How US Transact T+2 changes the timeline for quant and speed-focused investors
Two days doesn’t sound like much. But in a market where every team is working from similar data on the same timeline, two days earlier is the difference between seeing a signal and acting on one.
US Transact T+2 delivers company, segment, and brand-level consumer spending data two days after the transaction date. That alone is interesting. What makes it useful is that the accuracy holds.
Earlier reads, same rigor
The first question any serious investor asks about faster data is whether accuracy was sacrificed for speed. We built US Transact T+2 specifically so the answer is no.
US Transact T+2 delivers 130 ticker-metrics above 90% correlation to reported revenue, virtually identical to our full-composition panel. The speed is new. The accuracy is not something you trade for it.
On the 90 high-interest names clients ask about most, roughly half achieve above 90% correlation and two-thirds sit above 80%.
For the quant desk: backtest earlier, with cleaner data
If your models ingest consumer transaction data for signal generation, T+2 changes the math on your backtesting cadence. Tables land two days after the transaction date, structured for direct pipeline ingestion with no transformation required.
Coverage spans 650+ public tickers across the consumer economy, so you can backtest broadly rather than against a narrow slice. An additional 230+ private companies give a broader view of the market for further triangulation. The panel draws from approximately 80 million unique cards with balanced credit and debit representation, and every card flows through the same panelization methodology as our full-latency products.
Earlier signal with the same correlation profile means your models get more data to work with sooner, without re-tuning for a different noise profile.
For the fundamental PM: build conviction before the market moves
If you follow consumer-facing companies into earnings, T+2 gives you a head start that compounds through the quarter. Company-level spend data lands earlier, so you have more time to compare panel trends against consensus, pressure-test a thesis, and position before the print.
Segment-level depth helps you understand which parts of the business are driving or dragging results. Channel-level breakouts separate in-store from online spend, so you can track e-commerce mix shifts in near real time. CBSA-level geography shows you where spending is shifting regionally.
It’s the same Consumer Edge methodology, the same accuracy against reported revenue, delivered days earlier with more dimensional depth than any comparable product in the market.
For multi-strategy platforms: one dataset, both sides of the house
T+2 serves quant and fundamental workflows from the same panel. Your systematic teams get structured backtesting tables at T+2 speed. Your discretionary PMs get earlier company and segment reads with channel and geographic context. One vendor, one data source, no reconciliation.
What’s included
- T+2 delivery, updated daily
- Company, segment, and brand-level signal
- Channel-level breakouts (in-store vs. online)
- Distribution brand table
- Cardholder and store geography at the CBSA level
- 650+ public ticker coverage
- 80M unique cards, balanced credit/debit mix
- 130 ticker-metrics above 90% correlation
- Delivered to S3, GCS, Snowflake, and BigQuery
See it against your own names
We publish our accuracy because we’re confident in the comparison. Learn more about the US Transact product suite, or talk to Consumer Edge about running a walkthrough against the tickers your team follows.
