Financial crime is connected.
Detection should be too.
RAQB is building intelligent financial crime technology that analyzes relationships across transactions and entities to help uncover complex suspicious activity.
Built in Kuwait. Designed for financial institutions.
Traditional monitoring sees transactions.
Financial crime happens across relationships.
Financial crime rarely exists in a single transaction. Suspicious activity can emerge through sequences of transfers, related accounts, entities and behavioral patterns that become meaningful only when viewed together.
Isolated rules on single transactions.
- Fixed thresholds and static scenarios
- Each alert reviewed on its own
- High false positive volume
Relationships across the financial network.
- Behaviour analysed across linked entities
- Patterns emerge from the whole structure
- Investigators receive context, not noise
A single event, checked against a fixed threshold, in isolation.
Signals read together, so a pattern becomes visible before any single rule fires.
Understand the network, not just the transaction.
RAQB explores network-based methods for financial crime detection, combining behavioral analytics with graph and hypergraph intelligence.
- Transactions
Individual payments and transfers are observed.
- Relationships
Accounts, customers and entities are linked together.
- Patterns
Repeating structures reveal coordinated behaviour.
- Intelligence
Risk context is assembled for the investigator.
Turning financial crime research into technology.
RAQB is emerging from research into applying artificial intelligence and network-based learning to anti-money laundering and financial crime detection.
Advanced AML and network research
Graph and hypergraph intelligence
Financial crime detection technology
Solutions for financial institutions
Our work is being developed within a research environment focused on translating advanced data science and AI research into practical applications.
A new intelligence layer for financial crime teams.
Identify suspicious transaction behavior and financial patterns.
Understand relationships between customers, accounts, transactions and entities.
Give investigators clearer context around suspicious activity.
RAQB is exploring AI-assisted investigation capabilities that help analysts understand alerts, relationships and transaction patterns more efficiently.
The final decision always remains with the investigator.
Built around connected financial data.
Behavioral and risk pattern analysis.
Relationship analysis across financial networks.
Modeling complex interactions involving multiple entities and transactions.
Our research explores how these approaches can complement traditional AML monitoring rather than simply replacing existing controls.
Research shouldn't stop at publication.
Important advances in AI and financial crime research often remain within academic environments.
Take promising financial crime research and turn it into technology that institutions can actually use.
Building financial crime intelligence from Kuwait for the region.
We aim to develop research-driven RegTech technology for financial institutions in Kuwait and across the GCC.
Research-driven. Industry-focused.
RAQB is a Kuwait-based RegTech venture focused on translating advanced research in artificial intelligence, financial networks and anti-money laundering into practical financial crime technology.
Interested in what we're building?
Whether you're a financial institution, researcher, industry expert or potential partner, we'd like to hear from you.