The operators winning in 2026 have stopped treating security and signup rates as a trade-off.
Every operator knows the tension. Regulators demand stricter identity checks. Players demand instant access. And somewhere between those two forces, your revenue leaks out.
The numbers are brutal. Across regulated industries, an estimated 63% of potential customers never finish signing up. In iGaming specifically, the identity verification step (document capture and biometrics) is consistently the highest drop-off stage in the entire funnel. One study found that when users face more than three verification steps, abandonment rates jump by 60%. On mobile, where most players now sign up, the effect is even worse.
Meanwhile, fraud isn't slowing down. Deepfake-related fraud attempts have surged 2,137% since 2022. In 2025, one in every 20 identity verification failures was linked to deepfake usage. Synthetic identities, AI-generated documents, and coordinated multi-account schemes are becoming the standard operating procedure for organized fraud rings.
Investing in better KYC is table stakes. The hard part is doing it without destroying the signup experience that drives your business.
Here's what the best operators are doing differently in 2026.
The real cost of friction (it's higher than you think)
Most operators measure KYC performance by pass rates and compliance outcomes. Very few measure the revenue they never earned because a player gave up on slide four of a seven-step verification flow.
Consider the math. In competitive European iGaming markets, CPA deals typically range from €100–400 per depositing player depending on the geography and channel. But that's the cost for a completed acquisition, a player who made it all the way through signup, KYC, and first deposit. Now factor in that your KYC flow drops 40–50% of users who were already motivated enough to start verifying. That means your effective cost per acquisition doubles: what should be a €200 CPA becomes €400, because half the traffic you already paid to attract never converts. You're losing players who clicked, entered their details, and were ready to play, only to be stopped by a clunky verification process.
Traditional KYC flows typically require 10–15 discrete user actions: selecting a country, choosing a document type, positioning the document, capturing front and back, retaking failed captures, selecting a selfie mode, performing gestures for liveness detection, and so on. Each click is an exit opportunity. Each retry is a moment of frustration. Each confusing instruction is a reason to close the tab and visit a competitor.
The operators who have solved this understand something fundamental: the number of steps in your verification flow directly correlates with your cost of acquisition. Reducing steps improves UX and changes the economics of your entire growth model.
Why "good enough" KYC is getting operators burned
On the other side of the equation, the fraud landscape has shifted so dramatically that legacy verification approaches are becoming liabilities.
Deepfakes now account for roughly 40% of all biometric fraud attempts globally. Gartner projects that by 2026, 30% of enterprises will no longer consider standalone identity verification solutions reliable in isolation. Fraud-as-a-service platforms have industrialized what used to require technical sophistication. Today, anyone with a credit card can access tools that generate convincing synthetic documents and videos.
For iGaming operators, the consequences are acute. Multi-accounting (a single person creating dozens of accounts to exploit bonuses) is rampant. Document forgery has become nearly undetectable to basic OCR systems. And presentation attacks where fraudsters hold a phone screen up to the camera showing someone else's photo can bypass simple selfie checks entirely.
The regulatory response is equally aggressive. The UK Gambling Commission now requires identity and age verification before a player can deposit or access free-to-play content without any grace periods. Germany mandates instant KYC at signup, integrated with the centralized OASIS exclusion database. Brazil's new betting framework, active since January 2025, enforces strict identity controls and is banning credit card gambling entirely from April 2026.
Operators who rely on basic document checks and gesture-based liveness are exposed on both fronts: they lose legitimate players to friction and let fraudulent ones through.
The innovations that actually move the needle
The verification technologies making the biggest impact in 2026 share a common principle: they push complexity to the machine, not the user. Here's what that looks like in practice.
Zero-click document capture
The single biggest source of friction in traditional KYC is document scanning. Users are normally asked to select their country, choose their document type, position the card within a frame, hold steady, and hope the capture succeeds on the first try. It rarely does.
The most advanced systems now handle all of this automatically. The camera activates, the system detects the document type and issuing country without any user input, captures the image when quality thresholds are met, and extracts data — all without the user pressing a single button. No dropdowns. No retakes. No confusion about which side to photograph.
This eliminates what is typically 4–6 user actions from the flow and removes the most common failure point: bad-quality captures that trigger retries. When you consider that 30% of users leave registration the moment they're asked to upload an ID document, removing every unnecessary interaction from this step has an outsized impact on completion rates.
Automatic document detection and classification
Related but distinct: the ability to automatically identify what type of document a user is presenting — passport, national ID card, driver's license, residence permit — without requiring them to select from a list.
This might seem like a small UX improvement, but it eliminates a surprisingly common drop-off trigger. Users in many European jurisdictions carry multiple valid ID types and don't always know which one the platform expects. Forcing them to choose adds cognitive load. Getting it wrong triggers an error. Both create exit points.
Systems that support automatic classification across 14,000+ document types from 190+ countries can accept whatever the user has in hand and process it correctly. The user's only job is to point their camera.
Passive liveness detection
Liveness checks (confirming a real human is behind the camera, not a photo or a video) are essential for fraud prevention. But the way most systems implement them creates massive friction.
The system analyzes texture, depth, and micro-movement in real time. No instructions needed.
Traditional active liveness requires users to perform gestures: turn their head left, then right, look up, blink, smile. Each instruction adds time, confusion, and opportunities for failure. Users in low-light environments fail. Users with certain disabilities fail. Users who simply don't understand the instruction in their language fail. And every failure means a retry or an abandonment.
Passive liveness detection analyzes the camera feed in real time — examining texture, depth, and micro-movement patterns — without requiring any deliberate user action. The user looks at the camera. The system confirms they're a real, physically present person. Done.
This single change typically removes 3–5 steps from the verification flow, while actually increasing fraud detection accuracy. The algorithms catch presentation attacks (printed photos, screen replays) and deepfakes (AI-generated face swaps, virtual cameras, browser injections) more reliably than gesture-based systems, because fraudsters have become adept at mimicking head turns and blinks.
Built-in deepfake detection
This is the capability most operators are still underestimating. With deepfake incidents increasing 19% in Q1 2025 alone (more than the entire year of 2024), the threat to identity verification systems is existential.
Modern deepfake detection works at multiple layers: analyzing the video stream for artifacts of AI generation, detecting virtual camera software and browser injection tools, identifying inconsistencies in lighting, micro-expressions, and skin textures that synthetic media struggles to reproduce. The best implementations run these checks as part of the same liveness step — no additional user action required.
For operators, this means the difference between catching sophisticated fraud attempts in real time and discovering them weeks later through costly manual reviews or, worse, through regulatory fines
Full-funnel analytics
Here's the capability that ties everything together: the ability to see exactly where users drop off in your verification flow and why.
Most KYC providers give operators a binary outcome — pass or fail. They don't show that 22% of users abandoned at the document type selection screen, or that retry rates spike for German driver's licenses on Android devices, or that mobile users in the UK complete verification at half the rate of desktop users.
Without this data, optimization is guesswork. With it, operators can make targeted changes; adjusting flow order, enabling specific document types, tweaking camera quality thresholds and measure the revenue impact of each change.
The operators who treat KYC as a product problem (not just a compliance checkbox) are the ones systematically outperforming on both conversion and fraud metrics.
What a modern flow actually looks like
Put these innovations together and the difference is stark.
A legacy verification flow might look like this:
Select country → Select document type → Position document → Capture front → Capture back → Review scan → Select selfie mode → Read instructions → Perform gesture 1 → Perform gesture 2 → Perform gesture 3 → Wait for processing → Complete.
That's 12–15 actions. Average time: 2–4 minutes. Drop-off: 40–60%.
A modern flow:
Point camera at ID → Look at camera → Done.
That's 2 actions. Average time: under 30 seconds. The system handles document detection, data extraction, quality validation, liveness confirmation, deepfake screening, and compliance checks — all behind the scenes.
Same regulatory outcome. Radically different business outcome.
The bottom line
The operators who will win in 2026 and beyond are the ones who reject the premise that compliance and conversion are in tension. The technology exists today to verify identities faster, catch fraud more accurately, and let players start playing sooner — all at the same time.
The question is whether you're building your verification stack around what regulators require (the minimum) or around what your business needs to grow (the maximum conversion at the lowest fraud rate, with full compliance as the baseline, not the ceiling).
If your KYC process still asks users to choose their document type from a dropdown, or performs liveness checks through head gestures, or lacks real-time deepfake detection, or can't tell you exactly where and why users abandon — you're paying a tax on every single player who visits your platform.
And in a market where every percentage point of signup conversion translates directly to revenue, that's a tax you can't afford.
Checkin.com provides identity verification, biometrics, and KYC solutions for regulated industries. Our platform supports zero-click document capture, passive liveness detection, built-in deepfake protection, and full-funnel conversion analytics across 15,000+ document types in 190+ countries. Get a free trial to see it in action.
Sources
- Sardine, "11 Strategies to Improve KYC Conversion Rates" — sardine.ai/blog/kyc-conversion-rates
- Wndeer, "How to Reduce Drop-Offs in the KYC Process" (citing Jumio and Onfido data) — wndeer.com/how-to-reduce-drop-offs-kyc-process
- Didit, "How to Optimize the KYC Process to Enhance User Experience" (citing Deloitte study) — didit.me/blog/how-to-optimize-the-kyc-process-to-enhance-user-experience
- Keepnet Labs, "Deepfake Statistics & Trends 2026" — keepnetlabs.com/blog/deepfake-statistics-and-trends
- SQ Magazine, "Deepfake Statistics 2026: The Hidden Cyber Threat" — sqmagazine.co.uk/deepfake-statistics
- Deepstrike, "Deepfake Statistics 2025" (citing Gartner projection) — deepstrike.io/blog/deepfake-statistics-2025
- Veriff, "The Growing Threat of Deepfakes in Financial Services" — veriff.com/identity-verification/the-growing-threat-of-deepfakes-in-financial-services-and-why-a-trust-infrastructure-is-the-future
- ARGOS Identity, "2025 iGaming Regulatory Trends (Identity and Age Verification)" — blog.argosidentity.com/70052
- Affnook, "CPA in iGaming: A Profitable Affiliate Marketing Model" — affnook.com/cpa
- Business of Apps, "CPA Affiliate Networks (2025)" — businessofapps.com/affiliate/cpa
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