Proximitty

Autonomous business loan servicing

Winter 2026ActiveFintechCredit and LendingFinOpsFintechSaaSB2BLendingSan Francisco, CA, USA

Company

Proximitty helps build autonomous business loan servicing teams for fintechs and banks. We build unified lending data layers and personalised risk scoring models to power AI agents that dynamically learn, adapt and increase collection rates for banks, credit unions and fintechs, while automating complex servicing workflows with no-code browser agents. In < 3 weeks, we're working with 5 large banks and fintechs that process over >$1B of delinquent loans.

Verdict

High Signal

Market Opportunity

Business loan servicing for banks, credit unions, and fintechs is a large B2B enterprise market — U.S. commercial loan servicing alone represents hundreds of billions in outstanding debt. Clear ICP (banks and fintechs with delinquent loan portfolios), clear ROI metric (collection rate improvement), and enterprise SaaS monetization path. Regulatory complexity in fintech creates a meaningful moat for incumbents who get in early.

High Signal

Founder Signal

Wye Yew Ho has directly relevant fintech experience: McKinsey credit risk consulting (2 yrs), then Taptap Send where he led growth from $50M to $200M ARR and rebuilt the fraud stack achieving 70%+ chargeback reduction. Zi Zhang has 4+ years at Bloomberg leading platform security infrastructure (325k+ terminals), plus built ACI.dev's unified MCP server that hit 4k GitHub stars and 6k users in one month. Strong complementary CEO/CTO pairing with real fintech and engineering depth.

Medium Signal

Competition

No competitor data was returned in research, but the space includes legacy loan management systems (FIS, Fiserv, nCino) and newer AI-native challengers in collections/servicing. The 'no-code browser agents + unified data layer' framing is somewhat differentiated from pure LMS vendors, but the AI agent wrapper risk is real — Salesforce, ServiceNow, and fintech-specific players could absorb this functionality. Proprietary risk scoring models and lending data layer are the key moat claims that need validation.

Medium Signal

Product

Website is 'Book a Demo' only with no live demo, pricing, or API docs visible. However, the description claims 5 large banks and fintechs processing >$1B of delinquent loans as customers within 3 weeks — if true, that's meaningful early traction. No named customer logos or revenue figures to independently verify.

OverallB Tier

Proximitty has a genuinely strong founding team — Wye Yew's direct fintech operating experience at Taptap Send scaling ARR 4x and Zi Zhang's Bloomberg infrastructure + viral MCP build are both credible signals. The early claim of 5 bank/fintech customers processing $1B+ in delinquent loans within 3 weeks is eye-catching but completely unverified — if real, this jumps to an A or S. The product is still largely invisible publicly, just a 'Book a Demo' landing page with no screenshots, pricing, or demos. The core risk is that this is an AI wrapper on loan servicing workflows in a market where legacy vendors (FIS, Fiserv) have deep integration and compliance advantages, and the differentiation ('unified data layer' + browser agents) may not be durable. Worth watching but needs the traction claim validated.

Active Founders

Wye Yew Ho

Founder

Co-founder & CEO @ Proximitty (YC W26). Previously, led FinCrime and Growth at Taptap Send ($75m -> $200m ARR) and started his career advising banks and fintechs on risk strategy at McKinsey. Highest ranked Malaysian in history in the Southeast Asian Maths Competition (SEAMC).

Zi Zhang

Founder

Co-founder & CTO @ Proximitty (W26). Previously, led security infrastructure at Bloomberg (securing 300k+ terminals) and Head of Engineering at ACI.dev (built world's first unified MCP with 4k GitHub stars in 1 month).

Proximitty

TierB Tier

BatchWinter 2026

Team Size2

StatusActive

LocationSan Francisco, CA, USA