Who’s it for:

• Banking, credit union, and insurance QA leaders tasked with balancing compliance and CX
• Supervisors under pressure to meet regulatory standards without slowing service
• Executives seeking to reduce fraud risk and avoid costly enforcement actions
• Contact center managers needing actionable coaching insights, not just dashboards

Recap and Review

In this session, Mark Ezzell (AmplifAI) and Kotei Kotey (CMP Research) unpacked why financial services contact centers can no longer rely on manual QA or “do-it-yourself” approaches. With regulatory risk, fraud prevention, and compliance requirements shaping every interaction, Auto QA powered by AI offers the scale and precision needed to protect both customers and institutions.

The discussion traced the evolution of QA in financial services—from manual monitoring in the early 2000s to the compliance-heavy era post-financial crisis, and now to AI-driven QA that evaluates 100% of interactions, closes compliance gaps, and enables coaching that protects revenue and reputation.

Key topics included:

• Why compliance is the #1 differentiator in banking and insurance CX
• The role of Auto QA in fraud prevention and risk mitigation
• How AI enables real-time feedback loops for frontline coaching
• The impact of AI on time-to-proficiency and agent retention
• Best practices for starting Auto QA in finance with measurable outcomes

5 Takeaways That Matter

1. Compliance Isn’t Optional—It’s Survival

Financial services carry stricter regulations than any other industry. Missed disclosures, mishandled disputes, or improper collections don’t just harm CX—they trigger fines, consent orders, and reputational damage. AI-enabled Auto QA ensures compliance checks on every call, every time.

2. Fraud Prevention Starts with Frontline QA

Every customer interaction is a potential fraud risk. Auto QA lets you validate identification processes, detect gaps, and catch systemic failures before regulators do. This transforms QA from a sample-based audit into a fraud shield across 100% of interactions.

3. AI Accelerates Time-To-Proficiency

‍Turnover is costly. By surfacing what “good” looks like and feeding real-world examples into coaching and training, AI dramatically reduces time to proficiency—getting new agents compliant, confident, and effective faster.

4. QA Data Must Connect to Coaching—Not Just Reporting

Manual QA produces reports. Auto QA + AI produces actions. By operationalizing insights into daily coaching tasks, leaders can focus on the highest-risk behaviors and agents, preventing errors instead of reacting to them months later.

5. Most Financial Institutions are More Ready than They Think

You already have the raw material—call recordings, transcripts, and compliance forms. The next step is layering AI on top. Starting with a specific compliance or fraud challenge (like disclosure accuracy or credit dispute handling) ensures fast wins and builds confidence in scaling.

Resource Download

CMP Research Report

Download the CMP Prism Report on AutoQA vendors to see where AmplifAI stands out.

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🎙️ Final Quote ‍

“In finance, every call is a compliance risk. Auto QA plus AI doesn’t just identify issues—it closes the loop by coaching agents on the behaviors that keep customers loyal and institutions protected.”

— Mark Ezzell, VP Customer Success, AmplifAI

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