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Industries / Financial Services

You cannot sample your way out of a compliance problem.

In financial services, the call nobody reviewed is the one that becomes a finding. QEval scores every banking, lending, and collections interaction for disclosure, suitability, and sentiment, at an accuracy you can put in front of a regulator.

$2.8M
Annual savings
At one mid-size US bank
100%
Of calls scored
94,583 calls, not a sample
33%
Lower auto-fail rate
From 4.2% to 2.8%
5.1 mo
Payback
On the program investment
The shape of the problem

What a banking call actually carries.

01

You cannot sample for a regulator

A 2% manual sample is not evidence. When an examiner asks whether a disclosure was given, "we checked some calls" is not an answer. The unreviewed call is the one that becomes a finding.

02

Disclosures and scripts drift

Mini-Miranda, recorded-line notice, fee and rate disclosures, right-party contact. The wording slips on busy days and across sites, and you find out in an audit, not in time to fix it.

03

Repeat contacts become complaints

The same caller, the third time, on the same fee. Frustration that no one flagged turns into a CFPB complaint or a closed account. The signal was on the call the first time.

04

Revenue is left on the call

Cross-sell pitched at the wrong moment annoys customers; the right offer never gets made. Suitability and timing decide whether an offer is growth or a grievance.

On one call

What QEval hears on a single banking call.

One routine fee-dispute call. This is the difference between a 2% sample and every call.

Transcript Card servicing
Agent

Thanks for calling, this is Alex. Before I pull up the account, can you read me the full sixteen digit card number?

Customer

Sure, it is four... wait, again? This is the third time I have called about this same late fee.

Agent

Let me take a look. I do see the fee on the account here.

Agent

I can waive it one time as a courtesy, no problem.

Agent

While I have you, you would be a great fit for our Platinum cash back card. Want me to add it?

Customer

No. I just want this fixed.

Agent

Done. Anything else? Have a good one.

C+
Predicted CSAT
Low
Churn risk
High
Compliance58
Empathy72
Resolution78
Brand voice70
AI Coach

Lead with empathy on repeat contacts, never request the full card number on a recorded line, and hold the cross-sell until the issue is resolved.

Illustrative call. Not a real customer interaction.
What changes when QEval is applied

The same calls, finally read in full.

Layer 1 - Compliance

Disclosure and PCI detection on every call

Mini-Miranda, recorded-line notice, and fee disclosures are checked across 100% of interactions at 95%+ recall, and full card numbers are caught and redacted at ingest.

Compliance and redaction →
Layer 2 - Customer

Complaint and churn risk, while you can still act

Repeat contacts, rising frustration, and confusion are scored on every call and surfaced before they become a CFPB complaint or a closed account.

Customer intelligence →
Layer 3 - Revenue

Suitable offers at the right moment

QEval reads whether an offer was suitable and well-timed, so cross-sell becomes growth instead of a grievance. One financial services provider grew revenue $4M in a year.

Revenue intelligence →
Layer 4 - Operational

Why customers keep calling back

Repeat-contact drivers and handle-time outliers are clustered automatically, so you fix the policy or the script, not just the symptom.

Auto QA →
Layer 5 - Training

Coaching tied to the exact moment

When a disclosure is missed, the coaching points to the second it happened. Evidence-based coaching is the documented source of large QA-score gains.

Coaching and performance →
Data layer

Your data never leaves to an outside model

PII and account data are redacted before any model runs, and the Mixture-of-Experts model is built and run operated in-house. Nothing trains a third-party AI.

Security and trust →
Sector case study

A mid-size US bank ran QEval across 94,583 contact-center calls, scoring 100% of them instead of the small sample its team could review by hand. QEval classified call drivers across 52,161 calls and gave the bank coverage of 69% of why customers were calling, including 14% of contacts tied to card declines and 15% to digital friction the bank had not seen.

Within the program, the auto-fail rate fell from 4.2% to 2.8%, repeat contacts dropped 34.5%, and negative sentiment fell 43.8%. The documented result was $2.8M in annual savings with a 5.1-month payback on the investment. Outcomes attribute to the organization, anonymized at the bank's request.

$2.8M
Annual savings
-34.5%
Repeat contacts
-43.8%
Negative sentiment
69%
Call-driver coverage
Compliance and regulatory notes

What QEval helps you evidence.

QEval® documents adherence across every interaction, surfacing risk and recording the evidence your compliance team relies on. It is not a substitute for legal counsel

PCI DSS

Full card numbers caught and redacted at ingest via Named Entity Recognition, before storage. PCI DSS Level 1 scoped to the redaction pipeline.

FDCPA / Reg F

Mini-Miranda and required collection disclosures checked on 100% of relevant calls, with the transcript moment attached as evidence.

TCPA

Recorded-line notice and consent language flagged when missing, across every call rather than a sample.

UDAAP

Unfair or misleading language and suitability of offers scored, so fair-treatment risk surfaces before a complaint does.

GLBA

Customer data redacted before any model processing, and never sent to a third-party foundation model's training loop.

Complaint handling

Complaint signals detected and routed in real time, with a full audit trail from score to the exact words that triggered it.

SOC 2 Type IIISO 27001ISO 42001PCI DSS Level 1HIPAAGDPRCCPA

QEval surfaces, scores, and documents adherence to your policies and applicable regulations. It does not provide legal advice, and the regulations named here are illustrative of what QEval helps you monitor, not a complete compliance checklist.

Built on the Six Layers

Financial services leans hard on four of the six.

Quality and compliance is the floor. The value compounds in customer, revenue, and operational intelligence, all read from the same calls.

L1 Quality and Compliance L2 Customer Intelligence L3 Revenue Intelligence L4 Operational Intelligence
See all Six Layers →
For financial services

Questions compliance and ops ask.

Is the 95%+ accuracy something we can show an examiner?

Yes. 94%+ classification accuracy is a contractual SLA, and every score carries an audit trail back to the transcript moment that produced it. On flagged compliance violations specifically, recall is 95%+ at 98%+ accuracy, and every interaction is reviewed, not a sample.

Where does our customer and account data go?

Nowhere outside QEval. PII and card data are redacted at ingest through Named Entity Recognition, before any model runs, and the Mixture-of-Experts model is built and operated in-house. Your data never enters a third-party foundation model's training loop.

We already have QA from our CCaaS. Why add QEval?

CCaaS-native QA typically scores a small sample at 65 to 70% accuracy. QEval scores 100% of calls at the 94%+ contractual SLA and reads beyond compliance into churn, revenue, and operational drivers, where most of the value sits.

How fast can this be live?

30-day deployment, contractual. The mid-size US bank above saw a 5.1-month payback, and the documented customer-average is ROI in 120 days, with 60-day exit rights.

Financial services

Bring us one week of your calls.

We will score a real sample of your banking, lending, or collections calls and show you the disclosures, the complaint risk, and the revenue your current program is not catching.

Contractual commitments

Four numbers no peer publishes.

94%+
Accuracy SLA
Written into the master agreement
30 days
Deployment
Money-back guarantee
60 days
Exit clause
Cancel with notice, no penalty
120 days
ROI
Documented customer-average outcome