Zero-day close requires zero-day data. You're building on a 48-hour delay.

Your platform promises real-time financial visibility and faster close cycles. But the transaction data underneath still arrives 24–48 hours late through batch file transfers and aggregated bank feeds. The bottleneck isn't your software — it's your data infrastructure.

You can't close the books in real time on data that arrives a day late

Aggregated bank feeds were designed when accounting meant monthly closes and manual reconciliation. The pipeline hasn't changed: card transaction settles, bank processes it, aggregator scrapes it, your platform receives a flat file 24–72 hours later — with a raw merchant string, a single-currency amount, and no guarantee it won't break when the bank changes processors.

You can build the most sophisticated reconciliation engine in the world. If it's waiting on yesterday's data, your "real-time dashboard" is a day behind reality.

24–48h
Average delay between a card transaction and when it appears in your platform through bank feeds — even though the data exists at the network level the moment the card is swiped

Three forces are converging — and the data layer can't keep up

The bank feed pipeline is an engineering tax you can't stop paying

Every bank and aggregator sends data in a different format — proprietary file specs, custom CSVs, varying field structures. Each requires its own SFTP configuration, encryption keys, and credential management. Connections break silently when banks change processors or aggregators. Your engineering team spends cycles maintaining file parsers and debugging missing transactions instead of building product. And your support team fields the tickets when a customer's card feed goes dark for three days with no explanation. It's not technical debt — it's ongoing operational cost with no path to zero.

The entire market is rebuilding on real-time data — incumbents included

SAP rebuilt Ariba from the ground up as an AI-native platform — not a feature update, a full architectural rewrite. Sage acquired Fyle to add direct Visa and Mastercard real-time feeds to its accounting suite. Workday integrated Astrada for auth-time expense data. And a wave of AI-native ERP startups — Rillet, Campfire, DualEntry, Numeric, Everest — are all building toward zero-day close. This isn't a trend your platform can watch from a distance. The largest incumbents in enterprise software are rearchitecting around real-time transaction data right now.

AI agents are coming — and they'll need this infrastructure

Every major ERP is shipping AI-powered reconciliation and categorization — Workday Illuminate, SAP Joule, Oracle's AI suite. Goldman Sachs is deploying autonomous reconciliation agents. But an AI agent running on bank feed data that arrives once a day isn't doing real-time anything — it's doing retroactive cleanup. Real-time structured data is the foundation that makes accounting agents useful — not smarter models or bigger context windows. The platforms that invest in that foundation now will be the ones whose AI features actually work.

Auth-time data doesn't just make your platform faster. It changes what you can architect.

Continuous reconciliation replaces batch close

With auth-time data, reconciliation becomes a maintained state, not a month-end sprint. The "close" isn't a process your customers dread — it's a report that confirms what your platform already knows. Rillet's customer Postscript closes books in three days — with auth-time data, that's same-day.

Deterministic categorization replaces ML on raw strings

You built machine learning models to interpret "AMZN MKTP US" and "SQ *BLUE BOTTLE COF." With MCC codes, merchant IDs, and terminal IDs arriving as structured fields, your categorization logic becomes deterministic — not probabilistic. That precision is available for every card, from every issuer.

Policy enforcement at authorization, not after settlement

Spending limits, category restrictions, vendor approvals — your rules engine can evaluate every transaction the moment it happens. An out-of-policy purchase at 2pm Tuesday surfaces at 2pm Tuesday, not when the bank feed arrives Wednesday or Thursday.

Multi-currency as structured data, not reverse-engineered math

Bank feeds deliver a single-currency settled amount. Your platform reverse-engineers the original transaction currency and FX rate — and sometimes gets it wrong. Astrada delivers transaction currency, billing currency, and conversion rate as separate fields. International reconciliation becomes a solved problem.

The accounting stack is being rebuilt from the data layer up.

Every platform in the stack is asking the same question: in an agentic era, are you the foundation that AI is built on, or the workflow layer it replaces? The answer depends on your data infrastructure. Platforms built on real-time, structured transaction data become the system of record that agents depend on. Platforms still waiting on batch files become the thing that gets automated away.

Visa and Mastercard make real-time transaction data available at the network level. Astrada makes it accessible through a single API. The platforms that build on it will ship zero-day close, continuous reconciliation, and touchless expense management. The rest will keep building features on top of an infrastructure designed for a different era.

The first platform with real-time card data ships the zero-day close.

One API. Visa and Mastercard. Structured, real-time transaction data flowing into your reconciliation engine within weeks — not quarters.