Power BI for Finance & Banking: 5 Practical Projects to Build Your Career

Microsoft's Financial Sample Excel workbook is a safe place to learn importing and visuals, although it contains sales and profit data rather than banking transactions. For the banking projects, create fictional CSV files with a written data dictionary. Give each fact table a clear grain, such as one row per transaction or loan snapshot, and use separate date, product or branch dimensions when needed. Power Query prepares and types the data; DAX measures calculate values under report filters. Reconcile totals against the source before drawing conclusions.

Create fictional daily inflows, outflows, opening balances and expected settlement dates. Build daily net flow, cumulative closing balance and a maturity ladder by week. Add a slicer for currency or business unit, but never add balances in different currencies without an explicit conversion rule. Deliver a report page plus a reconciliation sheet showing opening balance + inflows - outflows = closing balance. In an interview, explain which dates are booked, expected or actual.

Use invented loan IDs, disbursed amounts, outstanding balances, due dates, payment dates and status codes. Show outstanding by product, aging buckets and count of accounts with a missed due date. Define whether a late account is measured as of the snapshot date or today's date, and avoid implying that your custom bucket is an official regulatory classification. Include a drill-through case page with fictional IDs and a note on missing or amended payments.

Create two fictional sources: an internal ledger and an external statement. Join on a stable reference and compare amount, currency and date under a documented tolerance. Show matched, unmatched, amount mismatch and stale exception counts. The important deliverable is a reproducible exception list with owner, age, evidence and next action. Check that matched plus exception rows equal the source population after duplicates are handled.

Create fictional payment instructions with received time, status events, channel, currency and resolution reason. Show volumes, completion rate, pending age and reason trends. Define the denominator for completion rate and distinguish a rejected instruction from one still under investigation. Add a view of cases nearing a fictional internal cutoff. Do not describe your practice cutoff as a real bank service-level agreement.

Start with Microsoft's financial sample or invented monthly expense records and a separate budget table. Align both to month, cost centre and category before calculating variance. Show amount and percentage variance, then explain a large movement with a note that separates confirmed cause from hypothesis. Handle missing budget lines explicitly: blank budget is not automatically zero. Save a one-page summary for a finance manager and a detail page for an analyst.

1. Publish a short problem statement, data dictionary and source note; mark all invented data as fictional.
2. Show the Power Query steps, table relationships and definitions for key measures.
3. Record three checks: row counts, source-to-report totals and one edge case such as a duplicate or blank date.
4. Explain one insight, its limitation and what you would ask a process owner before acting.
5. Share screenshots or a safe file only after checking that no confidential data, hidden page or embedded credential remains.

If a real employer authorises a report, follow its access rules. Microsoft notes that row-level security filters rows for specified users but is not a substitute for all data-access controls. A public portfolio should use synthetic or approved public data instead.

Download Microsoft's Financial Sample workbook

Read Microsoft's star-schema guidance

Explore finance operations portfolio projects

Editorial review: 9 October 2026. Project data and cutoffs in this guide are fictional learning examples, not employer procedures or financial advice.