Failure Analysis
Cushion died from a lethal combination of structural dependency risk and adverse market evolution that made their business model obsolete. The immediate cause was...
Cushion \USA
Cushion was a fintech startup that aimed to help Americans manage and reduce their bank overdraft fees through automated monitoring, negotiation, and fee recovery. Founded in 2017, the company positioned itself as a consumer advocate in the fight against predatory banking practices, promising to save users hundreds of dollars annually by tracking their accounts, identifying unfair fees, and automatically requesting refunds from banks. The timing seemed perfect: overdraft fees were generating $15+ billion annually for U.S. banks, affecting primarily low-income consumers who could least afford them. Cushion's value proposition was clear—turn your phone into a personal banking advocate that fights fees 24/7. The product connected to users' bank accounts via Plaid, monitored transactions in real-time, identified overdraft and other junk fees, then used templated communications to request refunds on behalf of users. They monetized through a subscription model ($36-48/year) or success-based fees (25-40% of recovered amounts). The 'why now' was compelling: API banking infrastructure (Plaid, Finicity) had matured, consumer awareness of predatory fees was rising, and mobile-first financial services were exploding. However, Cushion faced a fundamental problem: they were building a business model dependent on the continued existence of a fee structure that banks were already being pressured to eliminate, while simultaneously antagonizing those same banks whose cooperation they needed for account access.
Discover the reason behind the shutdown and the market before & today
Market Analysis
The overdraft fee market has undergone radical transformation since Cushion's 2017 founding, with the changes accelerating dramatically in 2022-2025. What was once a $15...
Startup Learnings
Never build a business that depends on the cooperation of entities whose revenue you're trying to eliminate. Cushion needed banks to maintain API access...
Market Potential
The total addressable market has actually contracted significantly since Cushion's founding. In 2017, U.S. banks collected approximately $15 billion in overdraft fees annually, with...
Difficulty
The core technical infrastructure is significantly easier to build today than in 2017. Plaid and similar services have matured dramatically, offering more reliable connections...
Scalability
Cushion's scalability was fundamentally constrained by several factors. First, the unit economics were problematic: customer acquisition costs in fintech are high ($50-150 per user),...
Rebuild & monetization strategy: Resurrect the company
Execution Plan
Phase 2
Step 2 - AI Financial Coach (Validation): Add GPT-4 integration that analyzes spending patterns and provides personalized recommendations in natural language. 'You spend $340/month on food delivery—switching to grocery delivery could save $150/month. Want help setting this up?' Implement 3 automated actions: move money between accounts, pause subscriptions via Truebill API, recommend better bank accounts. Add premium tier at $4.99/month for unlimited AI coaching and advanced forecasting. Target: 10,000 users, 8% conversion to premium. Validate willingness to pay and that AI recommendations drive behavior change (track action completion rates).
Phase 3
Step 3 - B2B White Label Platform (Growth): Pivot primary monetization to B2B. Package the financial health engine as white-label software for credit unions and regional banks who want to reduce member overdrafts and improve retention. Pricing: $2-5 per active user per month, minimum $10K annual contract. Build admin dashboard for bank partners to customize branding, set intervention thresholds, and track member outcomes. Target: 5 credit union pilots in 90 days (credit unions are desperate for fintech tools and easier to sell than big banks). Consumer app becomes free, funded by B2B revenue. This solves the adversarial relationship problem—you're now helping banks reduce costs and improve member satisfaction.
Phase 4
Step 4 - Financial Health Platform with Embedded Products (Moat): Expand beyond overdraft prevention into full financial health: credit building (report rent/utility payments to bureaus via Boom or Esusu integration), bill negotiation (partner with Rocket Money API), income smoothing (integrate with Earnin or Dave for early wage access), and personalized banking product recommendations (earn affiliate revenue from Chime, SoFi, etc.). Build network effects through anonymized benchmarking: 'You spend 40% more on transportation than similar households in your area.' The moat is the combination of proprietary cash flow prediction models trained on millions of transactions, deep integrations with bank partners who white-label the product, and the AI coaching layer that improves with usage. Revenue model: $3-8 per user per month from bank partners, 20-40% affiliate revenue on product switches, $9.99/month premium tier for consumers who want advanced features. At scale, this is a $100M+ ARR business serving 10M+ users through 500+ bank partnerships.
Monetization Strategy
Lighthouse uses a multi-sided monetization model that aligns incentives across all stakeholders. Primary revenue (60-70%) comes from B2B SaaS contracts with credit unions, regional banks, and neobanks who white-label the financial health platform for their members. Pricing is $2-5 per active user per month with $10K minimum annual contracts, targeting 500+ financial institutions at scale. This model works because Lighthouse reduces overdraft losses (banks save $50-200 per prevented overdraft), improves member retention (financial health tools increase stickiness), and provides competitive differentiation (smaller banks can offer neobank-quality experiences). Secondary revenue (20-30%) comes from affiliate partnerships and revenue sharing when users switch to better financial products. When Lighthouse recommends a user move from a high-fee bank to Chime or SoFi, the platform earns $50-150 per successful switch. Credit card and loan recommendations generate $100-500 per approval. This is performance-based and aligns with user outcomes—Lighthouse only earns when users genuinely improve their financial situation. Tertiary revenue (10-20%) comes from a premium consumer subscription at $9.99/month that offers advanced features: unlimited AI coaching sessions, detailed spending analytics, automatic bill negotiation, and credit score monitoring. This tier targets the 5-10% of users who want maximum control and insights. The model is defensible because the B2B contracts create recurring revenue and high switching costs (banks integrate Lighthouse into their core member experience), while the consumer side remains free for most users, funded by B2B and affiliate revenue. Unit economics at scale: $4 average revenue per user per month, $2 CAC (B2B sales amortized across users), $0.50 monthly infrastructure cost per user, resulting in 87% gross margins and 24-month payback period. This is dramatically better than Cushion's model because revenue is recurring, grows with user engagement, and aligns with rather than opposes the interests of financial institutions.
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