Recreate Monarch Money in Excel: A London-Ready Budget Template and Import Guide

Stop wasting hours reconciling spreadsheets — rebuild Monarch Money in Excel for UK small businesses

If you run a small business in London or elsewhere in the UK, you know the pain: multiple bank accounts, CSV downloads, messy categorisation, and a budgeting app that costs money and doesn’t match how you run cashflow. What if you could get the best Monarch Money features — account linking via CSV, accounting-grade reporting, automated categorisation, flexible and category budgeting — in a single London-ready Excel workbook that you control? This guide shows you how, step-by-step, using Power Query, tables, and simple automation so your monthly reporting feels like a budgeting app replacement.

Quick overview — what you'll get from this article

• A ready-made design for a Monarch-style budgeting workbook geared to UK small businesses.
• Step-by-step Power Query import instructions for bank CSVs (single file and folder combine).
• Rules-based categorisation (merchant mapping & fuzzy matches) examples.
• Two budgeting modes replicated: Flexible budgeting (envelope/rollover) and Category budgeting (monthly targets).
• Practical tips on reconciliation, governance and scheduling refreshes in 2026's toolset (Power Automate, Copilot-assisted Excel).

Why recreate Monarch Money in Excel in 2026?

Monarch Money and similar consumer apps remain excellent for many people, but small businesses have special needs: VAT timing, payroll windows, supplier payment cycles and bespoke categories. By 2026, a few developments make an Excel rebuild even more compelling:

• Open Banking maturity and CSV reality — while Open Banking APIs are more widely available, many UK banks still provide CSV exports as the most reliable repeatable feed for small businesses.
• Stronger Excel automation — Power Query, Power Pivot/DAX and Python in Excel are mainstream. Microsoft 365 Copilot helps craft transforms and formulas faster.
• Data governance expectations — firms need auditable, local records for accounts and HMRC compliance. A controlled workbook gives that audit trail. See also approaches from modern data catalogs for keeping metadata tidy.

"Rebuilding a budgeting app in Excel lets you control categorisation rules, data retention and reporting — and save hours on manual work each month."

How the London-ready workbook is structured (single source of truth)

The workbook uses a small set of tables and a Power Query pipeline. Keep these tables in a dedicated "Data" sheet or as Excel Tables on separate sheets for governance.

1. Accounts — list bank account name, sort code, account type and import rules.
2. Transactions — the normalized combined feed from Power Query.
3. Categories — budget categories with parent/child hierarchy, VAT tags.
4. Rules — merchant keywords, regex patterns, and mapped categories.
5. BudgetTargets — monthly category budgets, flags for flexible/carryover.
6. Metadata/Audit — import date, file origin, and reconciliation notes (treat this like a lightweight data catalog).

Step 1 — Prepare bank CSVs for Power Query

Most UK banks provide CSVs with slightly different layouts. Save each bank export into a dedicated folder (e.g., C:\BankCSV\January). Use a consistent naming convention: BankName_Account_YYYYMMDD.csv. That makes automated folder-based imports reliable.

Power Query: Combine all CSVs in a folder

Use Data > Get Data > From File > From Folder. Point to your bank CSV folder. Choose Combine & Transform and then harmonize columns.

Key transforms you should do in the Power Query Editor:

• Trim and lowercase text columns.
• Parse dates using Date.FromText or DateTimeZone conversions (UK date orders).
• Standardize amount sign conventions (some banks use CR/DR).
• Extract sort code/account number if present to link to Account table.

Example M (Power Query) snippet

Use this as a starting pattern (paste into Advanced Editor and replace folder path). Note: escape characters will be handled in Excel.

let
    Source = Folder.Files("C:\\BankCSV\\"),
    CSVFiles = Table.SelectRows(Source, each Text.EndsWith([Name], ".csv")),
    GetContents = Table.AddColumn(CSVFiles, "ContentTable", each Csv.Document(File.Contents([Folder Path] & [Name]),[Delimiter=",", Columns=10, QuoteStyle=QuoteStyle.None])),
    Expand = Table.ExpandTableColumn(GetContents, "ContentTable", {"Column1","Column2","Column3","Column4","Column5"}, {"Date","Description","Reference","Debit","Credit"}),
    Promote = Table.PromoteHeaders(Expand, [PromoteAllScalars=true]),
    CleanDate = Table.TransformColumns(Promote,{{"Date", each Date.FromText(Text.Trim(_)), type date}}),
    CleanAmt = Table.AddColumn(CleanDate, "Amount", each try Number.FromText(Text.Select([Debit], {"0".."9","-","."})) * -1 otherwise try Number.FromText(Text.Select([Credit], {"0".."9","-","."})) otherwise null)
in
    CleanAmt
  

Step 2 — Normalise the Transactions table

After the initial import, the Transactions table should be an Excel Table with columns like:

• Date
• Description
• Reference
• Amount
• AccountID
• Category (blank initially)
• ImportedFrom (filename)
• BankTxID

Keep the Transactions table read-only: update via Power Query and never allow manual edits except through reconciliation notes. That preserves your audit trail.

Step 3 — Automate categorisation with a rules table

A rules-driven approach is the most efficient and transparent for small business needs. Create a Rules table with columns:

• RuleID
• Pattern (keyword, phrase or regex)
• MatchType (Contains, StartsWith, Regex)
• CategoryID
• Priority

Implement rules in Power Query

Create a query that merges Transactions with the Rules table and applies the first matching rule. For fuzzy merchant matching, use Text.Contains on lowercased values or the Text.PositionOf function. For more advanced fuzzy matches, Power Query now supports the Fuzzy Merge option.

Fallback & manual tagging

Not every transaction will match a rule. Flag unmatched transactions with Category = "Unassigned" and expose them in a "Tagging" sheet. A monthly tagging session should take minutes once rules mature.

Step 4 — Build flexible vs category budgets

Monarch offers two popular budgeting styles. You can implement both:

Category budgeting (monthly targets)

Create a BudgetTargets table with Year, Month, CategoryID and BudgetAmount. Then add simple SUMIFS formulas (or DAX measures) to compare actual spend to budget.

Sample Excel formula for Actual spend in a cell (replace table references as needed):

=SUMIFS(Transactions[Amount], Transactions[Category], "=Sales & Marketing", Transactions[Date], ">=" & StartOfMonth, Transactions[Date], "<" & EndOfMonth)

Flexible budgeting (rollover envelopes)

Flexible budgets let unused budget roll into the next month. Implement this with a CarryOver column in BudgetTargets and a running balance measure. Power Pivot/DAX is ideal for this because it handles time intelligence well. For creator and seller cashflow patterns, see approaches in Advanced Cashflow.

Example DAX measure (conceptual):

RemainingBudget =
VAR CurrentMonth = MAX(Calendar[MonthIndex])
RETURN
SUMX(
  FILTER(BudgetTargets, BudgetTargets[MonthIndex] = CurrentMonth),
  BudgetTargets[BudgetAmount] + BudgetTargets[CarryOver] - [ActualSpend]
)
  

Use a simple loop in Excel if you prefer formulas: compute Remaining = PreviousRemaining + Budget - Actual. Mark flexible categories with a flag in the BudgetTargets table.

Step 5 — Cashflow forecasting and quick dashboards

With transactions categorised and budgets in place, build two key reports:

• Monthly Budget vs Actual — PivotTable or Power Pivot model segmented by category and month.
• Rolling 90-day cashflow — starting bank balances + scheduled invoices and payroll obligations. Use Excel’s Forecast and simple aggregations to produce daily/weekly views. For subscription-heavy businesses, consider patterns from subscription playbooks.

Pro tip: include a "Scheduled" table with expected invoice dates and amounts to model cashflow spikes (useful for VAT and PAYE periods). If you run hospitality or food businesses, see operational budgeting notes in the boutique hotel playbook.

Step 6 — Reconciliation and governance

Small businesses need simple, repeatable reconciliation procedures. Our recommended governance checklist:

1. Keep Power Query as the only import method for Transactions; never manually paste into Transactions.
2. Use an Audit sheet logging last refresh time and number of rows imported.
3. Protect structure and lock formulas. Use a read-only distribution copy for team members who should not change rules.
4. Version control: save monthly snapshots (e.g., WorkbookName_YYYYMM.xlsx) or use OneDrive/SharePoint version history.

Automation: scheduling imports and refreshing teams' copies (2026 options)

By 2026, refreshing and automating workbook updates is easier than ever:

• Power Query scheduled refresh via Excel Online and OneDrive for Business (if your CSVs are in a synced folder).
• Power Automate to download CSVs from bank portals where APIs are not available and drop them into a folder to be picked up by Power Query.
• Small scripts using Power Automate Desktop or a secure RPA flow to export CSVs behind MFA — always check bank terms. Consider developer controls described in embedded payments guidance when wiring third-party services.

Remember: fully automated bank scraping can violate bank T&Cs or present security risks. A hybrid approach — manual weekly exports placed in a cloud folder — is the safest for many micro businesses.

Case study: Hackney cafe saved 8 hours monthly

We worked with a London cafe (turnover ~£250k) that used three business accounts plus a personal card. Before rebuilding, the owner spent 8–10 hours each month reconciling and building cashflow. After implementing our Monarch-like workbook:

• Automatic folder-based imports consolidated 6 bank statements into a single Transactions table.
• Rules-based categories reduced manual tagging to 20 minutes/month.
• Flexible budgets let payroll and seasonal marketing spend roll-up without manual adjustment.
• Outcome: 8 hours saved monthly and clearer visibility for VAT payments and supplier scheduling. See similar small-business workflows in this local fulfilment case study.

Advanced tips and 2026 trends to leverage

• Use Excel’s Python or Copilot for data-cleaning templates — these tools are now mature for pattern extraction and anomaly detection. Read about modern toolchains in the New Power Stack.
• Link invoices and receipts by adding invoice ID in the Transactions table. Use VLOOKUP or Power Query merges to attach unpaid invoices to cashflow.
• Consider Power BI if team dashboards or multi-entity consolidation is needed; the same Power Query pipeline feeds both Excel and Power BI. For higher-volume streaming and dashboarding platforms, see cloud platform reviews.
• Security-first: store the workbook in OneDrive with MFA and restrict sharing for payroll and bank details. For guidance on developer and secret management, review best practices in platform security and zero-trust approaches.

Common pitfalls and how to avoid them

• Mixing manual edits with query outputs — causes data drift. Always treat query outputs as authoritative.
• Poor rule hygiene — rules should be reviewed monthly; give rules owners a simple checklist.
• Overcomplicating budgets — start with core categories and add granularity after 2–3 months. If you sell subscriptions or grow via creator channels, see the cashflow guidance in Advanced Cashflow.

Downloadable London-ready template bundle (what’s included)

Our downloadable bundle for UK small businesses includes:

• Master workbook: Transactions, Accounts, Categories, Rules, BudgetTargets, Audit.
• Power Query templates: folder-based CSV combine, merchant mapping example, fuzzy merge sample.
• Dashboard sheets: Budget vs Actual, Cashflow Forecast (30/90/180 days), VAT & PAYE calendar.
• Quick-start guide with example bank CSVs and a 20-minute setup checklist for London businesses.
• Optional add-ons: Invoice register, payroll schedule and supplier payment planner (UK-focused). For local fulfilment and supplier planning strategies, see a relevant case study here.

How to customise for your business in 30–90 minutes

1. Place bank CSVs in the folder and refresh the Power Query on the Master workbook.
2. Open the Rules table and add 10 common merchant keywords (e.g., "Sainsbury", "Stripe", "Square").
3. Populate BudgetTargets for key categories for the next three months.
4. Run the dashboard; review Unassigned transactions and add tagging rules.
5. Lock the workbook and save a monthly snapshot after your first reconciliation.

Final notes on compliance and best practice

Keep VAT and payroll windows in mind when modelling cashflow. Maintain transaction-level backups for at least 7 years for HMRC audits, and document your categorisation decisions for consistency. Using an Excel workbook doesn’t reduce professional obligations — it makes compliance easier if you keep good records. If you work with creators or subscription models, the techniques described in subscription playbooks may be helpful.

Takeaway — why this approach works for UK small businesses in 2026

By combining Power Query imports, rules-driven categorisation and flexible budgeting inside Excel, you get a trustworthy, auditable and UK-ready solution that replicates the best Monarch Money features — without recurring app fees and with deep customisation. The workbook bridges the gap between a consumer budgeting app and the operational reporting a small business actually needs.

Ready to try it?

Download our London-ready budgeting workbook bundle to get started. The bundle includes a 20-minute setup guide, Power Query templates for bank CSV import, and a pre-built Budget vs Actual dashboard. If you want hands-on help, we offer setup and training packages specifically for UK small business owners.

Call to action: Download the template bundle now and reclaim the hours you spend reconciling every month. Prefer a guided setup? Book a 30-minute setup session with our UK Excel specialists.

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