Finance One Uses CallCoach to Review Every Customer Call

Finance One CIO Chris Doyle told iTnews that the group's contact centres handle about 2,000 calls a day and 10,000 a week. Calls lasting at least one minute are passed through an internal workflow to CallCoach, which returns analysis to dashboards and reports. Team leaders are then directed to a smaller set of calls that may need follow-up instead of manually sampling recordings.

Icana's case study says CallCoach analysed 197,514 calls and 21,088 hours of audio during Finance One's first year with the system. IT Brief later reported cumulative totals above 300,000 calls and 33,000 hours. Those figures cover different time horizons and should not be treated as contradictory.

The case study reports a 42% improvement in adherence to Finance One's hardship workflows, a 48% improvement in compliance with its sensitive-data processes, a 42% improvement in query-process adherence and a 14% improvement in tone-of-voice consistency between May and October 2025. Finance One and Icana supplied these measurements; LDS did not retrieve an independent evaluation of the scoring model, its false-positive rate or its ability to detect hardship.

That distinction matters. Reviewing every call expands coverage, but it does not mean every automated flag is correct. The official case study says the teams performed extensive calibration to address non-deterministic AI behavior and build confidence in the scoring. Managers still review surfaced calls and decide what action is appropriate.

iTnews also reports that Finance One has completed an initial AI strategy and framework, is experimenting with LLMs and agents, and has introduced a platform for centrally managing LLM access. Doyle said low-risk, low-volume processes may be prototyped by business users, while core or regulated workflows require more involvement from the technology team.

For data and AI teams, the useful pattern is the separation of coverage from authority: automation can review a larger population and prioritize attention, but people remain responsible for consequential decisions. A production rollout also needs calibration, access controls, retention rules, drift monitoring and a clear escalation path for errors, especially when conversations involve hardship or sensitive financial data.