After the LA wildfires in early 2025, $4.3 billion in disaster relief funds was available. And people who’d lost their homes were still waiting.
The money existed. The systems to get it there didn’t.
That’s the core of a $5.5 trillion problem — and it’s where AI and fintech are starting to intersect in ways that could reshape how we respond to disasters.
The Distribution Problem
Disaster relief has always had two distinct phases: funding and distribution. The first phase — raising money, allocating budgets, appropriating federal and state funds — is well-established. It’s visible, political, and measurable.
The second phase — actually getting money to people — is where the system routinely breaks down.
Consider the numbers: 50 to 80 million Americans are unbanked or underbanked. When a disaster hits, these are often the most vulnerable populations — people who’ve lost everything and need cash immediately. But without a bank account, accessing relief funds means going through check cashers, prepaid card systems, or other intermediaries that charge 3% to 10% just to access your own money.
The people who most need help pay the most to receive it. That’s not a marginal issue. It’s a structural failure.
What Technology Has Made Possible
The technology to solve this problem largely exists. Real-time payment rails, digital wallets, biometric identity verification, and AI-powered fraud detection have all matured to the point where getting money to an unbanked individual in a disaster zone is technically feasible within hours of a crisis.
The barriers aren’t technical anymore. They’re about trust, communication, and coordination.
People affected by disasters don’t always trust new digital payment systems — especially when they’ve just experienced a traumatic loss and are being asked to onboard onto an unfamiliar platform. Government agencies often operate on legacy infrastructure that can’t connect to modern payment rails. And the coordination between federal agencies, state governments, financial institutions, and disaster relief organizations is frequently fragmented.
Where AI Enters the Picture
AI can address several of the coordination and communication failures that stall relief distribution.
Eligibility and verification is one of the most time-consuming bottlenecks. AI can cross-reference data sources — disaster declarations, property records, identity verification systems — to confirm eligibility in hours instead of weeks.
Fraud detection in disaster relief has historically been reactive. AI can shift that to real-time pattern detection, flagging anomalous claims while keeping legitimate ones moving.
Communication and outreach is where AI agent platforms come in. Getting information to affected populations — in multiple languages, through multiple channels, in plain language — is a real-time coordination problem that AI handles well.
Critically, AI can help with the integration layer between systems that don’t naturally talk to each other: federal disaster databases, state payment systems, community organizations, and financial institutions.
The Unbanked Equation
Organizations working on disaster aid payment infrastructure are already proving that the systems can reach people without traditional banking relationships. Their deployments in the US and Europe represent a proof point: it’s technically possible. The challenge is scaling them, connecting them to the agencies that hold the funds, and building the trust that drives adoption under crisis conditions.
A Solvable Problem That Hasn’t Been Solved
The $5.5 trillion figure represents the aggregate scale of relief funds globally that flow too slowly, reach too few people, and carry too high a transaction cost for the populations that need them most.
The technology is ready. The business case for better infrastructure is clear. What’s missing is the will to prioritize the last-mile distribution problem with the same energy we bring to the funding side.
AI can’t replace the human coordination, political will, and institutional trust that disaster relief requires. But it can remove the friction from the processes that keep money stuck in systems instead of reaching people who need it.
That’s not a moonshot. It’s just the work.
