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Blog · Alternatives and comparisons · Retail banking

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

How retail 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 20263 min read
The short answerStart from the questions retail 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 retail 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
Explain where my income came from this month. Net interest income bridge
Where is margin compressing? Margin by product
Which segments hold the fees? Fee income by segment
Which branches open accounts that never fund? Opened and never funded
Where are deposits quietly leaving? Balance attrition
Are we missing plan, and where? Income against plan

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

The data you already hold

  • Balances and rates by product and month
  • Interest
  • Funding rates
  • Fees file
  • Account openings
  • Balances by customer and month
  • Product holdings
  • Customer master

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 retail banking

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

  • Bridge: Income end − income start − (balance + rate + mix) = 0
  • Openings: Opened = funded + unfunded + closed within 90 days
  • Balances: Closing balance = opening + inflows − outflows, by product

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 retail banking compared, AI analytics for retail banking and Covirage for Retail banking.

Questions people ask

What should retail 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 retail 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 retail banks already hold?

Usually: balances and rates by product and month, interest, funding rates, fees file, account openings, balances by customer and month. Most analytics questions in this industry can be answered from those exports.

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