How Collecting Rare Coins Can Inspire the Next Generation of InsureTech Innovation

The insurance industry is ready for something fresh. I’ve spent time exploring how new ideas can make claims faster, underwriting sharper, and customer apps actually useful for InsureTech startups. One of the most unexpected sources of inspiration? Rare coin collecting—especially the careful world of PCGS slabbed coins. Who knew that a perfectly graded 1916-D Mercury dime could spark ideas about data trust, modernization, and how we build better insurance tech?

Why Rare Coin Collecting and InsureTech Share a Common DNA

Sure, one’s about history and metal. The other’s about risk and numbers. But at their core, both are about knowing what you’ve got. A rare coin isn’t just “old money.” It’s classified, graded, authenticated, and valued—all with precision. That’s exactly what modern insurance needs: systems that don’t just store data, but understand it.

Think about it: a PCGS slabbed coin comes with a certification number, a grade, and a history. Insurance data should be no different. Policies, claims, and customer behavior shouldn’t sit in dusty databases. They should be trusted, traceable, and meaningful—like a coin you can verify with a quick search.

Grading Systems: From Coins to Claims

When a coin grader looks at a piece, they check luster, strike, wear—sometimes microscopic details. Similarly, a claim shouldn’t be treated the same way every time. A 10-year customer with one accident deserves a different lens than someone with five fender benders in two years.

We can apply the same thinking to claims. Instead of static forms, use dynamic scoring models that consider context. A rare error coin gets special attention—so should a claim with unusual circumstances, like a first-time major loss or an IoT device alert.

Actionable Takeaway: Build a claim health score that evaluates each claim like a grader would a coin, factoring in:

• Claim frequency and severity over the past few years

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• Real-time device data (like dashcams or smart home sensors)

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• How quickly the customer reported it and how they communicated

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• External signals—weather, traffic, fraud patterns

Here’s a basic Python function to get started:

def calculate_claim_score(claim):
score = 100
if claim['frequency_last_3y'] > 2:
score -= 20
if claim['severity'] == 'high':
score -= 15
if claim['reporting_delay_hours'] > 24:
score -= 10
if claim['fraud_risk_score'] > 70:
score -= 25
return max(0, score)

Standardization and Trust: The PCGS Slab as a Blockchain for Insurance

That little plastic slab? It’s not just packaging. It’s a trust stamp. It says: “This coin is real. It’s been checked. Here’s its grade.” In insurance, we need our own version of that.

That means standardized, tamper-proof data envelopes for every policy and claim. No more guessing if the data is clean or complete. Just like a collector types in a PCGS number and gets verified details, a customer or agent should be able to pull up a claim and instantly see its status, risk level, and next steps.

This starts with insurance APIs and shared data formats. Think of it like a universal language for insurance data. Adopt standards like:

• Open Insurance Schema (the insurance version of open banking)

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• ACORD XML for policies and claims
• FHIR-inspired models for health insurance (yes, borrowing from healthcare works)

When data speaks the same language, apps, partners, and customers can all connect—seamlessly.

Modernizing Legacy Systems: Learning from the “Type Set” Approach

Legacy systems? They’re like a coin collection with missing dates, mismatched grades, and no catalog. You know the value is there, but it’s hard to access. The answer isn’t a full reset. It’s a smarter rebuild—one piece at a time.

Incremental Modernization: The “Coin-by-Coin” Strategy

Just like a collector fills a type set gradually, modernize step by step:

1. Start with APIs: Wrap old systems with modern REST APIs. Tools like MuleSoft or Kong can expose core functions—policy lookups, claim submissions—without overhauling the backend.
2. Build a data lake: Gather all data—claim notes, customer photos, IoT logs—into a cloud storage system (AWS S3, Snowflake). This is your new “catalog.”
3. Add microservices: Replace big, clunky modules with small, focused services. Need faster fraud checks? Build a standalone fraud detection service.
4. Train AI models: Use historical data to build underwriting and claims triage tools that get smarter over time.

For example, a claims API that returns:

{
"claim_id": "CLM-2023-4567",
"status": "in_progress",
"grading_score": 82,
"fraud_risk": "low",
"estimated_payout": 12500,
"next_steps": ["adjuster_review", "customer_document_upload"]
}

Now agents, customers, and third parties can access accurate, real-time info—no more chasing emails.

Underwriting Platforms: From Manual to Predictive

Old-school underwriting is like judging a coin by a blurry photo. Slow. Inconsistent. Modern underwriting platforms use data to make better calls—fast.

Think like a coin collector: what makes this piece unique? In insurance, that means looking at:

• Behavioral data: Driving habits, health from wearables
• Environmental context: Flood zones, crime rates, local weather
• Customer history: Claims, policy changes, service calls
• Social signals: Credit, digital footprints (with consent, always)

Use a risk modeling engine that stacks traditional actuarial math with machine learning and live data. A car insurer, for example, could use telematics from a connected vehicle to adjust premiums in real time—just like a collector adjusts the value based on new certification data.

Customer-Facing Apps: The “Show and Tell” Experience

Coin collectors love to share. Photos. Stories. Expert reviews. InsureTech apps should feel the same—personal, interactive, and human.

Key Features of a Next-Gen Insurance App

• Policy “Type Set” View: See all your policies and claims in one place—like a digital coin album.
• Claim Tracking: Real-time updates, document uploads, next steps—like checking a PCGS certification.
• AI Chatbot: Ask questions in plain English: “What’s my deductible for water damage?”
• Photo Claims: Snap a photo of a broken window or dented bumper. Let AI assess the damage and suggest repair shops.
• Community Forum: Share tips, ask questions, learn from others—just like coin collectors do.

A customer uploads a photo of a cracked windshield, gets an instant estimate, and sees a list of local shops. That’s not just convenient—it’s empowering.

API Ecosystems: The “Collector’s Network”

Collectors don’t work in isolation. They use PCGS, NGC, CAC—trusted third parties. InsureTech needs the same.

• Data providers: Carfax, Plaid, Weather.com
• Fraud networks: Shared databases of suspicious claims
• Service partners: Auto shops, contractors, hospitals

Build a partner API marketplace where insurers, startups, and service providers connect securely. Data flows. Trust grows.

Conclusion: Build Trust, One Data Point at a Time

When a collector shows off a rare coin, they’re not just sharing metal. They’re sharing trust—verified, graded, valued by a community. That’s the standard we should aim for in insurance.

Every claim. Every policy. Every interaction. They should be:

• Verified like a PCGS slab
• Valued with intelligent risk modeling
• Shared in a transparent, user-friendly way

The future of insurance isn’t trapped in legacy systems or paper files. It’s in connected, data-smart platforms—where trust is built in, not bolted on.

As an InsureTech builder, I’m not just coding software. I’m helping create a new kind of collection. One where every customer feels like their story—and their risk—is seen, understood, and respected. Just like a rare coin that finally found its rightful home.

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