18·Cross-industry

Building the ROI case for AI in regulated back offices

In regulated operations, ROI is not speculative, it is measurable in hours saved and errors avoided.

Regulated back offices are rich in quantifiable, repetitive work: verification, routing, drafting, publication. This makes the business case unusually concrete, provided it is built on defensible assumptions rather than optimistic guesses. The discipline that convinces both institutional partners and investors is explicit sourcing: separate sourced data, reasoned hypotheses and modelling choices.

Two distinct economic stories

Keep revenue-generation and cost-saving cases separate, conflating them weakens both.

OPEX savings: verification time, rework loops and drafting effort reduced (for example targeting 70%+ automation on routine cases).
Revenue generation: risk scores and entity data monetised via API to partner institutions.

Modelling discipline

Anchor per-unit pricing on a share of the manual cost saved
Normalise anomalous spikes rather than baselining on them
Make every assumption defensible to partners and investors alike

Value-based pricing

Per-case pricing anchored on 25 to 40% of the manual processing cost saved keeps the offer compelling for the buyer and profitable for the provider.