Status: Planned (Enabled through adversarial disputes with predefined rulesets)
The core problem with micro-insurance
Micro-insurance is designed to cover:- small financial losses,
- short-term risks,
- high-frequency events,
- users with limited access to traditional insurance.
The smaller the claim, the harder it is to resolve fairly.Why?
- Traditional claim reviews are expensive.
- Human adjusters don’t scale for 300 claims.
- Automation alone can’t handle edge cases.
- Users feel ignored or unfairly rejected.
- auto-approve everything (risking abuse), or
- auto-reject everything unclear (destroying trust).
Real-world micro-claim scenarios
These cases happen every day:- Flight delay insurance with disputed delay times.
- Delivery insurance for lost or damaged packages.
- Weather-based insurance with unclear local impact.
- Device insurance with ambiguous damage causes.
- Gig-economy insurance for short jobs or shifts.
- Parametric insurance where conditions partially trigger.
but the trust impact is huge.
Why traditional insurance logic breaks down
For micro-claims:- Manual review costs more than the payout.
- Centralized decisions feel opaque.
- Appeals are slow or non-existent.
- Users assume bias toward the insurer.
- Low trust → high churn
- High churn → stricter automation
- Stricter automation → more rejected claims
The missing layer: scalable, neutral judgment
Micro-insurance doesn’t need perfect accuracy.It needs fair, explainable decisions at low cost. Justly introduces a middle layer between:
- fully automated payouts, and
- expensive human adjusters.
- disputes are rare but resolvable,
- decisions are transparent,
- costs stay proportional to claim size.
How Justly fits into micro-insurance systems
Justly acts as an on-demand dispute resolver. Typical flow:- A claim is submitted.
- The system auto-processes it.
- If the claim is disputed, it is escalated to Justly.
- Evidence is submitted (photos, receipts, timestamps, sensor data).
- Independent jurors review the case.
- A ruling is issued.
- The payout contract executes the decision automatically.
No back-and-forth emails.
No black-box decisions.
Example: delivery micro-insurance
- A user insures a package for $50.
- The package arrives damaged.
- The insurer’s system flags the claim as “unclear”.
- The dispute is sent to Justly.
- The user submits photos and delivery timestamps.
- Jurors evaluate whether the damage matches transit issues.
- The ruling:
- approves full payout,
- approves partial payout,
- or rejects the claim with justification.
Example: parametric weather insurance
- A farmer has micro-insurance for rainfall.
- Sensors report borderline data.
- The claim is disputed due to conflicting sources.
- evidence from multiple oracles,
- local context evaluation,
- human interpretation where automation fails.
- blind oracle dependence,
- rigid yes/no logic.
Why this matters for insurers and protocols
For insurers- Lower operational costs.
- Reduced fraud without blanket rejections.
- Higher user trust and retention.
- A real chance to contest unfair outcomes.
- Transparent decisions.
- Faster resolutions.
- Removes reliance on admin intervention.
- Enforces rulings trustlessly.
- Keeps systems decentralized under stress.
Micro-claims need proportional justice
Big insurance can afford:- lawyers,
- adjusters,
- long processes.
- low-cost justice for low-value claims,
- without sacrificing fairness or decentralization.
The takeaway
Micro-insurance fails when disputes are ignored.It scales when disputes are cheap, fair, and enforceable. Justly makes micro-claims:
- economically viable,
- socially fair,
- technically enforceable.
Micro-claims are typically resolved using Tier 1, enabling fast and cost-effective evaluations that would be impractical in traditional insurance systems. See Dispute tiers.