Quadible builds fraud prevention and financial crime tools for banks, and for betting and iGaming operators. Its tools are for the security, anti money laundering (AML) and fraud teams who have to tell real customers from impostors and work through the alerts that follow.
The problem has two ends: stolen credentials let criminals into genuine accounts or open fake ones, and the alerts that result pile up faster than analysts can investigate them. Quadible works on both, while keeping the final decision with the institution’s own staff.
At A Glance
| Vendor | Quadible (Quadible Ltd) |
|---|---|
| Category | Behavioural authentication and AI fraud and AML investigation |
| Identities covered | Customer users of banking, betting and iGaming services, and their devices |
| Deployment | Cloud or the customer’s own environment |
| Agentic AI | AI Investigators for AML and fraud teams |
| Certifications | ISO 27001, ISO 22301, GDPR with EU data storage |
| Market classification | Workforce IAM |
What Quadible Does
Stolen passwords and one time codes no longer prove that a session belongs to the account holder, and fraud teams are buried in alerts. Quadible’s approach is to judge the person, not the credential: how someone interacts with an app says more about who they are than a code they typed. Checks run continuously in the background, and extra friction appears only when risk rises. Further down the line, AI agents prepare investigations for analysts inside the institution’s existing infrastructure and workflows rather than replacing them, with every conclusion traceable to its evidence.
Products
Behavioural Authentication
Behavioural Authentication scores risk continuously from how a user types, swipes, moves and interacts, combining more than 14 behavioural traits with device, location and network signals. Step up checks such as one time passwords appear only when the score calls for them. It targets two kinds of fraud. Account takeover is blocked when someone uses stolen credentials to get into a genuine customer’s account, and multi account fraud is caught when users open several or fake accounts to exploit promotions or bonuses. Lightweight SDKs for iOS, Android and web collect the signals.
AI Investigators
AI Investigators are agents that build case files for AML and fraud teams and draft reports in the bank’s own templates, with every finding linked to its source evidence. There are two:
| AML Investigator | Prioritise, build context, investigate and report. |
|---|---|
| Fraud Investigator | Prioritise, verify user and device signals, trace funds and connections, and respond with recommended actions. |
How It Works
| Component | What it does |
|---|---|
| SDKs | Behavioural Authentication is embedded in iOS, Android and web applications, where it gathers interaction and device signals. |
| Hosting | Behavioural Authentication runs in the cloud or in the customer’s own environment, under the customer’s permissions and audit trails, with data stored and processed in the EU. |
| Investigator deployment | AI Investigators run inside the bank’s environment on the bank’s own model endpoint. Registry lookups send only company names, never customer data. Alerts arrive from AML monitoring and fraud detection platforms, and the agents draw on core banking, KYC, CRM and case management systems. |
| Controls | Analysts approve sensitive actions, recommendations and final reports. Tool calls, findings and report figures can be audited, access goes through SSO, permissions and access lists, and behavioural regression tests run before any change reaches analysts. |
Identities And Systems Covered
| Customer users | End users of banking, betting and iGaming services, authenticated from behavioural signals. |
|---|---|
| Devices | Device, location and network signals, with research work on device fingerprinting. |
| Applications | IOS, Android and web applications. |
| Financial crime data | Alerts, transactions and connections examined during AML and fraud investigations. |
Agentic AI Capabilities
Autonomy Levels
Each stage of the AI Investigators workflow is marked as either autonomous or an analyst-guided copilot. Prioritisation runs autonomously in both agents, while the investigation stages work alongside an analyst, who approves sensitive actions and signs off each report.
Knowledge Base
The agents learn from procedures, typology documents, emails, team chats and closed cases. No knowledge record is used until the team has approved, edited or rejected it, which keeps the agents tied to the institution’s own practice.
Company Background
| Incorporated | 11 December 2015, as Quadible Ltd in the United Kingdom. |
|---|---|
| Founders | Dr Niklas Palaghias (CEO) and Georgios Sachpatzidis. |
| Collaborations | Samsung, Microsoft, Visa, Medtronic and the University of Surrey. |
| Research | 11 research projects, including Horizon Europe and Horizon 2020 programmes. |
Note: This overview is compiled from Quadible’s publicly available information as of 4 November 2026. It is provided for information only. NHI Mgmt Group does not endorse any vendor, and nothing on this page represents the opinions of NHI Mgmt Group.