AI in Insurance: 7 Compliance Tips for 2024

AI is transforming insurance, but with great power comes great responsibility. Here's what you need to know to stay compliant in 2024:

1. Know the rules: Keep up with AI laws like NAIC Model Bulletin and EU AI Act
2. Protect customer data: Follow GDPR, CCPA, and other data protection laws
3. Use AI responsibly: Check for bias and keep humans in the loop
4. Track AI models: Maintain an inventory of all AI systems
5. Spot and fix bias: Regularly test for fairness in AI decisions
6. Explain AI decisions: Make your AI choices clear to customers
7. Keep checking and updating: Set up ongoing compliance audits

Why care? Breaking AI rules can cost you up to 6% of global revenue. But using AI right can cut claims costs by 30%.

Quick Comparison:

Compliance Area	Key Action	Potential Risk
Regulations	Stay updated	Fines, legal issues
Data Protection	Encrypt, limit access	Data breaches
Fairness	Test for bias	Discrimination claims
Transparency	Explain AI decisions	Customer distrust
Governance	Regular audits	Regulatory scrutiny

Bottom line: AI in insurance is powerful but needs careful handling. Stay ahead of the rules to avoid pitfalls and reap rewards.

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How This Article Works

We're breaking down AI compliance for insurance companies into 7 key areas. Here's what you'll get:

• Q&A format covering essential AI compliance topics
• Practical advice and real-world examples
• Expert insights to shape your AI strategy

This approach helps you quickly grasp AI compliance basics for 2024, whether you're new to AI or fine-tuning your existing approach.

For example, in our data protection section, we'll tackle questions like:

"How can insurers meet GDPR requirements when using AI?" "What security measures are must-haves for AI systems?"

We'll answer based on current rules and what works best in the industry.

"Inaccurate or biased algorithms can be problematic when they're populating a social media feed, but things get much more serious when they're deciding whether or not to give out a loan or deny an insurance claim." - Usama Fayyad, Institute for Experiential AI at Northeastern University

This quote nails why getting AI compliance right in insurance is so crucial. We'll keep this high-stakes context in mind throughout the article.

Know the Rules

The insurance industry is diving into AI, but it's not a free-for-all. Here's what you need to know about AI regulations in insurance for 2024:

Key AI Laws in Insurance

1. NAIC Model Bulletin

The National Association of Insurance Commissioners (NAIC) dropped a new Model Bulletin in December 2023. It's a roadmap for using AI while sticking to existing laws.

What's the deal?

• Balances innovation and consumer protection
• Aims to stop unfair bias in AI
• 13 states are on board, including Alaska, Connecticut, and Illinois

2. State-Specific Rules

States aren't waiting around. They're making their own AI rules:

• Colorado: New life insurance rules for external data and algorithms (as of November 14, 2023)
• California: Tackling racial discrimination in insurance (Bulletin 2022-5)
• New York: Guidelines on AI in underwriting and pricing (Insurance Circular Letter No. 7)

3. EU AI Act

Agreed on December 8, 2023, this act is a big deal. It labels AI systems that influence insurance decisions as high-risk. That means strict compliance.

4. Local Laws

Even cities are getting in on the action. New York City's Local Law 144 requires bias audits for AI in hiring. This could affect how insurers hire.

"Regulators will expect insurers to take appropriate steps and measures to control and mitigate those stated risks." - NAIC

What You Need to Do:

1. Stay Sharp: Rules are changing fast. Keep an eye on your state's insurance department.

2. Brace for Oversight: Expect more scrutiny on AI in claims, underwriting, and fraud detection.

3. Get Your AI House in Order: Create a written plan that covers:

   • How you'll follow existing insurance laws
   • Your risk management strategy
   • How you'll audit yourself

4. Watch Washington: The SEC proposed new rules on predictive data analytics in July 2023. Similar federal rules might hit insurance soon.

2. Protect Customer Data

In the AI insurance world, data protection isn't just smart—it's the law. Here's how to stay compliant:

Meeting Data Protection Requirements

1. Know Your Laws

US laws are a mix:

• GLBA for financial services
• CCPA in California
• State laws like New York's SHIELD Act

Europe? It's all GDPR.

2. Privacy by Design

Build protection into your AI:

• Collect only what you need
• Store it safely
• Use it as promised

3. Lock It Down

Encrypt data in motion and at rest. Use strong access controls. Audit regularly.

4. Be Open

Tell customers what data you're collecting and why. Get consent before use.

5. Mind Your AI

AI learns from data. Once it's trained, you can't "untrain" it.

6. AI as a Helper

AI can boost your protection:

Tool	Function
Encryption Automation	Auto-secures data
Access Control	Manages viewing rights
Data Anonymization	Hides personal info

7. Breach Plan

Have a solid plan. Most laws give you 72 hours to report a breach.

"Balancing tech advancement with rights protection creates trust in AI." - Martin Davies, Drata

Breaking these laws? It'll cost you. GDPR fines hit €20 million or 4% of global turnover—whichever's worse.

Follow these tips to use AI while keeping customer data safe.

3. Use AI Responsibly

AI is changing insurance fast. But it comes with risks. Here's how to use AI fairly:

Making AI Fair and Responsible

1. Check for Bias

AI can pick up human biases from data. This can lead to unfair outcomes.

An AI might charge higher premiums to certain groups without good reason. To avoid this:

• Use diverse data sets
• Test AI models regularly
• Look for odd patterns in decisions

2. Keep Humans in the Loop

AI shouldn't make all choices alone. Human oversight helps catch issues.

"This isn't just about identifying disparities; it's about taking actionable steps to address them." - Luba Orlovsky, Principal Researcher at Earnix

3. Be Open About AI Use

Tell customers when AI affects them. Explain how it works simply.

4. Follow the Rules

AI laws in insurance are growing. Stay up-to-date:

Location	Key Regulation
US	Varies by state
EU	GDPR
Australia	Consumer Data Right (CDR)

5. Use AI to Boost Fairness

AI can help spot unfair practices too. Use it to:

• Find hidden biases in pricing
• Ensure consistent claim handling
• Improve risk assessment accuracy

6. Plan for Problems

Have a clear process to fix AI mistakes. Be ready to:

• Pause AI systems if needed
• Review and correct decisions
• Update models quickly

7. Work with Others

Team up with experts, regulators, and other insurers. Share best practices for ethical AI use.

Fair AI builds trust. Trust keeps customers. It's good for business and the right thing to do.

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4. Keep Track of AI Models

Managing AI models is crucial for insurance companies. Here's how to do it:

Managing AI Models

To stay on top of your AI systems:

1. Create an AI inventory

List all your AI models:

Model Name	Purpose	Data Sources	Version	Last Update
ClaimBot	Process claims	Customer forms, policy database	2.3	2023-11-15
RiskAssess	Underwriting	Credit scores, health records	1.7	2023-12-01

2. Document everything

Keep clear records of how each model works, what data it uses, and who's in charge.

3. Use version control

Track changes to your AI models. It helps you roll back if needed and see how the model has evolved.

4. Make an audit trail

Record who made changes, when, and why.

5. Set up governance

Create a team to oversee AI use. They should check for legal compliance, bias, and decision-making sense.

6. Keep it searchable

Use a system where you can easily find info about your AI models. It's handy for regulatory questions, explaining decisions, or updating models.

7. Stay up to date

AI laws change fast. Make sure your tracking system can adapt to new rules.

"The NAIC Model Bulletin requires insurers to develop, implement, and maintain a written program for the responsible use of AI Systems that make or support decisions related to regulated insurance practices." - National Association of Insurance Commissioners (NAIC)

5. Spot and Fix Bias

AI bias in insurance can hurt customers. Here's how to tackle it:

Reducing AI Bias

1. Check your data

Look for hidden biases in your training data. Life insurers often use BMI as a risk factor, but the American Medical Association says it might not work for everyone.

2. Test for fairness

Use these methods to spot bias:

Method	How it works
Equality of opportunity	Do qualified applicants have equal chances, regardless of group?
Disparate impact	Do decisions affect some groups more than others?

3. Try different approaches

Approach	Description
Fairness through unawareness	Remove sensitive info (race, gender) from AI input
Fairness through awareness	Include sensitive data but ensure fair treatment across groups
Counterfactual fairness	Change one factor (e.g., zip code) to see its impact
Adversarial debiasing	Use a second AI to spot bias in the main model

4. Get outside help

Hire a third party to check your AI for bias. They might spot issues you've missed.

5. Keep humans in the loop

Have people review AI decisions, especially for big choices like claim denials.

6. Document everything

Record how you test for and fix bias. It helps with compliance and improving your process.

7. Stay updated on rules

New laws are coming. Colorado now requires insurers to prove their AI doesn't discriminate unfairly.

"If you're using a data variable and there are questions about whether it has a discriminatory impact, it's important for the insurance company to consider … and to have appropriately tested and vetted the algorithm." - Chuck Bell, Advocacy Programs Director at Consumer Reports

6. Explain AI Decisions

AI in insurance can be a black box. But regulators and customers want to know how it works. Here's how to make AI choices clear:

Making AI Understandable

1. Use simple models when possible

Start with easy-to-explain models like decision trees. They show how choices are made.

2. Break down complex models

For trickier AI:

• Use LIME to explain individual predictions
• Apply SHAP to show how each factor affects outcomes

3. Show the math

Here's how different factors impact decisions:

Factor	Impact on Premium
Age	+5% per decade
BMI	+2% per point
Smoker	+50%

4. Speak human

Ditch the tech talk. Explain AI choices in plain English.

5. Be proactive

Tell customers upfront that AI helps make decisions. Explain how it works before they ask.

6. Offer appeals

Let customers challenge AI decisions. Have humans review edge cases.

7. Document everything

Keep clear records of how your AI works. It helps with audits and builds trust.

In March 2023, Colorado's Insurance Division drafted rules requiring life insurers to prove their AI doesn't discriminate unfairly. This shows the growing push for explainable AI in insurance.

"The public wants two things from insurance regulators. They want solvent insurers who are financially able to make good on the promises they have made, and they want insurers to treat policyholders and claimants fairly." - National Association of Insurance Commissioners (NAIC)

7. Keep Checking and Updating

AI moves fast. So do the rules. Here's how to stay on top of AI compliance in insurance:

Regular Compliance Checks

Set up an AI governance team. Include people from legal, tech, and business units. They'll be responsible for AI compliance.

Create an AI inventory. List all your AI systems and update it regularly. Know what each system does and how it affects customers.

Don't wait for problems. Check your AI systems often:

Audit Type	Frequency	Focus Areas
Internal	Quarterly	Data usage, model performance, bias detection
External	Annually	Regulatory compliance, ethical standards
Ad-hoc	As needed	New regulations, system changes

Keep an eye on new rules. The EU AI Act is coming. New York's DFS issued guidance in July 2024. More changes are likely.

Document everything. New York State wants detailed records of your AI systems. Be ready to show your work.

Check your AI models at least yearly. Look for bias, errors, and compliance issues.

Set up a system to handle AI-related complaints. Address issues quickly.

Review and approve your AI policies yearly. Make sure they match new laws and best practices.

If you use third-party AI, check that they follow the rules too. You're responsible for their compliance.

Think ahead. Colorado's new AI rules for insurers kick in fully in 2024. Other states might follow.

"The public wants two things from insurance regulators. They want solvent insurers who are financially able to make good on the promises they have made, and they want insurers to treat policyholders and claimants fairly." - National Association of Insurance Commissioners (NAIC)

AI compliance isn't a one-time thing. It's ongoing. Stay vigilant, and you'll stay compliant.

Wrap-up

AI is changing insurance. But it's not all smooth sailing. Here's a quick look at 7 compliance tips for 2024:

1. Know the rules: Keep up with AI laws.
2. Protect data: Boost your data governance.
3. Be responsible: Focus on fairness and ethics.
4. Track AI models: Keep an inventory of your AI tools.
5. Fix bias: Check and address biases regularly.
6. Explain decisions: Make AI decision-making clear.
7. Keep updating: Set up ongoing compliance checks.

Why care? The stakes are high. The NAIC introduced AI Principles in 2020 and a Model Bulletin in 2023. Ignoring these isn't an option. The EU's AI Act can fine you up to 6% of global revenue for non-compliance.

But it's not all bad news. AI can cut claims processing costs by up to 30%. It's a game-changer if you use it right.

Key points:

• Set up an AI governance team
• Document everything
• Check your AI systems often

Check Type	How Often	What to Look For
Internal	Every 3 months	Data use, model performance, bias
External	Yearly	Following regulations, ethical standards
As-needed	When things change	New rules, system updates

Bottom line: AI in insurance is powerful, but needs careful handling. Stay ahead of the rules to reap rewards and dodge pitfalls.

FAQs

What AI can do for the insurance industry?

AI is shaking up insurance in big ways:

1. Underwriting

AI crunches tons of data to nail down risk. Take life insurance: it sifts through medical records and personal info to predict chronic disease chances.

2. Claims processing

AI chatbots can handle claims faster. But here's the catch: people don't trust them much yet. Accenture found only 12% of customers trust automated web services for claims, and a measly 7% trust chatbots.

3. Fraud detection

AI spots fishy patterns humans might miss, catching potential fraud more easily.

4. Customer service

AI chatbots tackle simple questions, freeing up humans for the tricky stuff.

5. Marketing

AI digs into customer data to cook up personalized campaigns and product suggestions.

6. Risk assessment

AI mixes satellite images with geo-factors to figure out natural disaster risks for policies.

But it's not all smooth sailing. AI can mess up with biased algorithms or decision-making blunders. Some companies, like Armilla Assurance, now offer coverage for AI risks.

As insurance companies jump on the AI bandwagon, they need to watch their step. The EU AI Act is coming in 2024, and it'll affect AI use worldwide. Break the rules, and you could face fines up to €36 million or 7% of yearly turnover - whichever hurts more.

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