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Blog · Alternatives and comparisons · Commercial banking

How to choose analytics software for commercial banking: questions, data and traps

How commercial banks should choose analytics software: start from the questions, check the data you hold, ask vendors ten questions, avoid the traps.

By CoviragePublished 24 September 20264 min read
The short answerStart from the questions commercial banks ask every month, not from features. List the exports you already hold, ask every vendor what it needs before the first answer and whether its AI calculates figures, and check that every total reconciles. Then compare the first-year cost, all in.

Most buying decisions for analytics start from a feature list. For commercial banks the better start is the questions that come back every month, the files already on hand, and the traps that make a tool look right in a demonstration and wrong in the first board meeting.

Start from the questions

The question The measure behind it
Which clients borrow from us and bank elsewhere? Lending-only relationships
Where are deposits leaving? Deposit flight
Which relationships hold fewer products than their sector norm? Products held against sector norm
Whose facilities are nearly fully drawn? Facility utilisation
Which relationships do not earn their capital? Return per relationship
Are relationship managers seeing their largest clients? Coverage at cadence, by revenue

Any tool you consider should answer these from your data, not from a sample. Ask to see it.

The data you already hold

  • Product holdings file
  • Client master
  • Holdings file
  • Facility file
  • Balance file
  • Revenue file
  • Estimates by source grade
  • CRM

If a vendor needs a warehouse built before it can read these, count that in the cost and the time.

Ten questions to ask any vendor

  1. What does it need in place before the first answer? A warehouse, a data model, a modelling language, a partner? Ask for the list and the typical weeks.
  2. Who does the setup, and who maintains it? Your team, the vendor, or a partner, and what that costs after year one.
  3. Does the AI calculate figures, or choose from computed ones? A language model that writes queries or code can produce a plausible wrong number. Ask what it is allowed to do.
  4. Does every total reconcile to a control figure? Ask to see a bridge that does not sum and what the product does about it.
  5. Can every figure be opened to its rows? An answer nobody can check becomes a debate in the meeting.
  6. What does it cost in the first year, all in? Licences, consumption, implementation, modelling and training, not only the seat price.
  7. How does data arrive, and who holds credentials? A file your systems already export, a scheduled drop, or a live connection with the vendor holding keys.
  8. What happens to the data, and where is it stored? Residency, retention, deletion, and whether names can be replaced with identifiers.
  9. Can we see it on our own data before we sign? A demonstration on a sample dataset tells you little about your own.
  10. What does the tool do when it cannot answer? It should say so. A confident guess does more harm than no answer.

Checks specific to commercial banking

Ask whether the tool enforces these, and what it does when they fail:

  • Holdings: Product revenue per client sums to the revenue ledger
  • Balances: Relationship balances sum to the general ledger deposit total
  • Referrals: Sent = accepted + declined + pending; accepted = converted + lost + open
  • Coverage: Clients = covered + uncovered; each with one owner

The traps

Deposit flight. Balance reports are totals. The per-relationship trend against the client's own pattern is rarely produced.

Lending-only relationships. Credit approves the exposure; nobody lists the clients where exposure is all there is.

Portfolio load. Every analysis produces more clients to call. None checks whether the calendar can hold them.

Measures to leave out

Products per customer as a bank-wide average. Meaningless without the sector and size norm.

Calls logged. Replace with revenue coverage at cadence.

Loan growth, alone. Growth in lending-only exposure lowers return.

A scorecard

Criterion Weight Tool A Tool B Covirage
Answers our six questions on our own data High
Time to the first answer High
Needs a warehouse or data team Medium
AI calculates figures, or only explains computed ones High
Every total reconciles; figures open to rows High
First-year cost, all in Medium

Where Covirage fits

Covirage reads the exports above, answers the questions with figures our tools compute and check, and is set up for you within a week. See analytics software for commercial banking compared, AI analytics for commercial banking and Covirage for Commercial banking.

For the measures in full, with formulas and exports, read Relationship KPIs for commercial banking.

Questions people ask

What should commercial banks look for in analytics software?

The answer to their own questions, from the data they already hold, with every figure reconciled. Features matter less than what the tool needs before the first answer and who maintains it.

Is a BI suite enough for commercial banks?

It can be, with a warehouse and someone to build and maintain the model. Without them, the dashboard shows what changed and the explanation is still an analyst's job.

What data do commercial banks already hold?

Usually: product holdings file, client master, holdings file, facility file, balance file, revenue file. Most analytics questions in this industry can be answered from those exports.

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