When Offline Data Authentication (ODA) fails, replacing Certification Authority Public Keys (CAPKs) at random is rarely productive. Most field failures sit earlier in the chain: …
Fraud-detection papers regularly report near-perfect accuracy on public datasets. Almazroi and Ayub’s 2023 IEEE Access paper is a recent example: a ResNeXt-embedded GRU …
An EMV contact decline is not a single error. It is the outcome of decisions made by the terminal, the card, or the issuer at different stages of the transaction. Treating …
EMV authorization is the easy part. The hard problems are timeouts, retries, SoftPOS lifecycle gaps, store-and-forward declines, and the financial question that remains when two …
In EMV chip transactions, the card does not simply return “approved” or “declined” as plain text. It returns an application cryptogram: an 8-byte MAC bound to that transaction’s …
The next phase of AI in payments is not faster fraud scoring. It is AI moving from an advisory layer that observes the transaction to an actor that initiates payments and operates …
Manual capture is not about typing a card number by hand. It is the deliberate split of a card transaction into authorization and capture, managed as a backend state machine. Why …
A duplicate charge is rarely a coding bug. It is a distributed system losing certainty about whether an authorization already happened — and then guessing wrong. Why blind retries …
This is part 3 of a series on building grounded AI for payment systems. Part 1 made the case that payments need grounded AI, and part 2 Part 2covered the retrieval pattern that …
This is part 2 of a series on building grounded AI for payment systems. Part 1 made the case that payments need grounded AI, not a generic LLM guessing from training data. This …