Withdrawal Distribution — Report documentation

Purpose

The Withdrawal Distribution report helps finance and operations teams see how withdrawal volume is spread across payment providers (PSPs) over time, compare recent weeks, and understand successful vs cancelled vs failed mix and processing currencies. It also supports drill-down to individual withdrawals (aggregator, account, state, and last status message). Use it for monitoring payout routes, spotting shifts between providers, and investigating high-value or problematic withdrawals after you set the date range and filters you need.

What data this report uses

The report is built on General all tx: one row per payment transaction for your organisation, with amounts in client base currency, provider routing, customer and channel context, and outcome flags. For full field meanings, grain, and how amounts are converted, see the General all tx user guide.

Report-level filters

The page is typically used with withdrawals and the main lifecycle states in scope—Successful, Cancelled, and Failed—so you can see both completed flow and non-success volume in one view. Adjust State, Method, and the date range when you need a narrower or wider slice.

Filter (as in Looker)	What it does	How to use it	When it’s useful
Date range	Limits which transactions appear according to the report’s date control (aligned with updated timing for the main pivot views—see each block below).	Pick a preset or custom range.	Weekly checks, month views, or ad hoc investigations.
State	Keeps rows with the transaction state you select.	Pick one or more (default often includes Successful, Cancelled, Failed).	Focus on one outcome or compare several.
Method	Narrows by transaction method (for example Withdrawal).	Pick Withdrawal for this report’s intended view.	Withdrawals only vs deposits or other methods.
Orchestrator	Narrows by orchestrator context from the data.	Pick from the dropdown.	When you segment by orchestration setup.
Legacy Entity	Narrows by a legacy entity label derived from routing (for example SandTech, Igloo).	Pick one or more.	Reporting aligned to legacy entity groupings.
Brand	Keeps the brand (or mapped brand context) you select.	Pick one or more.	One brand or a brand family.
Status Code	Filters by status code on the transaction.	Pick codes you care about.	Drill into specific decline or outcome codes.
Country	Filters using the country field wired to this control (typically customer-facing country).	Pick one or more.	Market or geography slices.
Channel	Narrows by channel (and related channel fields in the source).	Pick from the list.	How the transaction was taken (e.g. web vs app style splits when present).
Deposit Type	Narrows by deposit type when populated.	Pick values that appear in your data.	Finer segmentation when the field applies.
Payment Type	Narrows by payment type when present.	Pick from the list.	Further method or product splits.
TX Type	Narrows by transaction type in the source.	Pick from the list.	When you need a specific TX type bucket.
Affiliate ID	Keeps transactions for the affiliate ids you select.	Pick one or more.	Partner or affiliate reporting.
User Categories	Narrows by user category fields from the source.	Pick categories.	Segmenting by customer or user class.
User ID	Narrows to selected user identifiers.	Pick users.	Individual or small-group analysis.
User Email	Narrows to selected email values when available.	Pick emails.	Support or case-level lookups.
First Time / Returning User	Splits or filters first-time vs returning style buckets when exposed.	Pick the segment you need.	New vs repeat behaviour.
FTD / Trusted	Uses the report’s FTD vs Trusted classification (first-time deposit style vs trusted).	Pick one or both.	Risk or onboarding style cuts.
Initial PSP / Initial PSP MID	Narrows by first provider or first merchant account on the route.	Pick PSP or MID.	Where the journey started.
Final PSP / Final PSP MID	Narrows by final provider or final merchant account that processed the payment.	Pick PSP or MID.	Where the withdrawal landed.
Final PSP Service	Narrows by final PSP service when present.	Pick from the list.	Service-level splits under a PSP.
Final PSP Mapped	Narrows by the mapped final PSP label (grouped / cleaned names for reporting).	Pick one or more labels.	Consistent PSP names when raw codes differ.
Include Multiple Failed Attempts?	Uses the fail-flag logic: whether to include rows flagged as multiple failed attempts.	Set as your team standard.	Cleaner success-focused views vs full attempt history.
Card Scheme	Narrows by card scheme (Visa, Mastercard, etc.) when the transaction is card-based.	Pick schemes.	Card-brand mix.
Card Issuer Country	Narrows by issuer country on the card.	Pick countries.	Cross-border issuing patterns.
Issuer	Narrows by card issuer name when present.	Pick issuers.	Issuer-level analysis.
BIN	Narrows by bank identification number when present.	Pick BINs.	BIN-level concentration.
Transaction ID	Keeps a specific transaction when you enter an id.	Type or paste an id.	Lookup one payment.
Search for a Rule ID	Narrows using rule identifiers when your data fills this field.	Enter a rule id.	Rule or compliance drill-downs.
PD True Data	Narrows using the PD True Data flag as wired on the report.	Choose the option your team uses.	Data-quality or source splits.
Include Test Users?	Controls whether test users appear.	Toggle or pick as designed.	Live vs test views.
Include Flagged Spam Users?	Controls whether spam-flagged users appear.	Toggle or pick as designed.	Excluding noisy or spam-flagged traffic.
Custom Sub Master	Narrows by custom sub-master grouping (merchant / brand buckets defined in Looker).	Pick a group.	Executive or internal groupings.

Use Export when you need a file of the current view.

Resource-level filters

Some tables and charts apply extra limits so each block answers a specific question. They only affect the named visual.

Filter (as in Looker)	Which part of the report it affects	What it does	How to use it
Successful	Last 7 Days incl. today - Successful, 7 Days Prior - Successful, Last 30 Days - Successful	Keeps only Successful withdrawals for that pivot, even when the page State control includes Cancelled and Failed.	Use the page filters for overall scope; use these blocks for successful volume by day and PSP only.
Excl Successful	Failed/Cancelled Volume	Shows Cancelled and Failed withdrawal amounts only (no successful rows in that table).	Read this block when you care about incomplete or declined withdrawal volume by PSP and day.

If a chart’s own date setting uses created time while the main pivot tables use last updated time, totals can differ between blocks for the same calendar labels—check the block title and your team’s convention when numbers look inconsistent.

Last 7 Days incl. today - Successful

The Last 7 Days incl. today - Successful pivot shows successful withdrawal amounts in euros for each Final PSP (row), with one column per calendar day based on when the transaction was last updated. Each cell is the sum of withdrawal amounts for that PSP on that day; Grand total rows and columns roll up the grid.

Use it to compare the most recent week including today across providers and days.

7 Days Prior - Successful

The 7 Days Prior - Successful pivot uses the same layout (Final PSP × daily updated dates × withdrawal amount) but for the previous seven-day window, so you can compare last week vs the week before side by side with the block above.

Last 30 Days - Successful

The Last 30 Days - Successful pivot again limits to Successful withdrawals and sums TX Amount by Final PSP and day (updated) over roughly the last thirty days (exact window follows the tile’s date setting). Use it for medium-term provider mix and daily pattern without scrolling only a single week.

Failed/Cancelled Volume

The Failed/Cancelled Volume pivot breaks non-successful withdrawals into Cancelled and Failed under each Final PSP, with daily columns (updated) and TX Amount in euros. Sub-totals per PSP and Grand total help you see which providers drive incomplete or declined payout volume in the selected period.

Breakdown	What it shows
Final PSP	The provider that ultimately handled the withdrawal.
State	Cancelled or Failed (successful rows are excluded from this table).
Updated (by day)	Calendar day from the last updated timestamp.
TX Amount	Total withdrawal amount in euros for that PSP, state, and day.

State Distribution - Volume

The State Distribution - Volume pie chart splits total withdrawal amount across Successful, Cancelled, and Failed for the chart’s date scope. Each slice is how much money fell into that state—useful for seeing whether volume is dominated by success or by non-success amounts.

The chart’s time window is driven by created date unless your team has aligned it to the page; if slice totals do not match a pivot that uses updated dates, compare the date setting on this chart with the pivot blocks.

State Distribution - TX Count

The State Distribution - TX Count pie chart shows how many withdrawal transactions fall into each state (Successful, Cancelled, Failed). A large slice here means many attempts, which can differ from State Distribution - Volume if average ticket sizes differ by state.

Processing Currencies - TX Count

The Processing Currencies - TX Count pie chart shows transaction counts by processing currency (for example EUR, CAD, USD). Use it to see where withdrawal traffic concentrates by currency under your current filters.

Transaction Reference

The Transaction Reference table lists individual withdrawals with identifiers and the last status message, sorted so larger amounts appear first for quick review.

Column / label	What it shows
Aggregator	High-level provider or platform group (for example the family name behind several MIDs).
Final PSP MID	The specific merchant account or route string used for the withdrawal.
State	Successful, Cancelled, or Failed.
Transaction ID	The unique id for the payment.
Last info	The latest status or reason text (for example authorised, insufficient funds, rule messages, or automatic cancellation text).
Volume	The withdrawal amount in euros for that row.

Pagination shows how many rows match your filters (for example tens of thousands); narrow filters or Transaction ID when you need a short list.

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