Screen out Fraud Before KYC and Account Funding

Verisoul detects the most common and costly fraud targeting financial services, including synthetic identities, fake and automated sign-ups, account takeovers, proxy- and VPN-based abuse, location spoofing, bonus and referral abuse, mule activity, and repeat fraudsters.

Verisoul is built to protect the entire financial risk flow — from pre-KYC screening to login and account monitoring — by combining identity intelligence, device forensics, network analysis, behavioral signals, and consortium data into a single real-time risk decision.

Verisoul detects high-risk users before KYC is triggered, allowing financial platforms to avoid unnecessary verification costs.

During onboarding, Verisoul evaluates:

• Identity signals associated with synthetic or fake users
• Email and account patterns linked to automated sign-ups
• Device and network behavior indicating farms, emulators, or scripted activity
• Early abuse signals tied to bonus and referral exploitation

This allows teams to block or deprioritize high-risk users early, reserving KYC spend for legitimate customers and improving onboarding efficiency.

Verisoul detects account takeovers by identifying abnormal login behavior and identity changes that indicate compromised accounts.

ATO detection includes:

• Sudden device or environment changes inconsistent with prior behavior
• Impossible travel between login sessions
• Proxy, VPN, or remote access usage during sensitive actions
• Behavioral anomalies that suggest credential stuffing or scripted access

These signals allow teams to stop takeovers before funds move or accounts are misused, without locking out legitimate users.

Verisoul detects mobile proxies, residential proxies, VPNs, and location spoofing commonly used to evade FinTech controls.

Detection techniques include:

• Encrypted traffic pattern analysis to flag proxy tunneling and abnormal packet flows
• Middleman and relay detection, identifying intermediary infrastructure intercepting sessions
• True-location inference, triangulating routing paths, device behavior, and session context to determine actual user geography
• Environmental mismatch analysis, including inconsistencies in language, fonts, keyboard layout, time zone, and OS region

These techniques are critical for detecting cross-border fraud, mule networks, and high-risk login attempts that traditional IP checks miss.

Verisoul prevents bonus and referral abuse by identifying coordinated clusters of accounts created to exploit incentives.

Cluster detection includes:

• Device and network reuse across multiple sign-ups
• Behavioral similarity across onboarding and usage
• Identity overlap between seemingly separate users
• Longitudinal tracking across campaigns and promotions

This allows FinTech teams to stop promotion abuse before payouts, protecting growth spend and preventing skewed metrics.

Consortium intelligence allows Verisoul to identify fraud patterns and identities that have appeared across multiple customers, rather than relying on a single platform’s data.

This includes:

• Detection of repeat fraudsters who rotate apps, devices, or accounts
• Identification of known abuse infrastructure used across FinTech products
• Early warning signals for emerging fraud techniques

Consortium intelligence helps financial platforms stop fraud earlier and with higher confidence than standalone tools.

Yes. Verisoul reduces false positives by analyzing live behavior and context, rather than relying on static rules or IP reputation alone.

Static approaches often misclassify:

• Mobile users
• International customers
• Privacy-forward browsers
• Shared or corporate networks

By using probabilistic identity resolution and contextual scoring, Verisoul allows teams to block more fraud while approving more legitimate users.

No. Verisoul operates passively and invisibly by default.

All detection runs in real time using device, network, and behavioral signals, allowing teams to block, step up, or monitor users without forcing captchas or unnecessary interruptions during onboarding or login.

Verisoul differs from legacy tools by focusing on early risk detection and signal quality, not just verification.

• KYC vendors verify identity after cost is incurred
• IP-based tools struggle with proxies and location spoofing
• Rule-heavy systems generate false positives and friction

Verisoul acts as a pre-KYC and ongoing risk layer, combining identity, device, network, behavior, and consortium intelligence to improve decisions across the entire customer lifecycle.

Yes. Verisoul works across mobile apps and desktop web, including native iOS and Android apps as well as browser-based FinTech experiences.

Verisoul is designed for mobile-first and cross-platform financial products, and supports real-time fraud detection during onboarding, login, and sensitive account actions without degrading performance or user experience.

Mobile and desktop deployment includes:

• Native iOS and Android SDKs for FinTech apps
• Web and browser-based integrations for desktop onboarding and account access
• Consistent identity and risk signals across platforms, even when users switch devices

This allows FinTech teams to apply one unified risk layer across all user touchpoints.

Verisoul detects advanced mobile and device-level abuse signals that traditional FinTech tools often miss.

These signals include:

• App tampering and runtime manipulation, including hooking frameworks and instrumentation tools
• App cloning and repackaged applications used to bypass controls
• Direct integrations with Apple and Google to validate app integrity and confirm devices have not been compromised
• Detection of emulators and virtualized environments commonly used in fraud and account farming
• Remote access and automation tooling, including screen control and scripted interaction
• Compromised device indicators, such as rooted or jailbroken environments

These signals are combined with identity, network, and behavioral context so decisions are high-confidence and low-friction, even in high-risk financial workflows.