Skip to content

No account required

Start a project

5 min · 4 sections

Analysis for your own money.

Budgeting apps categorise transactions to fit their charts. Your own statements, cleaned properly, say something different.

By Data Analysis App team

Why do budgeting apps get my spending categories wrong?

Because the same shop appears as several merchants across a year whenever its payment descriptor changes, and a budgeting app treats each as separate. Recognising those descriptor variants as one shop before any category total is computed is most of the work and the step consumer tools skip. Separating recurring commitments from one-off purchases is what makes a year of spending legible.

Section 01

Categories are the whole problem

The same coffee shop appears as three merchants across a year because the payment descriptor changed. A budgeting app treats them as three, and the category totals it shows you are quietly wrong in a direction you cannot see.

Treating those three as one shop before any category total is computed is most of the work, and it is the step consumer tools skip because it is expensive and invisible. Descriptor variants that look like the same merchant are listed together for you to confirm rather than merged automatically, because merging two shops that are genuinely different is not something you can undo.

Section 02

Recurring and one-off behave completely differently

A £900 month with one large purchase and a £900 month of subscriptions are the same number and entirely different situations. The first is a decision; the second is a standing commitment that will happen again next month whether you decide anything or not.

Separating the two changes what the total means, and it is usually the first thing that makes a year of spending legible.

In the worked example, 14 recurring payments were no longer used but still cost $7,344 a year.

Section 03

Subscription creep is invisible per month by design

Each individual subscription is small enough not to trigger a reaction, which is precisely why the total is surprising. The useful view is not this month's spend but the trend over a year, with each service's start date marked.

The services worth cancelling are rarely the expensive ones. They are the ones with no usage, which no statement shows you and which have to be inferred.

Section 04

What you need

A year of statement exports, in whatever format your bank produces. CSV, Excel, or a PDF statement all work.

Nothing needs categorising first, and nothing here categorises it for you. A category column that is already in the export is used as it stands; without one, the figures come from dates, amounts and descriptions.

See it on a real project

Two clients, 38% of revenue, accounted for every one of the 38 overdrawn days.

Is winter actually our slow season?

Keep reading

Every check in this guide runs on every upload.

Drop the file in and the problems described here are tested before anything is reported: with the rows behind each repair kept, so you can see exactly what changed.

  • Subtotal rows detected and excluded
  • Duplicates matched on identity, not on whole rows
  • Text-typed numbers found, coerced and counted

No account needed to start. You only pay when you like what you see.