Protocol Authorisation TRIZ Cases

Camera-based user recognition automates bill splitting and fund transfers, cutting manual entry errors and transaction steps.

Unique transaction IDs expose missing RDC deposits across network stages, enabling automatic remediation with less manual investigation.

Conversion flags route dual-message payments into single-message batch settlement, cutting merchant fees without POS upgrades.

Real-time payment messages carry verification elements to confirm destination accounts before funds move, reducing misdirected transfers.

When a transfer exceeds a preset limit, nearby device verification via NFC, QR, Bluetooth, or GPS can temporarily raise the threshold and reduce fraud.

A verification element sent through a real-time payment message confirms the destination account before irrevocable funds are transmitted.

Localized SHAP values and feature normalization reveal each data vendor's fraud-detection value, enabling smarter remediation and resource allocation.

Event-sourced actors and CQRS help process high-volume real-time payments with fault tolerance, auto-scaling, and lower resource use.

Biometric and behavior data on a smart wearable verify payment identity offline, reducing unauthorized access with low resource use.

A unified payment scoring event maps diverse transaction types into one fraud model, improving detection while fitting merchant risk thresholds.

Stored card details are converted into dial tones during a call, avoiding spoken disclosure while improving payment convenience and security.

A short-range payment proxy lets merchant and customer devices exchange payment data offline, then submit authorization when one device reconnects.

Historical nearby merchant pairs let contactless card payments exceed soft limits with fewer declines, lower processing load, and less network traffic.

Biometric passkeys are added to 3-D Secure to sign transaction challenges across cross-origin flows, reducing fraud risk in online payments.

A third-party verifier combines identity checks, confidence scoring, and reimbursement coverage to reduce fraud risk in asset rental and purchase transactions.

Combined transaction and membership verification speeds mobile checkout while supporting electronic documents and promotion handling.

Pseudo-labeling high- and low-risk transaction bins lets fraud models train in extreme low-fraud settings while cutting false positives and misses.

A payment network generates non-payment referents to obfuscate PAI and PII, easing PCI DSS compliance while reducing fraud exposure.

Encoded scannable images prefill user and instrument data, reducing authentication friction while verifying inputs for secure activation.

A universal transaction identifier combines KYC, account, and dynamic message data to connect financial networks while reducing fraud and delays.

A rule-based server maps authentication data to provider-specific templates to avoid redundant FIDO re-authentication and storage duplication.

Shared chargeback history lets card issuers screen customer risk and validate disputes, reducing fraud losses across issuers.

Trigger-based notifications send deep links to the right webpage action, cutting menu search time and improving mobile app engagement.

Encrypted sensitive data is split across separate databases, enabling recurring access while preventing exposure from any single breach.

Switching among phone, card scan, and biometric checks based on device-change conditions improves authentication convenience and security.

Machine learning classifies new and unforeseen transactions for automated approval, review, or denial with less manual oversight.

A second terminal reads a payment code from the first terminal to authenticate automatically, improving payment security without extra user steps.

A payment code shown on one user terminal is read by another terminal, preserving security while avoiding extra user scanning steps.

Balanced training with synthetic outlier events helps unsupervised models cut false positives and improve rare-event detection accuracy.

A server-issued payment element lets digital wallets pay with an encrypted user ID, removing the need to upload a physical payment card.

Combining GPS and Bluetooth verifies payment location indoors and outdoors, adding fraud-resistant authentication without disrupting existing payment systems.

A zero-trust blockchain shares and prunes data across computers, removing central authentication while reducing storage footprint.

Temporary wallets and presigned transactions simplify phone-number crypto transfers while reducing password friction and hacking risk.

Embedding-based mini-graphs compare image and transaction parts with prior cases to detect fraud quickly and at lower computational cost.

Biometric liveness checks and verifiable credentials let a decentralized identity exchange verify users across siloed systems and flag fraud faster.

Off-chain pricing and authorization handle dynamic asset rules before blockchain verification, cutting transaction cost and on-chain complexity.

Machine learning analyzes transaction data and fee causes to route settlements that reduce overdraft risk despite slow transfer confirmation.

Machine learning risk scoring cuts AML false positives while improving anomalous transaction detection and compliance review efficiency.

By clustering past transactions and device attributes into user profiles, this case improves authentication accuracy for shared accounts.

Pre-approved operating parameters let IoT devices transact autonomously while an authorization device checks compliance to reduce fraud risk.

Automatic NFT minting links retail purchases to digital wallets, unifying physical goods sales with verifiable ownership records.

Fragile hard-wired links break when a chip is removed, disabling the chip and magnetic stripe while alerting the issuer.

Pre-checking user intent and stored identity data raises fraud confidence while reducing checkout authentication steps and delay.

Merchant category embeddings and an autoencoder score transaction patterns to flag anomalous or unauthorized activity faster and more accurately.

A session-bound passkey proof lets checkout requests reuse one FIDO authentication, cutting repeated logins and network traffic.

Synthetic transaction graphs with inserted adversarial patterns help train machine learning models when real-time payment history is scarce.

Machine learning ranks compliance tests by transaction-stream trends, enabling real-time alerts with lower compute load and fewer false positives.

Off-chain NFT creation stores token data outside the blockchain, then validates ownership on transfer to cut fees and computing load.

Geo-fencing and beacon-triggered ML authentication verify device location and timing to block unauthorized digital card transactions.

A cumulative replacement request lets offline token transactions be registered once, cutting signature overhead and data growth.

Risk-based shared wallet autofill replaces merchant card storage with tokenized browser checkout, cutting user entry effort while preserving security.