AI built into the financial infrastructure
BTS does not position itself as an AI company. We are a FinTech infrastructure company that has integrated AI capabilities directly into the payment platforms, terminal estates, and banking channels we already operate — so banks get AI-powered outcomes without adopting a separate AI stack.
Our AI positioning
- BTS is a FinTech infrastructure company — not an AI startup.
- Our AI capabilities enhance the payment and banking platforms we already operate.
- Every AI component is designed to run inside the bank's own infrastructure perimeter.
- Human oversight is a non-negotiable requirement, not an optional add-on.
- We track emerging MENA central-bank guidance and align before it becomes mandatory.
The AI Financial Ecosystem
Each capability runs inside the BTS platform stack — in the transaction path, the terminal management layer, or the customer-facing channel.
Capability 01
AI Orchestration
BTS AI orchestration layer coordinates multiple AI models and decision engines across the transaction path — routing requests to the right model based on context, aggregating outputs, and enforcing policy guardrails. Banks get a consistent, governed AI interface without managing a fragmented set of point solutions.
Key capabilities
- Unified model registry and versioning across all AI capabilities
- Context-aware routing between models based on transaction type
- Policy enforcement layer: thresholds, overrides, and escalation rules
- Latency-aware inference: on-device, edge, or data-centre deployment
- Full audit trail of model invocations, inputs, and outputs
Capability 02
Behavioral Intelligence
Passive risk scoring built into the transaction path using device fingerprinting, behavioral biometrics (keystroke and touch dynamics), session signals, and velocity patterns. The model raises risk scores silently — step-up authentication is triggered only when thresholds are crossed, reducing friction on legitimate transactions while catching account-takeover and card-not-present fraud.
Key capabilities
- Device fingerprinting and session continuity scoring
- Keystroke dynamics and touch-pattern behavioral profiling
- Cross-channel velocity and anomaly detection
- Step-up to OTP or biometric only when risk score warrants
- Protocol-transparent: no changes required on the host side
- Tunable thresholds per customer segment and transaction type
Capability 03
Intelligent Banking Channels
AI-enhanced interfaces across every customer-facing channel — ATM, kiosk, mobile app, and web. Channels adapt dynamically to customer context: surfacing relevant services, pre-filling flows with known data, and escalating to human support when confidence is low. All intelligence is grounded on the bank's own product catalog and customer data, not general-purpose web models.
Key capabilities
- Context-aware ATM and kiosk UI adapted to customer history
- Pre-filled transaction flows reducing customer input steps
- In-app conversational assistant grounded on bank-specific content
- Intelligent escalation to human agent with full context transfer
- Multi-language support with bank-defined tone and terminology
Capability 04
Document Intelligence & RAG
Retrieval-augmented generation over BTS product documentation, runbooks, ISO 8583 / NDC+ specifications, terminal configuration manuals, and certification artifacts. Operations teams, integrators, and support engineers query a single grounded assistant rather than searching PDFs. Responses include citations to source pages. Access is role-gated, and the system runs on-prem or inside the bank's VPC.
Key capabilities
- Indexed over product manuals, runbooks, and certification documents
- Cited responses — every answer links to the source page
- Role-based access control: staff see only what they are permitted to see
- On-prem or private-VPC deployment — no customer data leaves the perimeter
- Continuously updated as documentation changes
Capability 05
Financial Risk & Intelligence
Real-time anomaly detection on transaction streams, with explainable scores that compliance teams can present to a regulator. Models are tuned per market because fraud patterns in Amman differ from those in Dubai or Baghdad. AML monitoring integrates with existing case-management systems via standard REST APIs. Human-in-the-loop controls apply to all consequential decisions.
Key capabilities
- Streaming anomaly detection on the full transaction path
- Explainable scores: contributing features visible alongside each alert
- Per-market model tuning to reflect local spending and fraud patterns
- AML integration with case-management systems via REST
- Sanction screening and PEP list enrichment
- Human-in-the-loop on all transaction-decline decisions
Capability 06
AI-Powered Banking Automation
Operational AI that removes manual steps from routine banking workflows — cash forecasting for ATM and branch, hardware-failure prediction for terminal estates, automated reconciliation exception triage, and document processing for onboarding and compliance. Each automation is designed to assist operations teams, not replace oversight.
Key capabilities
- Cash-out forecasting by terminal, branch, and region
- Hardware-failure prediction from ATM and kiosk telemetry
- Automated reconciliation exception flagging and triage
- Document processing for KYC, onboarding, and compliance
- Field-dispatch recommendations surfaced inside TMS dashboard
- Performance benchmarking across the terminal estate
Capability 07
AI-Driven Financial Workflows
End-to-end workflow automation for financial operations that span multiple systems: loan application processing, account opening with digital identity verification, transaction dispute resolution, and regulatory reporting. BTS workflow engine connects AI decision points to existing core banking and operations platforms without requiring replacement of those systems.
Key capabilities
- Digital account opening with AI-assisted KYC and identity verification
- Loan origination workflow with automated document classification
- Transaction dispute intake, classification, and routing
- Regulatory report generation with AI-assisted data aggregation
- Exception handling with human-review queues and audit trails
- Integration with T24, Finastra Finestra, Oracle FLEXCUBE, and other core banking systems
Responsible AI by Design
Every BTS AI capability is built with human oversight as a non-negotiable requirement. Consequential decisions — transaction declines, account restrictions, fraud flags — always have a human-review path. All model inferences are logged to an immutable audit trail. Model cards are available on request. We track emerging MENA central-bank guidance on AI in financial services and update our deployment patterns accordingly. The default architecture keeps all customer data inside the bank's own infrastructure perimeter.
Human-in-the-loop
No automated transaction decline or account restriction without a human review path. AI recommends; humans decide on consequential outcomes.
Explainable outputs
Every model score surfaces the contributing features so operations teams can understand, audit, and defend the decision.
Data sovereignty
Default deployment architecture keeps all customer data inside the bank's own infrastructure. No data crosses to public LLM infrastructure.
Regulatory alignment
We track MENA central-bank guidance on AI in financial services and align deployment patterns before they become mandates.
Talk to our team about your AI roadmap.
We can run a scoping workshop against your specific environment, regulatory constraints, and existing infrastructure.