AI fraud detection: Key insights for startups and SMBs on rising online fraud

Key takeaways:

• Identify challenges and risks for SMBs regarding AI driven fraud
• Use AI-powered identity verification to catch fake documents and deepfakes.
• Implement flexible and effective security solutions to prevent the costs of fraud, and train your team to recognize fraud attempts.
• Continuously monitor transactions and account behavior.
• Staying proactive: with the right solution, SMBs can protect themselves from the growing threat of AI-driven fraud and focus on growing their business.

Fraud: the hidden threat for SMBs

Imagine this: as your customer base expands, you discover that many of your users sign up with fake IDs, a clear case of financial fraud. 

You’ve been working for months to grow your business, only to find out you have a major problem. Suddenly, what felt like a milestone for your business turns into a nightmare.

This isn’t a rare occurrence. With the rapid development of AI tools, fraudsters can now impersonate customers, business partners, or even the business owner with alarming accuracy.

According to a recent Deloitte report, financial crimes, including money laundering, have reached unprecedented levels, with estimates suggesting a staggering 2% to 5% of the global GDP, equivalent to nearly $2 trillion, laundered annually.

Most startups and SMBs have limited resources and budgets to address fraud. On the other hand, with the rise of AI, fraud is increasing and becoming more sophisticated.

So let’s dive into the most common challenges that SMBs face when it comes to fraud.

Here are some common challenges SMBs face:

• Limited resources for fraud detection.
  Most small businesses don’t have the budgets to invest in large, complex fraud-detection systems. This leaves them vulnerable to even the most common identity fraud, let alone sophisticated AI-driven attacks.
• Small teams with multiple responsibilities.
  SMB employees often wear many hats, from operations to customer support. Adding the task of identifying fraudulent activity to their existing workload makes it easy for fraud to slip through the cracks.
• Over-reliance on outdated security methods.
  Many SMBs still rely on traditional fraud prevention methods, like manual document verification or simple password protection. These methods are no match for AI-powered attacks designed to bypass standard security protocols.

What are the challenges presented by AI?

Generative AI has revolutionized industries by streamlining content creation and automating tasks, but it’s also a tool used by fraudsters.

Criminals now use AI to create deepfakes, bypass identity verification systems, and produce counterfeit documents.

Startups and SMBs are particularly at risk of falling victim to sophisticated fraud techniques fueled by AI advancements, such as deepfakes and document fraud.

Moreover, there is another issue leaving SMBs and startups open to the increasing risk of AI-generated fraud: the lack of precise and updated regulations regarding AI usage, especially when it comes to identity.

The rapid pace of AI advancement has outstripped regulators’ ability to keep up. Many countries lack a cohesive legal framework to govern AI usage, leaving businesses, especially SMBs, exposed to various risks.

As highlighted in Veriff’s guide on legal frameworks, global regulatory bodies are working to develop standardized rules around AI, but the process is slow and fragmented.

Another challenge is false positives in AI-powered fraud detection systems. Legitimate transactions can be incorrectly flagged as fraudulent, leading to customer frustration and potentially damaging the relationship between consumers and businesses. Ongoing refinement of AI models is essential to see fraud patterns, minimize false positives, and enhance customer satisfaction.

How AI is changing fraud 

Artificial intelligence is transforming the way fraudsters operate. While technology has given us powerful tools for growth, it has also enabled criminals to commit fraud and financial crime on a massive scale.

Here’s how generative AI is making online fraud easier for criminals - and harder for SMBs and startups to detect: 

1. Creating fake documents for identity theft

Fraudsters now use AI to generate highly convincing fake IDs, passports, and legal documents. These documents can pass basic identity checks, and because they’re generated by sophisticated algorithms, they can look identical to the real thing.

Generative AI can identify fraudulent activities, but also create convincing counterfeit documents, which can fool traditional ID verification methods. Fraudsters are evolving faster than ever, making it critical for startups and SMBs to use advanced identity verification solutions that go beyond manual checks.

Historical data plays a crucial role in training AI systems to detect fraud and fake documents. By analyzing previous cases of fraud and non-fraud, these systems can improve the precision of risk rules and optimize fraud prevention strategies.

Veriff’s insights on document fraudemphasize the importance of leveraging AI-based document verification systems that can detect even the most sophisticated forgery techniques.

Example scenario:

 A small e-commerce startup selling high-end electronics receives a large order. They perform a standard identity check on the buyer’s ID and everything appears legitimate. However, the buyer’s ID is a fake and generated by AI. The goods are shipped, and the business never receives payment.

This type of fraud can be devastating for an SMB, leading to both revenue and product loss, and making it difficult for the small business to recover. Additionally, it can create negative word of mouth, further damaging the business.

Learn more about how AI impacts identity verification in our article on adapting to evolving fraud tactics.

2. Deepfakes and virtual impersonations

AI can now create “deepfakes,” which are videos or audio files that mimic real people with frightening accuracy. Fraudsters use this technology to impersonate business executives, vendors, or even customers.

AI can generate highly realistic fake videos or audio clips, known as deepfakes, which are used in social engineering attacks or to impersonate executives and business partners. In a world where remote work and virtual meetings have become commonplace, deepfakes are an increasing concern. 

Natural language processing (NLP) plays a crucial role in detecting deepfakes and virtual impersonations by analyzing unstructured data, such as emails and chat transcripts, to flag suspicious communications and verify identity-related documentation.

According to a recent Deloitte study, the financial sector, already a prime target for such frauds, reported a 700% increase in deepfake incidents in 2023 alone.

Veriff’s deep dive on deepfakes highlights how these tools are being used to manipulate not just social media, but also internal business communications, making them a significant threat to SMBs.

Example scenario:

Your startup is finalizing a deal with a key partner. You receive a video call from what appears to be the partner’s CEO, authorizing the transfer of funds to a new account.

But the person on the call isn’t the CEO, it’s a fraudster using a deepfake video to convince you to send the money to a fake account. Once the funds are transferred, the fraudster disappears. 

Want to know more about deepfakes? Read our deep dive on deepfakes and their impact on credit card fraud and prevention.

3. Bypassing traditional security

AI also helps criminals exploit gaps in traditional security measures. For example, AI can be used to study login attempts, learn password patterns, and detect vulnerabilities in outdated systems.

Anomaly detection plays a crucial role in identifying unusual patterns and behaviors that signify potential fraud. By often leveraging automated systems that learn and adapt to new, new and varied data, businesses can ensure that fraudulent activities are effectively flagged and investigated.

Example scenario:

A hacker uses an AI algorithm to “learn” the login patterns of a small business’s website. The algorithm bypasses two-factor authentication by predicting the code generated by the system. This allows the hacker to access the company’s sensitive data, leading to data breaches or account takeovers.

Startups and SMBs often rely on basic fraud detection systems that aren’t designed to handle these advanced AI threats. Without AI-driven, fraud detection systems and prevention tools, businesses may not even realize they’ve been compromised until it’s too late.

Business challenges SMBs face in preventing AI-driven fraud

Trust and reputation

Startups and small businesses rely heavily on trust. A single incident of fraud can damage your reputation, leading to lost customers and decreased revenue. And this can have a devastating impact on your company. If customers perceive your business as insecure, they may hesitate to work with you or make purchases. In a world where AI-generated content is widely available and capable of creating realistic visual and audio content, seeing is no longer believing. Consumers can no longer trust their own eyes and instincts when discerning real news from fake news. In fact, according to a recent McAfee study:

• Nearly 7 of 10 (66%) people are more concerned about deepfakes than they were a year ago.
• More than half (53%) of respondents say AI has made it harder to spot online scams.

Lost revenue

SMBs and startups are generally operating on tight margins, that’s why the financial loss from a fraud incident can be intimidating. Whether it’s losing thousands in a single fraudulent transaction or facing legal costs from a data breach, the financial impact of fraud can push a small business to the brink of closure. AI and machine learning technologies can enhance the accuracy and efficiency of detecting fraudulent transactions, helping identify unusual patterns and behaviors in transaction data to mitigate the rising sophistication of fraud attempts. The Deloitte Center for Financial Services estimates that generative AI email fraud losses could total about US $11.5 billion by 2027 in an “aggressive” adoption scenario.

Increased complexity

SMBs don’t typically have the in-house expertise or time to manage complex fraud prevention systems. Solutions need to be simple to implement and manage, without overwhelming small teams with extra tasks. Approximately 60% of financial institutions have adopted at least one form of AI, and 1 in 4 have adopted machine learning for fraud detection, according to a recent McKinsey report.

How can SMBs guard against AI fraud?

While AI-driven fraud is growing, there are practical steps small businesses can take to protect themselves and prevent fraud, by enhancing their fraud prevention capabilities. Here’s how:

Invest in AI-powered identity verification

Traditional identity checks aren’t enough anymore. AI-powered solutions like Veriff’s self-serve Identity Verification can automatically detect fake IDs and suspicious activity in real-time. These tools use machine and deep learning algorithms to analyze large volumes of data, identify patterns and anomalies indicative of fraudulent activity, and continuously improve their accuracy through real-time data processing and ongoing training.

For global banking, McKinsey estimates that AI technologies could potentially deliver up to $1 trillion of additional value each year.

Why it matters: instead of relying on manual verification or basic software, AI-powered systems can identify fraud and suspicious transactions faster and more accurately, reducing the chances of costly mistakes.

Train your team on fraud prevention

Your team is your first line of defense against fraud. Regular training sessions on how to recognize fraud attempts, phishing emails, and other social engineering tactics can prevent costly mistakes.

It is crucial to distinguish legitimate transactions from fraudulent ones, as AI systems mistakenly flag legitimate transactions as they detect fraudulent activities, causing customer frustration and harming business relationships.

Include regular training: SMBs should implement easy-to-understand training for employees, especially around recognizing suspicious emails, identity theft red flags, and deepfake-related scams.

Monitor fraudulent transactions and behavior patterns

Set up systems that monitor account activity and flag unusual or fraudulent behavior by analyzing transaction data. For example, a sudden change in shipping addresses, login attempts from unusual locations, or requests for large sums of money should raise red flags.

According to a McKinsey study, more or less half of KYC-review time is spent on transaction analysis.

Visual aid suggestion: use a graph or chart here to display the types of red flag activities that should trigger a fraud check, such as sudden account changes, unusually large transactions, or login attempts from foreign locations.

Invest in fraud protection solutions tailored for SMBs

For startups and SMBs, one of the biggest challenges is finding affordable, easy-to-use payment fraud and prevention tools. Veriff’s self-serve identity verification solution is designed to meet these needs. It offers:

• Quick setup. No need for a large IT team to implement it.
• AI-Powered protection. Automatically detects fake IDs and documents, as well as suspicious behavior patterns, using advanced machine learning models.
• Scalability. Whether you’re verifying a few users or hundreds, Veriff grows with your business.
• Cost-effective. Tailored pricing plans for startups and SMBs with smaller budgets.
  
• By using Veriff, small businesses can gain access to the same powerful fraud prevention tools used by larger companies, without the hefty price tag or complicated setup.
• Explore how Veriff’s AI-driven solution can help protect your small business from fraud by checking out the self-serve plans here.

Conclusion: taking action to stay safe

In an increasingly complex digital landscape, small businesses and startups face significant challenges in protecting themselves from the rising threat of AI-driven fraud. Limited resources, outdated security methods, and lack of regulatory clarity further complicate their efforts. However, by leveraging advanced AI-powered tools like identity verification systems, regularly training staff on fraud prevention, and monitoring transactional behaviors for anomalies, SMBs can mitigate these risks.

AI has transformed the capabilities of both businesses and fraudsters, making it crucial for SMBs to adopt proactive and flexible security strategies tailored to their needs. By investing in scalable and effective fraud protection solutions, companies can not only reduce their vulnerability to fraud but also build trust, maintain their reputation, and focus on growing their business with confidence. Remember, staying ahead of fraud requires a combination of technology, vigilance, and continuous improvement.