Industry Solutions

Financial Services client experience

Trust is the KPI examiners measure.

Banks, credit unions, and fintechs balance member experience with intense regulatory scrutiny. We design AI programs that pass examiner review, protect cardholder data, and reduce fraud handle time — without eroding member trust.

Typical outcomes
Financial Services engagements
32%
Handle time reduction
0
PCI scope expansion
45%
Dispute automation
100%
SR 11-7 coverage
Where it hurts

Financial Services-specific challenges

The pain points we hear most from financial services leaders — and the regulatory context that shapes every decision.

Fraud & dispute volume

Rising card-not-present fraud drives handle-time spikes and CFPB complaint risk.

PCI scope creep

Any AI touching PAN, CVV, or authentication data expands audit scope dramatically.

Reg E & UDAAP exposure

Automated decisions on disputes, disclosures, or account access invite examiner findings.

Model risk management

SR 11-7 and analogous frameworks require documented governance for AI models in production.

Authentication friction

KBA is failing; voice biometrics and behavioral signals need careful rollout to avoid discrimination claims.

Fintech partner risk

Sponsor banks are on the hook for their fintech partners' contact-center AI decisions.

Compliance & regulatory context
PCI-DSS 4.0GLBA / Reg PReg E, Reg Z, Reg CCSR 11-7 model riskCFPB UDAAPSOC 2 Type II
Our approach

Solutions tailored to financial services

KPI-first, vendor-neutral, and built to survive audit — not just the pilot.

01

AI risk & KPI baseline

Handle time, first-call resolution, fraud false-positive rate, and complaint volume — measured before tooling.

02

PCI-safe voice architecture

DTMF suppression, tokenization, and BAA-equivalent contracts to keep AI out of PCI scope.

03

Model governance framework

SR 11-7-aligned documentation, monitoring, and human-in-the-loop controls for every model.

04

Fraud & dispute automation

Intent detection, evidence gathering, and Reg E-compliant workflows that shorten cycle time.

Case in point

Mid-size credit union — 800K members

A credit union faced examiner concerns about fraud handle times and Reg E compliance gaps. We designed a fraud-triage virtual agent, established SR 11-7-aligned governance, and rolled out agent-assist across 220 member service reps.

32%
Handle time reduction
45%
Dispute automation
Zero
Exam findings

Our examiners actually complimented the governance documentation. That's not something I ever expected to say about an AI project.

Chief Risk Officer, Regional Credit Union

Composite example based on typical engagements. Details anonymized.

Every engagement begins with a KPI baseline, not a product demo.

Ready to design for financial services KPIs?

A 45-minute session with a senior advisor. No sales pitch — just your metrics, your constraints, and where AI actually fits.