dataforge-labs/remittance-pricing-panel

Remittance pricing panel

Repeated observations from Wise's public remittance comparison service, covering exchange rates, stated fees and estimated recipient amounts across selected currency corridors.

Contents

Table	Record
remittance_quotes	A provider's displayed comparison for a corridor and send amount, with rate, fees and recipient amount

Using the data

The collector queries twenty configured currency corridors at specified send amounts. Compare providers within the same corridor, amount and observation round. Recipient amounts provide a combined view of the displayed exchange rate and explicit fees.

Separate the collection timestamp from the source's price-update timestamp. A recently collected row can contain older competitor pricing. Wise's competitor comparisons can use previously collected markups applied to updated reference exchange rates, so these records should not be described as simultaneous executable quotes obtained directly from every provider.

Limitations

• Wise operates the comparison service and is also one of the providers being compared. Provider selection and comparison methodology reflect that source.
• Competitor information can be stale or reconstructed. Check update times before treating a change as a new provider quote.
• Actual transfer terms can depend on payment method, customer eligibility, limits and verification requirements.
• Provider coverage varies by corridor and date. The configured currency pairs do not constitute a complete survey of remittance markets.
• Differences in displayed recipient amounts describe the comparison service's observations; they do not prove realised customer savings.

Files and access

Data is stored as Parquet files under table_name/YYYY/MM/, with partitions for collection windows. Each measurement table has a fixed 7-day sample beginning at its configured collection start date. The sample windows in this repository span 2026-08-26 to 2026-09-01. Availability within each window depends on successful collection. The public sample dates remain fixed as additional history accumulates privately. Contact DataForge through the discussions tab to enquire about additional history.

Load a table

Install datasets and pandas to run this example. The train split contains all observations in the selected table; it is not a predefined modelling split.

from datasets import load_dataset

data = load_dataset("dataforge-labs/remittance-pricing-panel",
                    "remittance_quotes", split="train")
df = data.to_pandas()

Coverage

collection_runs records collection windows, poll counts and failures. It is published in full and may cover dates beyond the fixed data sample. Collection gaps are not interpolated. Use this table together with measurement timestamps and error fields to assess coverage.

License and contact

The public sample is published under ODC-BY. Attribute it to "DataForge (dataforge-labs)". For questions about the data or access to additional history, open a discussion in this repository.

Earlier file paths

Each table is stored under a directory with the same descriptive name. The file contents and date partitions are unchanged. Scripts using an earlier directory name should use the corresponding table name below, or pin downloads to revision before-folder-rename-20260915 to access the original layout. Internal collector IDs are retained in the private archive and may appear in raw coverage records.

Current table and directory	Earlier directory
remittance_quotes	e13_remittance_quotes/
collection_runs	e0_run_manifest/