You didn’t sign up to be insurance QA leads, let alone review 2 percent of our calls and guess at the other 98 percent.
But that’s exactly what happens in the vast majority of insurance contact centers today.
Meanwhile, 79 percent of customers say they’d switch companies after one terrible customer service interaction.
Which is why this article lists a few things to look for on your next insurance call center software purchase.
By doing this, you can navigate the sales pitches well enough to spot a piece of software that works great even in a highly regulated environment.
The Three Types of Insurance Call Center Software
Insurance call center software is not one product. The stack splits into three layers, and mixing them up leads to double spend or big gaps. Know your layer before you open a single demo.
Type ONE: CCaaS and Traditional Contact Center Platforms
These platforms provide the core routing and telephony capability. Some newer players have integrated modern technologies like AI and voice biometrics into traditional systems. Think NICE CXone, Genesys Cloud CX, Talkdesk, Five9, and Cisco WebEx Contact Center.
These tools focus on handling incoming call distribution and IVR. They often include some rudimentary call recording capabilities along with workforce management functions. Though many vendors claim to integrate AI, users report limitations. Nothing can make up for.
- Five9 offers an excellent experience for outbound dialing scenarios such as call center sales or collections activities. But users have reported experiencing instability (dropped calls) when using this software. Some have also noted seeing their screen break up when they are logged into Five9 on two monitors.
- Talkdesk has great feedback on its cloud-native interface. While Talkdesk users love the overall appearance of the platform, there have been reports of audio codec issues leading to one-way audio situations.
- Both NICE CXone and Genesys Cloud CX take a dominant market share within the enterprise world because of their massive agent scalability capabilities. However, each vendor packages features within very distinct price points ranging from $110 to well over $249 per user per month. Advanced AI and Quality Management offerings are typically found only in the most expensive “top” service suite tiers.
- Amazon Connect throws this convention out the window with usage-based pricing ($0.038/minute for example for voice). With this it creates huge flexibility to your tech team. But also requiring them to build (and maintain!) all of those agent screens and their associated logic flows.
Type TWO: Specialized AI Quality Management and Agent Assist Platforms
Native CCaaS AI often doesn’t have enough depth to handle all these insurance compliance.
That’s where our second market comes in — AI overlays by companies such as Thunai, Observe.AI, Level AI, Cresta, CallMiner, Verint, Calabrio, Balto, and.
They provide AI listening capabilities for your live phone streams via their API or SIP recording fork, but don’t take over routing.
- The Deep Analysis Market (CallMiner /Observe.AI) does scoring of 100 percent of interactions for compliance and conversation intelligence. Companies are using it to figure out what’s causing customer friction.
- The Live Guidance Market (Cresta / Balto), provides real time guidance and behavioral prompts to the live agent during the call.
- Orchestration 2.0 – Thunai also uses this live call data to build a continuous knowledge graph. This allows the tool to handle L1 queries independently (as well as direct humans), in under a second.
The best part of all? Insurers don’t have to rip out their current CCaaS to bring these features aboard.
After all, your existing legacy phone system probably still works just fine (so long as it’s capable of modern media streaming).
Type THREE: Insurance Systems and Connected Data Platforms
The third layer holds the core insurance systems. Salesforce Service Cloud is the main record of customer relationships.
Guidewire, Duck Creek Technologies, and agency management systems run policy admin, billing, and claims. Meaning, call center software is useless if it cannot pull accurate policy data from them.
- Without API Links: Agents hunt for coverage limits and deductibles across split apps. That drives up cost.
- Bad Answers: Manual search also raises the odds of wrong policy info for the insured. In the grand scheme, a wrong answer can create legal risk for the carrier.
- Clean Connections: Strong API links let the AI query live policy and claims data. Agents then spend less time searching and more time helping.
Comparison Table: Insurance Call Center Software at a Glance
Use this table to match each tool to its layer and watch for the main limit.
Insurance Must-Haves for AI Call Scoring
Manual QA reviews a tiny slice of calls, and two supervisors can grade the same call in two ways. AI call scoring software checks every interaction and moves teams from checkbox audits to real conversation intelligence. Use the four checks below to test any vendor.
1. Custom Scorecards by Call Type and Line of Business
Remember a “First Notice of Loss” call is not a billing dispute - your agents need to show high empathy levels with detailed notes about the damages, as well as use of approved mitigation services.
Honestly, traditional out-of-the-box scorecard methods do not work anymore in insurance companies because each part of the industry has unique needs for customer service teams.
For example, here’s what we look at when evaluating an agent’s weighted scoring abilities:
- Do they have weighted scores tailored for their claims handling process? Their policy renewals? Underwriting? Billing Inquiries?
- Do they have pass-or-fail rules where critical compliance violations automatically result in failure? Will a single missed disclosure be able to cover up for bad overall performance by having a good score on average?
- QA Managers – You must build your grading logic using plain language only. It shouldn’t require you to do any code to modify rules.
2. Regulatory Checks (CMS, State Disclosures, Consent Capture)
Insurance calls are subject to strict regulations, making compliance monitoring a financial imperative.
Now, CMS requires that all enrollment-related calls be retained and made searchable for 10 years.
Further, CMS can fine companies up to $48,833 per determination for marketing violations. It doesn’t take much to create a costly problem
The bottom line? Just one missed disclaimer could spell trouble!
- State Disclosures: Each state has an insurance department responsible for enforcing its state’s Unfair Claims Settlement Practices Acts. Before agents bind someone’s coverage, they’re expected to disclose their own licensing status and provide any other required disclosure.
- TCPA Consent: Any outbound call requires prior, express written consent. If you don’t track this properly, you open yourself up to massive class-action lawsuits. For example, Farmers Insurance recently agreed to pay out $2.87M as part of a TCPA suit against them.
- HIPAA: Health calls will fall under HIPAA. If agents capture PHIs (PHI) with card data via an un-encrypted call, carriers would have high liabilities.
- PCI: Healthcare data breach costs on average $10.93 million compared to others, which was the highest among all sectors.
- Audit Trail: Showing every single disclosure and Consent is necessary as per NAIC Rules on AI.
3. Explainable Scores and Calibration Tools
Accountability – This means that insurers retain full responsibility for all decisions made by or with the help of artificial intelligence (AI).
For example, if you use some sort of black box scoring system that just returns whether an interaction failed, then this model won’t work for you.
You need to tie each inference back to a specific line in the call transcript at a timestamp (and be able to prove that).
- Score Justifications - There’s another section where you have to explain what went wrong when there was a critical issue. It also requires you to specify which words from the call caused those errors to surface.
- There are many complaints in places like Reddit and G2 about false positives. E.g., a compliant call got tagged because the agent said a synonym instead of using the exact phrases included in the script
- Human Workflows - QA Managers can now review AI decisions and ensure consistency between humans and AIs evaluating a call.
4. Coverage of 100% of Calls Across Voice and Digital
Sampling creates blind spots where important issues go unnoticed. By offering full-coverage monitoring, we were able to identify missed disclosures, false coverage claims, and misleading sales tactics within both voice and digital channels (email, chat).
For example, Signify Health scaled their QA from 70k manually audited calls per year to 65m+ automated audits annually.
They’ve been able to see into agents’ work and compliance at levels previously impossible with manual reviews. And here are some ways teams can:
- One Scorecard Methodology: Simply put, omnichannel QA. Make sure that digital interactions (call, email, chat) are monitored using the same scorecard methodology within the tool.
- Transcription Quality: Most engines have trouble understanding heavy accents, overlapping conversations, ambient noise, and industry-specific terminology. A poor transcript results in an invalid QA score.
- Real Coverage: Some vendors insist on 100 percent coverage but will batch processes, delaying analytics delivery for up to 24hours. Make sure that your call scoring proof has real-time inference.
In the big picture, it’s about moving past these simple binaries to actually understand the roots of customer friction.
Insurance Must-Haves for Real-Time Agent Assist
Automated QA fixes what went wrong after the call. Real-time agent assist helps while the customer is still on the line.
Done well, in insurance call center software, it cuts handle time and speeds up new agents, as at Signify Health, where proficiency rose 12 percent and sales conversion went from 30 to 34 percent.
1. Answers Grounded in Current Policy Documents With Citations
The biggest risk insurance contact centers face is made-up answers.
An example might be that an assist tool creates some invented coverage exclusion or deductible. This could put the carrier at legal liability risk if they make it public as part of their response.
Every single question from the user needs to be able to trace back to a set of current/approved policy papers for validation. This means our tools need to show their sources instead of guesses.
- RAG Retrieval: With retrieval augmented generation (RAG), we are querying against your knowledge base or policy admin systems during calls (think Guidewire, Duck Creek, and Salesforce Service Cloud).
- Document Citations: The ideal world scenario would also allow you to have specific policy details, such as claims procedures or state-specific billing rules, appear with citations linking to where exactly these policies were found. This helps ensure accuracy and transparency when sharing info with clients.
- Policy limits change over time: How does this system track these changes to make sure that agents are never given old policy limits?
ANY answer with no citation introduces a risk that cannot be audited. Grounded answers ensure agents stay fast and carriers remain safe.
2. Latency and Accuracy During Live Calls
Real time means what you think it does: tips delivered within milliseconds of a user asking them are good.
- Tips delayed by even 5s become distracting because they’re late for the party. Speed matters.
- Secondly, streaming design: batch processing APIs have inherent latency (event-driven solutions like Apache Flink and Kafka allow for audio + LLM inference to be processed in parallel).
- Finally, aim high! We demand sub-200ms latency from our vendors - but there’s a lot of smoke and mirrors out there. You can always test these tools with your own networks to find those end-to-end latencies yourself.
3. Compliance Prompts and Escalation Rules
Compliance Prompts that appear live are our “guardrails.” For instance, if agents begin to misstate a specific Medicare policy or omit a key point about TCPA consent, we automatically pop up a blocker right then.
This also works for all of our required insurance disclosures, HIPAA reminders, and CMS compliance mandates. In other words, you’ll never miss a step due to human error turning into findings.
- Tools should suggest a cross-sell or next-best action: As these alerts only provide suggestions rather than mandates, your agent will be able to continue the conversation without interruption.
- Introduce mandatory blockers: This should prompt your agent to pause until the customer provides the necessary disclosure making sure there’s no way around certain requirements.
- Escalation rules: Vulnerable customers need to be escalated to a human supervisor themselves. You can ask vendors about how they differentiate this or inform managers as soon as this happens.
Integration Checklist
If your favorite call scoring and agent assist tool isn’t integrated into your stack, then you’re out of luck. A survey by Deloitte found that legacy integration was the number one challenge facing contact center leaders. And it’s no shocker! In fact, many IT managers on Reddit complain that call center platforms use opaque APIs and charge steep service fees to sync data between core systems. Test all integrations before signing up - these are tools and systems like:
- Telephony Integration. Ask if the platform takes in media streams through SIP REC, WebRTC, or native APIs from NICE, Genesys, Five9, or Cisco. Webhooks should pass call events in real time.
- Core System APIs. Check if the tool can query policy and claims data from Guidewire through its RESTful system APIs and Swagger UI, or from Duck Creek. In doing so, the tool can power RAG answers with live terms from your AMS and claims management systems.
- CRM Sync. Look for two-way sync with Salesforce Service Cloud, with screen pops based on caller identity. Post-call summaries should write straight into the case file.
- Security and Access. Check that API rate limits can handle peak call volumes. With this, OAuth 2.0 and JWT keep data safe in transit even on your busiest day.
My advice is to ask who builds each link. Heavy services fees can turn a cheap license into a costly project. Ask for a fixed price on every integration.
Security, Privacy and AI Governance Checklist
Insurance centers handle huge volumes of PII, PCI data, and PHI. Sending that data to an unsecured LLM is an existential risk. Healthcare and insurance breaches average $10.93 million. In the grand scheme, a weak security choice can undo every other win.
- HIPAA and BAA. The vendor must sign a Business Associate Agreement. The vendor must also follow HIPAA rules and encrypt data at rest and in transit.
- PII Redaction. The tool must auto-redact PCI DSS data and PHI from audio and text transcripts. Meaning, card numbers and health details never sit in plain view.
- Model Training Limits. Get a binding data agreement. The agreement must say the vendor will not train public or shared LLMs on your calls or customer PII.
- Data Residency and Access. Data should stay in set regions or private cloud sites to meet state privacy acts. With this, role-based access control, data retention rules, and consent management stay in your hands.
- AI Governance. To meet the NAIC Model Bulletin, the platform needs audit logs for each AI decision, score, and response. Humans must stay in the loop.
Measuring Value: The Metrics That Prove ROI
AI quality management takes real money, so set baselines before launch. Mature, AI-centric centers are 85 percent more profitable than legacy peers, per Deloitte. They are also 60 percent more likely to rate employee experience as excellent. Meaning, the payoff shows up in both profit and people.
- QA Coverage: Track the share of calls scored, from 2 percent by hand to 100 percent by AI. Cost per evaluation should fall as coverage grows.
- Score Accuracy and Compliance: Compare AI scores to human baselines and log false positives. In doing so, you build trust, and you set targets like the 98 percent compliance score that Frontline Asset Strategies hit in six months.
- AHT and FCR: AXA Health cut handle time by 60 seconds per call with automated summaries. Value this as seconds saved times hourly agent cost times annual call volume.
- CSAT and Retention: Bamboo Insurance lifted CSAT and NPS by 15 points. In the grand scheme, Trupanion linked standard scoring to 5 percent higher retention.
- Agent Productivity: Agent assist lifted speed to proficiency from 70 percent to 82 percent in one year. Faster onboarding cuts training costs.
Affordable Care shows the top end, with $8 million in added revenue and 2,000 hours saved each month. With this, add in the risk you no longer carry, such as fines for missed disclosures.
25 RFP Questions to Ask Vendors
Generic sales talk hides weak spots. Put these 25 questions in your RFP to pin down real answers on call scoring accuracy, QA coverage, agent assist latency, integrations, compliance, security, pricing, and deployment. Group them by topic so each team can own its part.
AI Call Scoring and Accuracy
- Does your platform score 100% of interactions, or does it sample because of API rate limits?
- How do you show why a score was given, such as timestamped citations in the transcript?
- What is your measured false-positive rate on nuanced compliance disclosures?
Insurance Scorecards
- Can we build custom, weighted scorecards for P&C, Life, and Health lines?
- Do you offer language models trained on insurance terms, such as subrogation and indemnity?
Regulatory Compliance
- How do you spot and redact PCI and PHI in audio and transcripts in real time?
- Do you log Medicare Advantage CMS disclaimers to meet the 10-year retention rule?
Real-Time Agent Assist
- What end-to-end latency do you guarantee for live transcription and prompts, with a target under 200ms?
- Can you tell info nudges apart from mandatory compliance blockers?
- How does the UI stop agent overload when many knowledge articles pop up at once?
Policy Document Retrieval
- Does your RAG setup cite specific internal policy documents to prevent hallucinations?
- How do you handle document versions so agents never see old policy limits?
Integrations and Architecture
- Do you support native media routing and event streaming with our CCaaS, such as NICE, Genesys, or Five9?
- Can you share API docs that show real-time queries to Guidewire or Duck Creek?
- Do you offer two-way sync with Salesforce Service Cloud for automated call summaries?
Security and Governance
- Will you sign a BAA for HIPAA?
- Will our proprietary conversation data or customer PII be used to train shared LLMs?
- Can you share current SOC 2 Type II and ISO 27001 proof?
- Do you provide immutable audit logs of every AI decision to meet NAIC Model Bulletin rules?
Reporting and Analytics
- Do you offer dashboards that blend QA scores, AHT, and CSAT in one view?
- Can supervisors easily calibrate AI scores and override false positives to train the model?
Pricing and Licensing
- Are transcription, custom scorecards, and CRM integrations included, or billed as add-ons?
- Is pricing per agent, per minute, or per interaction, and what are the overage penalties?
Implementation and Support
- What is the average deployment time for a mid-market insurance carrier, and what IT resources do we need?
- After launch, what SLAs guarantee uptime and support response times?
A 30-Day Proof of Value Plan
Never buy contact center software on a demo alone. Run a 30-day proof of value in a secure setup with a small group of agents. Set baseline metrics first, so you can measure real gains. In the grand scheme, a good pilot replaces marketing promises with proof.
- Week 1: Data and Baseline. Pick one high-volume call type, such as FNOL or billing. Gather past recordings, define the scorecards, and log current QA coverage, AHT, and FCR.
- Week 2: AI Call Scoring. Feed the old audio into the platform and run automated scores. With this, you can compare AI scores to human baselines and find the exact rate of false positives and false negatives in compliance detection.
- Week 3: Real-Time Agent Assist. Roll out live assist to a small group of tenured agents, and link it to a clean set of approved policy documents. Measure live response latency and gather agent feedback on distraction.
- Week 4: Results and Decision. Compare pilot results to the Week 1 baseline and work out the QA cost savings. Meaning, you can also flag any CRM integration failures or open security gaps before you sign.
Add the ROI math to the final report. Then write your buy decision on evidence, not hype.
Where Thunai Fits
Thunai is an enterprise AI orchestration and agent assist platform. Thunai does not replace your CCaaS. Instead, Thunai sits on top as a digital labor layer that handles Tier 1 support and boosts human agents. Meaning, insurers skip the rip-and-replace project and keep their phone base.
- Call Scoring. Thunai scores 100 percent of interactions against custom quality and compliance rules. Instant audits flow out of every call.
- Real-Time Agent Assist. During live calls, Thunai shows playbook prompts and policy knowledge right in the agent's workflow. With this, agents stop hunting across tabs, and a streaming design built on IBM Confluent and Apache Kafka keeps latency ultra low.
- Thunai Brain. A continuous knowledge graph ties policy papers and live data together for RAG answers. Conversation intelligence and compliance monitoring feed from that same base.
- Post-Call Automation. Thunai writes case summaries and updates CRMs like Salesforce on its own. In the grand scheme, that wipes out after call work.
Thunai cites 70 to 80 percent deflection rates for Level 1 support. Talonify used Thunai for 100 percent automated legal liability flagging, with a projected $15 million in compliance risk mitigation. Plans start at $7 per agent with a free tier, and self-hosting and strict data residency controls are on offer. On the whole, any advanced AI setup takes initial effort, and Thunai needs legacy databases mapped to its knowledge graph so RAG answers stay accurate.
Want to see Thunai in action? Just click to book a free demo call!
FAQs
What is the best call center software for insurance companies?
There is no single best pick, and the right choice depends on your current setup. If your phone base is failing, a CCaaS leader such as NICE CXone, Genesys Cloud CX, Talkdesk, Five9, or Cisco Webex Contact Center gives you a steady, scalable core. If the phones work fine, a specialized AI quality management platform adds deeper insurance compliance checks and fast agent assist. In the grand scheme, that route skips a multi-year overhaul.
Do I need to replace my CCaaS to add AI call scoring?
No, most AI quality platforms work with any CCaaS. Observe.AI, Level AI, Cresta, CallMiner, and Thunai take in audio and metadata through SIP REC media forking, API connectivity, or secure webhooks. You only need to swap the CCaaS if the old PBX cannot stream audio in real time or if it drops calls. In doing so, you keep your phone base and add the AI layer on top.
How much does call center QA software cost?
Pricing swings by model. CCaaS suites charge per user per month, and AI features often sit in premium tiers of $110 to $249 per agent. Amazon Connect charges by usage, such as $0.038 per minute for voice. Meaning, AI overlays mostly use custom contracts, though Thunai lists plans from $7 per agent. Watch for vendors that charge extra for features like screen recording or basic API integrations. Total cost of ownership should count transcription, scorecards, and CRM links.
How long does it take to deploy AI QA and agent assist?
Basic historical call ingestion and simple transcription can run in days. A full enterprise rollout takes several weeks to months. That covers telephony media routing, Guidewire API links, scorecard configuration, calibration, InfoSec approvals, BAA signing, and agent training. In the grand scheme, clean policy da
