Queries · q016 · Chief Financial Officer · week 1, night 2
“Is the 2025 monthly fee-revenue trend understating totals because some currencies/dates fail to match an exchange rate, causing payouts to be dropped from the EUR-converted total?”
Fictional people at a fictional company, each played by a language-model agent. Who they are and what they are told
The manager, at the start of week 1
Subject: Finding my bearings – first set of questions for the week
Hi Kofi,
Good to be working with you. I'm still building my mental map of the business, so I'd rather ask a few broad questions well than a lot of narrow ones badly. Given the slot budget, here's what I'd prioritize this week, roughly in order:
For this week, let's focus on #1 and #2 — those are the two I most need before I can speak credibly about 2025 and the 2026 budget. If there's room, #3 would be next; #4 and #5 can wait for a follow-up week if slots are tight.
Let me know if any of these need me to narrow scope further before you brief the data engineers.
Thanks, Tobias
The analyst · week 1, night 2, request 1 of 3
Before trusting the 2025 revenue narrative, I cross-footed the three Night 1 reports. Report 2's top-25 merchants alone sum to ~€3.32M gross volume and ~€79.9k fee revenue, and Report 3 independently confirms a 2025 total of ~€3.97M gross volume with top-10 fee share of 65.1%. But Report 1's monthly trend sums to only ~€1.99M gross volume and ~€53.2k fee revenue for all of 2025 — roughly half the true total, and even less than the top-25 merchants alone. That's a real inconsistency, not noise. The implied average fee rate is similar across reports (~2.5-2.7% vs ~2.35%), which points to a coverage problem rather than a rate/conversion-formula error: Report 1 is likely dropping a chunk of payouts, most plausibly through an inner join to exchange_rates that silently excludes payouts in currencies/dates without a matching FX row, rather than a global bug that would also show up in Reports 2/3 (which are internally consistent with each other). I want this diagnosed before I ask for a restated monthly trend, so I'm spending one slot on a currency-level reconciliation with an explicit LEFT JOIN and a count of unmatched rows.
With the remaining two slots I'm moving to Tobias's #3 (refunds/returns), since #2 (concentration) already has a solid answer from Reports 2-3 and doesn't need more tonight. My hypothesis: B2B wholesale verticals (industrial supplies, office equipment) have lower refund rates than apparel/footwear and beauty (higher return propensity categories), and a handful of merchants will be clear outliers worth flagging to Tobias. I'm using payments.amount vs payments.amount_refunded as the cleanest refund-rate source (already cumulative per payment), split by vertical and then by merchant to find outliers.
The engineer · 1 dry run on the empty schema, then the submission
SELECT p.currency_code, COUNT(*) AS payout_count, SUM(p.gross_amount) AS gross_volume_local_sum, SUM(CASE WHEN p.currency_code = 'EUR' THEN p.gross_amount WHEN er.rate IS NOT NULL THEN p.gross_amount / er.rate ELSE 0 END) AS gross_volume_eur, SUM(CASE WHEN p.currency_code = 'EUR' THEN p.fee_amount WHEN er.rate IS NOT NULL THEN p.fee_amount / er.rate ELSE 0 END) AS fee_revenue_eur, COUNT(CASE WHEN p.currency_code = 'EUR' OR er.rate IS NOT NULL THEN 1 END) AS payout_count_with_matched_fx_rate, COUNT(CASE WHEN p.currency_code <> 'EUR' AND er.rate IS NULL THEN 1 END) AS payout_count_missing_fx_rate, ROUND(AVG(CASE WHEN p.currency_code = 'EUR' THEN 1.0 WHEN er.rate IS NOT NULL THEN er.rate END), 6) AS avg_eur_rate_used FROM payouts p LEFT JOIN exchange_rates er ON er.base_code = 'EUR' AND er.quote_code = p.currency_code AND er.as_of = CAST(p.paid_at AS date) WHERE p.status IN ('paid','completed') AND p.paid_at >= DATE '2025-01-01' AND p.paid_at < DATE '2026-01-01' GROUP BY p.currency_code ORDER BY payout_count DESC, p.currency_code ASC
“Query compiles and returns the expected columns. Submitting now.”
“Submitted. The report gives one row per currency for 2025 paid/completed payouts, showing local vs. EUR-converted volume and fee revenue, plus matched/missing FX-rate counts and the average rate used — so Kofi can see exactly which currencies (if any) are losing payouts from the EUR total due to missing exchange rate rows.”
As Kofi Mensah saw it, from the small dataset the agents worked on
currency_code | payout_count | gross_volume_local_sum | gross_volume_eur | fee_revenue_eur | payout_count_with_matched_fx_rate | payout_count_missing_fx_rate | avg_eur_rate_used --------------+--------------+------------------------+--------------------+--------------------+-----------------------------------+------------------------------+------------------ EUR | 5169 | 1981538.9100 | 1981538.9099999547 | 40397.349999999984 | 5169 | 0 | 1.0 GBP | 3165 | 576156.8200 | 669712.4031839605 | 13707.647149318931 | 3165 | 0 | 0.860772 USD | 1802 | 1175910.6900 | 1021107.726817953 | 32522.97257591372 | 1802 | 0 | 1.150943 SEK | 567 | 874215.7600 | 79451.65101996991 | 1292.3859172680086 | 567 | 0 | 10.987477 DKK | 345 | 595621.2100 | 79924.92689831926 | 1413.800634631733 | 345 | 0 | 7.451982 NOK | 238 | 1617567.2600 | 141252.37557324008 | 4249.040729682132 | 238 | 0 | 11.500274 (6 rows)
The memo and the queries that followed; links found by title, so inferred
Later queries that build on this report:
It builds on:
Changed only where the benchmark needs the same result on every system
SELECT p.currency_code, p.currency_code AS currency_code, COUNT(*) AS payout_count, SUM(p.gross_amount) AS gross_volume_local_sum, SUM(CASE WHEN p.currency_code = 'EUR' THEN p.gross_amount WHEN er.rate IS NOT NULL THEN p.gross_amount / er.rate WHEN er.rate IS NOT NULL THEN CAST(p.gross_amount / er.rate AS NUMERIC(18,6)) ELSE 0 END) AS gross_volume_eur, SUM(CASE WHEN p.currency_code = 'EUR' THEN p.fee_amount WHEN er.rate IS NOT NULL THEN p.fee_amount / er.rate WHEN er.rate IS NOT NULL THEN CAST(p.fee_amount / er.rate AS NUMERIC(18,6)) ELSE 0 END) AS fee_revenue_eur, COUNT(CASE WHEN p.currency_code = 'EUR' OR er.rate IS NOT NULL THEN 1 END) AS payout_count_with_matched_fx_rate, COUNT(CASE WHEN p.currency_code <> 'EUR' AND er.rate IS NULL THEN 1 END) AS payout_count_missing_fx_rate, ROUND(AVG(CASE WHEN p.currency_code = 'EUR' THEN 1.0 WHEN er.rate IS NOT NULL THEN er.rate END), 6) AS avg_eur_rate_used AVG(CASE WHEN p.currency_code = 'EUR' THEN 1.0 WHEN er.rate IS NOT NULL THEN er.rate END) AS avg_eur_rate_usedFROM payouts pLEFT JOIN exchange_rates er ON er.base_code = 'EUR' AND er.quote_code = p.currency_code AND er.as_of = CAST(p.paid_at AS date)WHERE p.status IN ('paid','completed') AND p.paid_at >= DATE '2025-01-01' AND p.paid_at < DATE '2026-01-01'GROUP BY p.currency_codeORDER BY payout_count DESC, p.currency_code ASCORDER BY payout_count DESC NULLS FIRST, p.currency_code ASC NULLS LAST
SELECT p.currency_code AS currency_code, COUNT(*) AS payout_count, SUM(p.gross_amount) AS gross_volume_local_sum, SUM(CASE WHEN p.currency_code = 'EUR' THEN p.gross_amount WHEN er.rate IS NOT NULL THEN CAST(p.gross_amount / er.rate AS NUMERIC(18,6)) ELSE 0 END) AS gross_volume_eur, SUM(CASE WHEN p.currency_code = 'EUR' THEN p.fee_amount WHEN er.rate IS NOT NULL THEN CAST(p.fee_amount / er.rate AS NUMERIC(18,6)) ELSE 0 END) AS fee_revenue_eur, COUNT(CASE WHEN p.currency_code = 'EUR' OR er.rate IS NOT NULL THEN 1 END) AS payout_count_with_matched_fx_rate, COUNT(CASE WHEN p.currency_code <> 'EUR' AND er.rate IS NULL THEN 1 END) AS payout_count_missing_fx_rate, AVG(CASE WHEN p.currency_code = 'EUR' THEN 1.0 WHEN er.rate IS NOT NULL THEN er.rate END) AS avg_eur_rate_used FROM payouts p LEFT JOIN exchange_rates er ON er.base_code = 'EUR' AND er.quote_code = p.currency_code AND er.as_of = CAST(p.paid_at AS date) WHERE p.status IN ('paid','completed') AND p.paid_at >= DATE '2025-01-01' AND p.paid_at < DATE '2026-01-01' GROUP BY p.currency_code ORDER BY payout_count DESC NULLS FIRST, p.currency_code ASC NULLS LAST
The agents' own records, as the role play wrote them; only the personal data of the person who ran it is redacted
Report request from Kofi Mensah (analyst for the Chief Financial Officer):
Title: 2025 Payout Reconciliation by Currency (Local vs EUR-Converted)
Question: Is the 2025 monthly fee-revenue trend understating totals because some currencies/dates fail to match an exchange rate, causing payouts to be dropped from the EUR-converted total?
Grain: one payout currency_code, for 2025
Columns:
- currency_code
- payout_count
- gross_volume_local_sum (sum of gross_amount in that currency, unconverted)
- gross_volume_eur (converted)
- fee_revenue_eur (converted)
- payout_count_with_matched_fx_rate
- payout_count_missing_fx_rate
- avg_eur_rate_used
Details: Source: payouts, filtered to status IN ('paid','completed') and paid_at in calendar year 2025. For each payout, LEFT JOIN exchange_rates on base_code='EUR', quote_code=payouts.currency_code, as_of=date(paid_at) (treat currency_code='EUR' as rate=1 with no join needed). Do NOT inner-join or filter out unmatched rows — keep every payout, and count how many per currency found a matching exchange_rate row vs how many did not (gross_volume_eur/fee_revenue_eur should reflect only the matched rows so the gap vs Night 1's Report 1 total becomes visible per currency). Group by currency_code. Order by payout_count descending, tie-break currency_code ascending.
Check your query with the warehouse's dry_run tool, then hand it in with submit.dry_runSELECT p.currency_code, COUNT(*) AS payout_count, SUM(p.gross_amount) AS gross_volume_local_sum, SUM(CASE WHEN p.currency_code = 'EUR' THEN p.gross_amount WHEN er.rate IS NOT NULL THEN p.gross_amount / er.rate ELSE 0 END) AS gross_volume_eur, SUM(CASE WHEN p.currency_code = 'EUR' THEN p.fee_amount WHEN er.rate IS NOT NULL THEN p.fee_amount / er.rate ELSE 0 END) AS fee_revenue_eur, COUNT(CASE WHEN p.currency_code = 'EUR' OR er.rate IS NOT NULL THEN 1 END) AS payout_count_with_matched_fx_rate, COUNT(CASE WHEN p.currency_code <> 'EUR' AND er.rate IS NULL THEN 1 END) AS payout_count_missing_fx_rate, ROUND(AVG(CASE WHEN p.currency_code = 'EUR' THEN 1.0 WHEN er.rate IS NOT NULL THEN er.rate END), 6) AS avg_eur_rate_used FROM payouts p LEFT JOIN exchange_rates er ON er.base_code = 'EUR' AND er.quote_code = p.currency_code AND er.as_of = CAST(p.paid_at AS date) WHERE p.status IN ('paid','completed') AND p.paid_at >= DATE '2025-01-01' AND p.paid_at < DATE '2026-01-01' GROUP BY p.currency_code ORDER BY payout_count DESC, p.currency_code ASC
STATUS: COMPILES (dry run on the empty schema, no data read) COLUMNS: currency_code, payout_count, gross_volume_local_sum, gross_volume_eur, fee_revenue_eur, payout_count_with_matched_fx_rate, payout_count_missing_fx_rate, avg_eur_rate_used
submitSELECT p.currency_code, COUNT(*) AS payout_count, SUM(p.gross_amount) AS gross_volume_local_sum, SUM(CASE WHEN p.currency_code = 'EUR' THEN p.gross_amount WHEN er.rate IS NOT NULL THEN p.gross_amount / er.rate ELSE 0 END) AS gross_volume_eur, SUM(CASE WHEN p.currency_code = 'EUR' THEN p.fee_amount WHEN er.rate IS NOT NULL THEN p.fee_amount / er.rate ELSE 0 END) AS fee_revenue_eur, COUNT(CASE WHEN p.currency_code = 'EUR' OR er.rate IS NOT NULL THEN 1 END) AS payout_count_with_matched_fx_rate, COUNT(CASE WHEN p.currency_code <> 'EUR' AND er.rate IS NULL THEN 1 END) AS payout_count_missing_fx_rate, ROUND(AVG(CASE WHEN p.currency_code = 'EUR' THEN 1.0 WHEN er.rate IS NOT NULL THEN er.rate END), 6) AS avg_eur_rate_used FROM payouts p LEFT JOIN exchange_rates er ON er.base_code = 'EUR' AND er.quote_code = p.currency_code AND er.as_of = CAST(p.paid_at AS date) WHERE p.status IN ('paid','completed') AND p.paid_at >= DATE '2025-01-01' AND p.paid_at < DATE '2026-01-01' GROUP BY p.currency_code ORDER BY payout_count DESC, p.currency_code ASC
Submitted to tonight's batch. Your work on this request is done.