Finance

Financial institutions are rarely short of data; the problem is which question to ask.

Defining the decision first

We start by defining the decision itself: which customer, through which channel, with which offer? Models built before that question is settled tend to work well and go unused.

Where we work

Customer segmentation and behavioural modelling. Grouping customers by what they will do, not by what they have done.

Channel and campaign effectiveness. Measuring what a campaign actually produced — separated from the transactions that would have happened anyway.

Process and operations analytics. Making visible where operational processes stall and how long each step takes.

Reporting infrastructure. A reporting layer where a number can be traced and its refresh time is known.

Data sensitivity

Working in finance has a particular character: data is both plentiful and sensitive. In the structures we build, where personal data sits, at which layer it is masked and who can reach it are defined upfront. That is good engineering before it is a compliance requirement.