How map the verifiable credentials needed in business and life events?

Back at Nordea in -99 we tested the slogan – Do not serve your customer! Serve her life events! I even suggested – half in jest – that the bank should organise itself  around life events – not segments or products. It was too early to get data grouped in actionable ways.. but the thinking was rooted.

Now the data for events should be the very starting point when making wallets useful. 

I asked ChatGPT for help and edited a bit. And in Part II how LLM and AI-agents can help.

Part I

1. Anchor Everything in Events, Not Tech

Don’t start from wallets or “what credentials exist.” Start from life and business events that actually trigger the need for verifiable data. Examples:

• Life: Birth, school enrollment, renting a flat, getting married, buying property, child birth,  finding next job, finding next hobby, getting divorced,death in the near family, healthcare,  retirement etc. All by using bank issued identification credentials – on the way to PID
• Business: Company incorporation, opening a bank account, financing, leasing hiring/firing, payroll, invoicing, VAT reporting, cross-border shipping, ESG reporting, currency and credit risk management etc. All by using bank issued identification credentials – on the way to LPID

List these in business and life event clusters (call them ladders where the wallets are the rails and each credential a  rung. 

2. For Each Event, locate the data and Identify Roles and Claims

Ask: Where is the data? Who needs to trust what, about whom, to act?
Example:

• Hiring → Employer needs to trust identity, work permit, diplomas, CVs, bank accounts
• Buying property → Seller needs to trust buyer’s ID, property ID and certificates, financing, planning permits,  signatures
• Shipping goods → Customs needs to trust origin certificate, VAT status, power-to-act credential.

3. Group Credentials into Reusable Building Blocks

You’ll see repetition – general purpose credentials with general purpose wallets —identification, proof of address, representation rights, permits, qualifications etc. Collapse duplicates into reusable credential families:

• Identity & Representation: ID, power-to-act, corporate mandate.
• Legal/Financial: Tax numbers, bank accounts, creditworthiness, insurance.
• Professional/Qualification: Diplomas, licenses, safety training.
• Transaction-Specific: Invoice refs, shipping docs, ESG declarations.

This reveals where the economy of repetition, economy of reuse and economy of scope “learn once, use everywhere” kick in.

4. Map to Wallet Types and Trust Frameworks

Decide where these live:

• Personal Wallets: IDs, diplomas, health, power to act..
• Business Wallets: Company mandates, certificates, ESG proofs…
• Cross-Actor Bridges: Power-to-act (employee representing employer), delegation chains (parent for child, agent for company).

Overlay regulatory anchors (eIDAS2, NIS2, PSD3, ESG, customs codes) to ensure compliance. Much needed by PEPPOL and Data Spaces 

5. Visualize as a Two-Rail Ladder or Matrix

A powerful visual is two vertical rails—personal on the left, organisational on the right—with horizontal rungs for shared events. Place credentials at the rungs where they first appear and reuse them upward. This makes gaps and redundancies obvious.

6. Validate with Real Stakeholders

Reality check with:

• HR/payroll teams for business flows.
• Municipal clerks, banks, insurers for life events.
• Compliance/legal for regulatory must-haves.
• A couple of AI-agent scenarios to stress-test automation readiness.

7. Iterate and Prioritize

Don’t over-engineer. Mark:

• Critical now (e.g., IBAN-credentials for payroll).
• Soon (e.g., ESG proofs for supply chains).
• Future-ready (AI agents signing contracts, post-quantum credentials).

Attack eye-opening (pensioner credential for rebates..) high-reuse, high-pain points first—like power-to-act, e-receipts (Proof of Purchase – PoP) and invoicing—then expand.

Bottom line:
Map events → roles → trust claims → credential families → wallet rails. Keep it visual and reusable. This approach cuts through hype, shows business value fast, and creates a roadmap regulators, enterprises, and AI-agent designers can all rally around.”

Part II

Then I asked how AI-agents could help:

ChatGPT: “AI-agents can turbo-charge the whole credential mapping and usage process instead of adding more noise. Here’s how they can pull real weight:

1. Discovery & Mapping

• Crawl and Cluster Events: Feed them regulations, business process docs, and service catalogs—agents can auto-cluster similar events (“incorporate company” in Estonia vs. “register business” in Germany) and spot common credentials.
• Detect Redundancy: They can flag that five processes all demand proof of address—evidence for standardization.
• Gap Analysis: Compare existing credential catalogs (EUDI wallet schemes, ISO docs) against life/business events and surface what’s missing.

2. Designing Credential Families

• Use large-scale semantic analysis to group related claims (different countries’ tax IDs) into interoperable credential types.
• Propose common data schemas aligned with standards like W3C VC or ISO 18013.

3. Simulation & Stress Testing

• Run “what-if” scenarios: e.g., simulate an SME onboarding with 12 different banks across EU—agents expose bottlenecks and highlight where a single reusable credential would cut friction.
• Model AI-agent-to-AI-agent transactions (e.g., an accounting bot verifying invoices with customs bots) to test real-time trust flows.

4. Automation of Lifecycle Tasks

• Pre-Fill and Request Credentials: When you trigger a life or business event, your agent can pre-fetch what’s needed (“You’re hiring a contractor—here are the three credentials you’ll need to request and where to get them”).
• Delegation Management: Agents can automatically check power-to-act credentials before taking action on your behalf, preventing accidental or fraudulent transactions.
• Continuous Compliance: They can watch for regulation changes and update credential requirements dynamically.

5. Cross-Ecosystem Coordination

• Bridge Personal and Business Wallets: Your personal AI can talk to your employer’s AI to verify representation rights without humans exchanging PDFs.
• Integrate with Data Spaces: AI-agents can request or deliver verifiable data to sectoral data spaces (energy, transport, health) with proper consent and audit trails.

6. Analytics & Policy Feedback

• Aggregate anonymized usage patterns—feeding insights back to regulators or standards bodies about which credentials deliver the biggest impact or where rules are too fragmented.

7. Future-Proofing

• Incorporate post-quantum cryptography or new trust frameworks automatically as they emerge.
• Act as policy-aware negotiators: your agent could negotiate data-sharing terms or insurance premiums based on credentials it can present.

Why it matters:
Without AI-agents, credential systems remain static checklists. With them, you get dynamic, context-aware, self-updating trust flows—exactly what a multi-jurisdictional, real-time economy needs. The payoff is less manual form-filling, fewer compliance failures, and faster cross-border transactions. In other words: agents turn credential mapping from bureaucracy into competitive advantage.