Leading finance organisations face mounting call-centre costs—driven by high agent turnover, lengthy IVR wait times, and strict PCI compliance overhead—that hurt both budgets and customer experience. This case study explores how sub-300ms voice agents automated high-volume inquiries end-to-end, slashing operating costs by 46% while maintaining audit-ready compliance. By handling 85% of calls without human intervention and cutting response times from minutes to under 30 seconds, the solution delivered a 720% first-year ROI and boosted customer satisfaction by 25 points. One deployment even eliminated plans to hire 2,000 additional representatives, proving AI voice automation can deliver enterprise-scale savings without compromising service quality.

Case Study Source: Retell AI

Problem Statement

Finance organisations are spending heavily on call centres to handle routine queries, while legacy IVR latency and stringent PCI obligations erode customer satisfaction and drive operating costs up.

Goal

Deploy sub-300ms, PCI-compliant voice agents to automate high-volume finance calls, cut call-centre spend by 30–40%, improve resolution speed and CSAT, and keep audit-ready compliance in place.

Challenges

Legacy IVR delays of **800–1200 ms** cause frustration and high abandonment.

A large share of costs tied to people and churn: agent pay **$35k–$50k** per FTE, onboarding **$8k–$12k** per hire, and **75%** annual turnover.

Maintaining PCI DSS compliance requires extra tools, audits, and strict access controls.

Reliability and latency risks from external API dependencies can degrade call quality at enterprise scale.

Speech-recognition accuracy varies with accents, dialects and background noise.

Actions

Mapped 3–6 months of call data to identify top reasons, costs per interaction, and compliance needs.

Built voice agents using a no-code approach and configured core workflows (ID verification, balance checks, PCI-safe payments, dispute intake).

Integrated with existing telephony and back-end systems (e.g., SIP/Twilio/Vonage, CRMs, core banking APIs) without replacing current infrastructure.

Enabled real-time transcription, sentiment monitoring, consent logging and audit-ready reporting for PCI.

Set escalation rules and warm transfers so complex or high-value cases reach human agents with full context.

Piloted with 10–20% of traffic, then iterated on latency, dialogue flows and escalation triggers before scaling.

Impact:

Sustained cost-out of **30–40%** on call-centre spend through always-on automation and instant scaling.

Friction-light service supports higher completion rates; research cited indicates a **25%** uplift in transaction volume.

Headcount plans dramatically reduced; one organisation scrapped plans to hire up to **2,000** representatives.

Automating Finance Call Centres: A Case Study

Financial institutions have long struggled with ballooning call centre costs. Routine enquiries tie up expensive resources, whilst outdated phone systems frustrate customers and push up operating expenses. The challenge is made worse by strict payment card security rules that demand constant monitoring and extra tools.

The Core Problem

Old interactive voice response systems lag by nearly a second before responding. That delay alone drives many callers to hang up. Meanwhile, the human cost is eye-watering. Each agent earns between $35,000 and $50,000 a year. Bringing a new hire up to speed costs another $8,000 to $12,000. With three-quarters of staff leaving every year, the recruitment treadmill never stops.

Add in the burden of maintaining card payment standards, managing unpredictable external data feeds, and dealing with patchy voice recognition across accents, and it’s clear why satisfaction scores sag whilst bills climb.

A Clear Objective

The aim was simple: build voice assistants that respond in under 300 milliseconds, meet all compliance requirements, and handle the bulk of incoming calls. Success would mean trimming call centre spending by a third to two-fifths, speeding up resolution, and keeping audit trails intact.

How They Did It

The team started by reviewing six months of call records. They identified which questions came up most often, what each interaction cost, and where security rules mattered most. Armed with that insight, they built automated agents using drag-and-drop tools—no coding required. The agents handled identity checks, balance requests, secure payments, and dispute logging.

Crucially, the new system plugged into existing phone networks and banking platforms. There was no need to rip out legacy infrastructure. Real-time transcripts, mood tracking, and consent records kept everything audit-ready. The system was smart enough to pass tricky or high-value calls straight through to a person, along with everything the bot had already learned.

Before going live across the board, they tested the setup on a tenth of all calls. Over several weeks they fine-tuned response times, conversation flows, and handover rules.

What Changed

Costs fell sharply. When the numbers were run, total annual spending—salaries, training, systems, and compliance—dropped by 46%.

Payback came fast. The investment paid for itself in just six weeks, delivering a 720% return in the first year.

Automation took over. In one rollout, 85% of calls were resolved without any human stepping in.

Speed improved dramatically. Average response times shrank from two or three minutes down to under 30 seconds.

Customers noticed the difference. Satisfaction scores jumped by 25 points once the faster, smoother service went live.

The Bigger Picture

The sustained savings—between 30% and 40% of call centre budgets—come from round-the-clock availability and instant capacity when demand spikes. Smoother interactions also encourage people to complete more transactions; research cited in the project suggests a 25% lift in completed business.

Perhaps most striking is the effect on hiring plans. One organisation cancelled a recruitment drive for 2,000 new agents, confident that automation could handle the load. That shift frees capital and management attention for higher-value work, whilst customers enjoy faster, more reliable service.