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VP of Claims

Regulatory & Compliance

Enhances✓ Available Now

What You Do Today

Ensure claims practices comply with state regulations — prompt payment laws, unfair claims practices acts, documentation requirements, and market conduct standards. Non-compliance means fines, lawsuits, and reputation damage.

AI That Applies

AI compliance monitoring that tracks claim handling against regulatory requirements by state — payment timing, required communications, documentation completeness.

Technologies

How It Works

The system ingests claim handling against regulatory requirements by state — payment timing as its primary data source. The automation engine executes each step in the process sequence — validating inputs, applying business rules, generating outputs, and routing exceptions to human review queues. The results integrate into the practitioner's existing workflow — presenting recommendations, flags, or automated outputs alongside their normal working context. The compliance culture.

What Changes

Compliance monitors in real time. The AI flags when a claim is approaching a regulatory deadline for payment or communication before the violation occurs.

What Stays

The compliance culture. Regulatory compliance in claims isn't just about deadlines — it's about fair dealing with every claimant. Building that culture requires leadership and accountability.

What To Do Next

This section won't tell you what your numbers should be. It will show you how to find them yourself. Every instruction below produces a real, verifiable result in your organization. No benchmarks, no projections — just the steps to build your own evidence.

1

Establish Your Baseline

Know where you are before you move

Before adopting AI tools for regulatory & compliance, understand your current state.

Map your current process: Document how regulatory & compliance works today — who does what, how long it takes, where the bottlenecks are. You need this baseline to measure improvement.
Identify the judgment points: The compliance culture. These are the boundaries AI won't cross.
Assess your data readiness: AI tools for this area need data to work. Check whether your organization has the historical data, integrations, and data quality to support Compliance AI tools.

Without a baseline, you can't measure whether AI actually improved anything. You'll adopt tools without knowing if they're working.

2

Define Your Measures

What to track and how to calculate it

Time per cycle

How to calculate

Measure how long regulatory & compliance takes end-to-end today, then after AI adoption.

Why it matters

The most visible improvement is speed. If AI doesn't save time, question whether it's adding value.

Quality of output

How to calculate

Track error rates, rework frequency, or stakeholder satisfaction scores before and after.

Why it matters

Speed without quality is just faster mistakes. Measure both.

When to check: Check after 30 days of consistent use, then quarterly.
The commitment: Give new tools at least 30 days before judging. The first week is always awkward.
What NOT to measure: Don't measure AI adoption rate as a KPI. Adoption follows value — if the tool helps, people use it.
3

Start These Conversations

Who to talk to and what to ask

your board chair or lead independent director

Which compliance checks are we doing manually that could be continuous and automated?

They shape expectations for how AI appears in governance

your CTO or CIO

How would our regulator react to AI-assisted compliance monitoring — have we asked?

They own the technology infrastructure that enables AI adoption

4

Check Your Prerequisites

Confirm readiness before you invest

Check items as you confirm them.