This article has been written by Geetanjali Wadhwa pursuing a Training program on Using AI for Business Growth course from Skill Arbitrage.

This article has been edited and published by Shashwat Kaushik.

Introduction

In our ever-evolving digital landscape, more and more people are turning to the internet for healthcare advice, information and even to buy medicines. Especially during the COVID-19 pandemic, online pharmacies became incredibly popular due to their convenience during lockdowns.

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In the Journal of Medical Internet Research, Andras Fittler  Pharm D, PhD, and his colleagues An online pharmacy is an internet-based vendor (legal or illegal) that sells medicine and may operate as an internet-only site, an online branch of a “brick-and-mortar” pharmacy, or sites representing a partnership among pharmacies.”

While these online pharmacies offer convenience, they also come with risks. There is a dark side to this ease: fraudulent practices. Some websites sell fake drugs or use stolen prescriptions, putting people’s health in danger. Unlike spotting fake designer bags or counterfeit money, identifying shady online pharmacies or bogus medications is much harder. An illegal or fake online pharmacy does not follow any rules, They are not licensed, to sell pharmaceuticals and those running the pharmacy do not have permission to prescribe or distribute medications.

It is worth emphasising that the traditional methods used for fraud prevention are inadequate in the current environment because the cyber attacks being executed are highly advanced and sophisticated. This is where AI emerges as a game changer.

The problem of fraud in online pharmacies

The internet has made it easy to buy all sorts of medicines through online pharmacies, often at lower prices than traditional stores. But unfortunately, among the legitimate ones, many shady websites are posing as real pharmacies. They take advantage of the online platform to sell fake, tainted or low-quality drugs. 

And to make matters worse, some medicines are sold illegally without the necessary prescriptions. Counterfeit drugs are a global issue, with their presence increasing worldwide. As per The Times of India In some countries, the percentage of counterfeit drugs is even higher, with estimates ranging from 10% to 30%. According to the National Library of Medicine, An estimated 95% of all online pharmacies operate unlawfully.

Consequence 

Risk to health and wallet

Counterfeit drugs are fake copies of real, legitimate medicines. They often look identical to the real thing-the same size, shape, and colour.

Health risks Counterfeit drugs may contain:-

  • An incorrect amount of the active ingredient.
  • The wrong active ingredient, or
  • No active ingredients at all,
  • Counterfeit drugs laced with fentanyl (an opioid that is 50 times stronger than heroin) have killed numerous people
  • Counterfeit antibiotics:- They not only fail to deliver the much-needed treatment, but fake antibiotics can also create antibiotic resistance in a community, decreasing the effectiveness of these critical medications.

Financial risk (Identity theft)

  • Consumers often unknowingly purchase counterfeit drugs directly through online sources that seem like legitimate pharmacies but are, in fact, illegal.
  • They are lured into illegal sales as these sites offer large price discounts,
  • They are offered options for purchasing medications without a prescription or in large quantities.
  • These illegal online pharmacies put consumer’s financial information into the hands of criminals.
  • They do not meet the required security standards, which means consumers who shop at them may be at risk of having their information leaked, stolen, or shared by antisocial elements. Some fraudulent online pharmacies have planted malware downloads intended to steal personal information from consumers who visit them.

Rip-offs

Various illicit web-based pharmacies demand payment through PayPal or Google Pay. Countless grievances lodged by consumers with the National Consumers League’s Fraud.org attest to payments made for medications that never materialise. Attempts to trace purchases or secure refunds lead to a frustrating cycle of customer service communications or outright silence, leaving consumers empty-handed.

AI: a weapon against fraud

AI is a machine performing a task that would otherwise require human intellect. Consumer products such as Siri, Alexa, and Google are examples of AI for day-to-day tasks like depositing a cheque with a banking app or, converting speech to text. But AI goes beyond these basics, it is involved in things like facial recognition, brain-implanted computer chips, and even creating content. 

AI fraud detection operates much like a vigilant detective, piecing together clues from vast amounts of data to uncover suspicious activities. It starts with gathering data from various sources, much like detectives canvassing a neighbourhood for evidence. Then, it’s about refining the data, picking out the most telling features that might indicate foul play, akin to identifying key pieces of evidence at a crime scene.

Once the data is prepped, it’s time to train the AI models, teaching them to recognise patterns of fraud just like detectives train their instincts through experience. The models are then unleashed to sift through the data, looking for anything suspicious, much like detectives scanning for anomalies.

But AI isn’t just a one-and-done deal; it’s a continuous learning process, much like detectives who keep up with evolving criminal tactics. AI systems constantly update themselves with new data, ensuring they’re always one step ahead of fraudsters.

When the AI detects something fishy, it doesn’t just keep it to itself; it raises the alarm, flagging suspicious activities for further investigation, much like a detective reporting their findings to the higher-ups.

In short, AI-powered fraud detection systems use machine learning algorithms to analyse large amounts of data, including transactional patterns and user behaviour. By establishing a baseline of normal activity and continuously monitoring for deviation, these systems can efficiently

Identify suspicious activities that are indicative of fraud. 

Beyond detection- AI for proactive measures

Beyond just spotting fraud, AI also takes proactive measures. It’s like having a detective who not only solves crimes but also predicts where the next one might happen. By analysing vast amounts of data, AI can sniff out potential risks before they turn into full-blown threats, causing

significant losses or substantial harm to a platform and its users.

Technology applied for proactive measures

Enhanced data analysis

AI refines risk management by incorporating more sophisticated data analysis. Machine learning models can evaluate a broader range of data sources, including news articles and social media, to pinpoint potential risks that may not be evident through traditional methods.

Continuous learning

Predictive analytics excels in fraud detection due to its ability to learn continuously and adapt simultaneously. These systems constantly update their models with fresh data so that they stay in line with the latest fraud tactics and remain highly up-to-date and effective.

Implementing additional verification steps like two-factor verification (2FA) and blocking suspicious IP addresses bolsters security measures against fraudulent activities.

Thus, AI extends beyond detection to proactive measures such as enhanced data analysis and continuous learning. By leveraging predictive analytics, AI systems can anticipate emerging threats before they result in significant harm.

Human AI partnership- a winning combination

The symbiosis of human expertise and AI remains vital, with AI complementing human capacity rather than replacing it. Collaborative efforts between AI and humans enhance efficiency and effectiveness by mitigating fraudulent activities.

Paypal hired detectives to train the machine to identify patterns of fraudsters. They developed legitimate and fraudulent user examples so that machines could identify one from the other.

Jason Gasper, senior vice president and chief commercial officer of Orderinsite, an inventory software company for pharmacies, told PYMNTS that his company uses AI to help recognise instances of prescription fraud or abuse by examining prescription patterns, dispensing habits, and patient histories. It can flag dubious activities, enabling the pharmacy to take necessary measures to protect against misuse.

It’s important to note that while AI can greatly benefit pharmacies, human judgement and action remain crucial, he said. “AI systems should be viewed as tools to augment pharmacists rather than take their place to ensure the highest standards of patient care and safety.”

The future of AI based fraud detection

Looking ahead, it’s clear that AI and machine learning will keep evolving and play a big role in how we catch fraudsters. There’s a lot of hope that they’ll make fraud detection more accurate and faster, but at the same time, we need to deal with worries about privacy and biases that these technologies might bring. However, if we can find a way for humans and AI to team up, the future of fraud detection looks pretty bright. It means we can keep online transactions safe and trustworthy, especially in sensitive fields like pharmaceutical sales.

Moreover, by combining the strengths of human intuition with the computational power of AI, we can create a robust system that not only identifies fraudulent activities but also adapts to new threats in real-time, ensuring a constantly improving defence against cybercrime.

Conclusion

The proliferation of online pharmacies presents both opportunities and challenges in the healthcare landscape. While these platforms offer convenience and accessibility to consumers, they also open avenues of fraudulent activities, including the sale of counterfeit drugs and the compromise of sensitive personal information. Traditional methods of fraud detection have struggled to keep pace with the increasingly sophisticated tactics employed by cybercriminals. This is where artificial intelligence (AI) emerges as a vital tool in combating fraud in online pharmaceutical sales.

However, it is essential to recognise that AI should complement rather than replace human expertise. While the challenges of fraud in online pharmacies are significant, AI offers a promising solution for detecting and preventing fraudulent activities, ultimately contributing to a safer and more secure online healthcare ecosystem.

References

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