

Our AI-/ML-powered and future-ready technology solutions for the retail and e-commerce industry, together with a team of experienced professionals, can transform your business. Automate your fraud prevention process with  fewer false positives, better ROI, and improvement in potential savings. The solution offerings include:

View our retail and e-commerce fraud management solution.

*For organisations on the digital transformation journey, agility is key in responding to a rapidly changing technology and business landscape. Now more than ever, it is crucial to deliver and exceed organisational expectations with a robust digital mindset backed by innovation. Enabling businesses to sense, learn, respond, and evolve like a living organism, will be imperative for business excellence going forward. A comprehensive yet modular suite of services is doing exactly that. Equipping organisations with intuitive decision-making automatically at scale, actionable insights based on real-time solutions, anytime/anywhere experience, and in-depth data visibility across functions leading to hyper-productivity, Live Enterprise is building connected organisations that are innovating collaboratively for the future.

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