Protocol Authorisation TRIZ Cases

AI analyzes third-party geopolitical data to score transaction threats and trigger denial, delay, or user verification in real time.

Precomputed risk profiles, decision trees, and transformer analysis cut fraud detection delay while improving real-time transaction screening.

Stores card transactions locally during network outages, then forwards them when service returns using risk-based limits on offline storage.

Joint video endorsements and blockchain verification make soft-skill references more credible without adding complex assessment steps.

API-based prevalidation checks transaction data against account details and user intent to cut delays, improve fraud screening, and support compliance.

Additional device, profile, and behavioral data help weaker mobile authenticators pass high-risk transaction approval with fewer denials.

Transaction data matching and issuer-linked identification messages help block social-engineering-based payment provisioning fraud.

Peer-to-peer wireless transfer moves encrypted bank card data between terminals, removing manual entry while preserving TEE or SE security.

Local routing logic uses server-updated ML data to choose the best payment network in 20-30 ms while reducing terminal processing load.

Camera-based verification checks coded and uncoded transaction data to block man-in-the-middle attacks without relying on error-prone user approval.

NFC card tap verification replaces one-time passcodes to secure sensitive transactions while keeping mobile authentication fast and simple.

Machine learning prompts automate cross-dataset connection detection, cutting analyst time while preserving fraud and AML match identification.

Transaction-based propensity models flag and correct misclassified merchant category codes, reducing manual review and improving fee and risk accuracy.

Code-based guardian approval screens high-risk transactions for vulnerable persons, reducing fraud while limiting delays to selected cases.

Camera-based OCR and 3D card modeling replace manual mobile entry while comparing captured card data with stored records to detect fraud.

A machine learning TM Index scores customer behavior across time windows and scenarios to catch suspicious activity missed by single-scenario alerts.

Guardian code approval is triggered for higher-risk transactions to block coerced transfers and reduce fraud exposure for vulnerable users.

Mobile authentication and FBO fund transfer enable instant merchant payment while reducing intermediaries, fees, and chargeback fraud.

A recipient-created link pre-fills payment details, cutting manual entry and helping non-technical users complete payments faster.