The mass adoption of artificial intelligence is changing how businesses approach KYC. We’ve entered an era of AI vs AI.

On one side, the technology is being weaponized by fraudsters. Multiple research pieces show that more than 50% of fraud is now driven by artificial intelligence and hyper-realistic impersonations.

But at the same time, AI powers automated fraud detection and more accurate identity verification than ever before. A report from Asset Finance states that 78% of global business and technology leaders reported improvements in fraud detection and risk management following the implementation of AI.

This new wave of AI-driven fraud is pushing businesses and their compliance teams to adopt smarter, AI-based fraud detection and fraud prevention solutions capable of spotting anomalies that traditional tools simply miss.

In this educational piece, we explore the most common AI-driven fraud techniques and explain how AI fraud detection solutions like Allpass.ai can help businesses improve the quality of customer due diligence.

The Rise of AI-Powered Fraud

A 2025 report by Entrust found that the industries hit hardest by identity-fraud attacks are all within financial services, with cryptocurrency platforms seeing fraudulent onboarding attempts jump from 6.4% to 9.5% in a single year, followed closely by lending and traditional banking.

The problem isn’t confined to one market, either. Between July and August 2025, Akamai observed that over half of all AI bot activity (54.9%) targeted organisations in North America, with EMEA (23.6%) and APAC (20.2%) also facing significant waves of automated abuse.

The pattern is clear: AI-enabled fraud is global, but it concentrates especially where money moves quickly and digital onboarding is the norm. To understand how to fight AI-powered fraud, we first need to understand what it looks like.

Deepfake Impersonation

A deepfake is basically a computer-generated video or audio clip that shows a person doing or saying something they never did. Fraudsters use AI-generated videos to slip through checks and open accounts under identities that aren’t theirs. A single deepfake account can be used to move stolen funds, apply for credit, commit chargeback fraud, or become the entry point for an AML violation. The financial and reputational risks start the moment a synthetic face is onboarded into your platform.

Synthetic Identities

If deepfakes are about impersonating someone, synthetic identities are about creating a persona that doesn’t exist. These profiles often look more legitimate than real customers. They have no negative credit history, no flags, and no obvious red flags. When they get through onboarding, they behave like perfect clients until the moment they default, disappear, or start laundering money.

The financial damage here is silent and long-term. Businesses lose money through unpaid loans, fraudulent transactions, and increased regulatory exposure. Traditional KYC processes simply cannot detect a person who never existed.

AI-Enhanced Document Forgery

AI has turned document forgery into a cheap, scalable service. Fraudsters can generate extremely realistic passports or IDs that will pass basic template checks and superficial human review. If your system can’t detect digital manipulation, pixel-level inconsistencies, or deviations in document structure, you are essentially approving customers who don’t exist.

The consequence is direct financial exposure: fraudulent loans, fake accounts used for scams, compliance penalties for weak KYC controls, and a dramatic increase in operational workload. Businesses that rely on manual review or outdated OCR end up spending more on remediation than on financial crime prevention.

Bot-Driven Onboarding Attacks

This technique involves automation. Fraudulent actors deploy botnets and scripted agents to overwhelm onboarding systems with waves of fake applications. Some bots are powered by machine learning models that adapt to form layouts, bypass rate limits, and simulate human behaviour.

This approach allows criminal groups to test verification systems at scale, probing for weak spots. Once a vulnerability is identified, the bots exploit it repeatedly, creating dozens or even hundreds of fraudulent accounts.

Voice Cloning

Voice cloning is a type of deepfake. Just like AI can copy a person’s face, it can also clone the person's voice. With only a few seconds of someone’s voice, an AI tool can create a copy that sounds almost identical. A fraudster can then use that fake voice to call customer support, pretend to be the account owner, and request access or changes.

In one high-profile incident, Arup, a UK engineering firm, lost around $25 million after fraudsters used a deepfake video call impersonating the company’s senior manager to authorize transfers. While it doesn’t have anything to do with KYC, it shows the scale of impact a deepfake can have on a business.

How AI-based Fraud Detection Can Help Protect Your Business

AI has changed how fraudsters operate; however, fraud detection software is adapting just as quickly. Today, AI can be used to strengthen many steps of the onboarding process. The most common AI-enhanced features on KYC software are:

AI-Powered Document Verification

One of the biggest advantages of modern KYC tools is their ability to verify documents with far greater precision.

For example, Allpass.ai’s document-verification engine is trained on over 14,000 types of identity documents from more than 250 countries and territories. This includes standard passports and IDs, as well as more complex documents where the text is handwritten rather than typed, something traditional OCR struggles with.

AI helps the system:

• read text accurately in difficult conditions;

• match document layouts to real templates;

• detect inconsistencies in fonts, colors, or security features;

• spot subtle signs of digital manipulation;

• identify fraud even when the image “looks fine” to a human reviewer.

For businesses, this means far fewer manual checks and far more reliable onboarding decisions.

Liveness Detection & Facematch

A liveness check is a biometric security step that confirms a real human is present during verification. In Allpass.ai, this can take different forms depending on the level of security and friction you choose.

The one-shot check offers the simplest user experience: the user takes what feels like a single selfie. Behind the scenes, AI analyzes several frames, micro-movements, lighting behavior, and texture patterns to determine whether the face is genuine. This approach keeps onboarding smooth, though it provides a lighter layer of protection compared to more advanced options.

For higher-risk scenarios, Allpass.ai supports 3D and active liveness, which require the user to perform specific movements. These checks allow the system to analyze depth, facial structure, and motion cues in more detail, making it much harder for spoofing attempts, replay attacks, or high-quality deepfakes to pass.

When combined with facematch, which compares the selfie to the document photo, liveness detection becomes a strong defense against deepfake videos, face-swap attacks, pre-recorded clips, and synthetic identities. Older verification flows can often be fooled by realistic fakes, but AI-powered liveness makes impersonation significantly more difficult — without adding unnecessary friction for legitimate users.

Risk Scoring

ID verification and liveness tell you what was submitted and who is in front of the camera. Risk scoring tells you how trustworthy the entire verification attempt is.

Risk scoring often combines a mix of rules-based systems and machine learning for fraud detection. It uses signals like document quality, selfie consistency, device behaviour, submission patterns, and more to calculate a confidence score. This allows the system to classify users as:

• Low risk → safely auto-approved.

• Medium risk → sent to manual review.

• High risk → automatically rejected.

With AI-powered risk scoring, you don’t have to waste time and money conducting deep investigations on every customer. The scoring system acts as a gatekeeper. If a new applicant scores high during the initial KYC process, the system flags them immediately for EDD or allows rejecting the relationship outright.

Will AI Replace Compliance Teams?

No, but it will take over the parts of KYC that machines can do better than humans.

AI isn’t here to replace compliance teams. It’s here to replace the slow, manual, repetitive tasks that make KYC costly, inconsistent, and vulnerable to human error. Tasks like:

• reading documents;

• extracting data;

• checking for tampering;

• matching faces;

• confirming liveness;

• assigning risk scores.

These are things AI already does faster, more accurately, and at scale, which is why AI-powered KYC is becoming the standard rather than a nice-to-have.

Hybrid Fraud Prevention Model Is the Way to Go

Humans are still essential. AI cannot fully understand intent, context, or nuance. That’s why the strongest KYC today combines AI-driven automation with human oversight.

Here are a few practical ways businesses can maintain that balance:

1. Make AI Your First Line of Defense

Use AI-powered KYC verification to handle the repetitive, time-consuming checks: document authenticity, liveness, deepfake detection, and ongoing monitoring. Let technology do the heavy lifting, so your team can focus on the cases where human insight matters.

2. Invest in Training for Compliance Teams

Teams need ongoing training in common fraud patterns, the latest techniques, etc. The more informed your team is, the more effectively they can spot things even AI may miss.

3. Create Clear Escalation Paths

Medium- and high-risk cases should never be left to guesswork. Define workflows that allow analysts to review suspicious attempts, request additional documentation, or escalate highly unusual patterns to specialists.

4. Regularly Review and Refine Rules

AI helps detect anomalies, but human teams can provide context. Use their insights to fine-tune rules, adjust thresholds, and guide future improvements.

See What AI-Powered Onboarding Looks Like With Allpass.ai

Allpass.ai brings automation to the parts of KYC that traditionally consume the most time

• document checks;

• liveness verification;

• face matching;

• ongoing AML monitoring.

Instead of slowing down as your business grows, your onboarding becomes faster, more secure, and easier to manage.

AI handles the repetitive steps. Your team focuses on the decisions that matter. And your users get a smoother, more modern verification experience.

If you’re ready to upgrade to a faster and more reliable KYC process, book a demo today. You’ll see immediately how automation can transform your onboarding flow.