Customer support · Production

MONY Group scales AI-powered customer support with Intercom Fin, resolving 64% of queries across chat and email

The problem

MONY Group's support team was handling more than 25,000 conversations a month in a tightly regulated environment, creating burnout risk and an ever-present queue. Customer expectations had shifted toward real-time answers, and their existing Zendesk setup lacked the automation and flexibility to keep pace.

First attempt

MONY Group evaluated Zendesk's own AI offering but found it insufficiently reliable and compliant for a regulated financial services environment; it was described as not 'bulletproof' and not built for real-time conversations.

Workflow diagram · grounded in source

Customer contacts support

trigger

“Fin is now the first point of contact in 98% of conversations across MoneySuperMarket and Quidco, handling both live ch”

Fin resolves customer query

ai_action

“resolving 64% of queries across chat and email, including complex questions around reward eligibility and cashback claims”

Fin Guidance enforces compliance rules

validation

“the team used Fin Guidance to establish clear rules for how Fin should behave. These included tone preferences like using British English and personalizing responses, but also more critical logic: when to ask follow-up questions, when to…”

Fin queries rewards API

integration

“connected Fin directly to their rewards wallet using secure API calls. Now, when a customer asks about a reward, Fin checks their account, replies instantly with personalized details, like the reward's value, current status, and key dates”

Human agent steps in with context

human_review

“Agents could see the full Fin-customer conversation before stepping in, which built trust and ensured every handoff came with context”

Agent flags inaccuracies

feedback_loop

“they built a feedback loop right into Intercom ticket workflows. If an agent spotted an inaccurate or incomplete answer, they could flag it instantly, making it easy to iterate on content and improve Fin's performance”

CX Score evaluates every conversation

ai_action

“CX Score uses AI to evaluate every single conversation for resolution, tone, and sentiment”

Reported outcome

Fin now resolves 64% of queries across chat and email, including complex cashback and reward eligibility questions, and is the first point of contact in 98% of conversations across MoneySuperMarket and Quidco, transforming the most common query type from a manual team effort into an instant, frictionless experience.

Reported metrics

queries resolved by Fin64%

Fin involvement rate (first point of contact)98%

Monthly conversation volumemore than 25,000 conversations a month

resolution time for complex queries before Finhours or even days

Reported stack

IntercomFinFin GuidanceSendSafelyFin InsightsZendesk

Source

https://www.intercom.com/customers/mony-group

Read source ↗

Frequently asked questions

What did this team achieve with this AI workflow?

Fin now resolves 64% of queries across chat and email, including complex cashback and reward eligibility questions, and is the first point of contact in 98% of conversations across MoneySuperMarket and Quidco, transfo…

What tools did this team use?

Intercom, Fin, Fin Guidance, SendSafely, Fin Insights, Zendesk.

What results were reported?

queries resolved by Fin: 64%; Fin involvement rate (first point of contact): 98%; Monthly conversation volume: more than 25,000 conversations a month; resolution time for complex queries before Fin: hours or even days (source-reported, not independently verified).

What failed first in this deployment?

How is this customer support AI workflow structured?

Customer contacts support → Fin resolves customer query → Fin Guidance enforces compliance rules → Fin queries rewards API → Human agent steps in with context → Agent flags inaccuracies → CX Score evaluates every conversation.