Fintech-focused asset manager spanning lending, digital assets and quant
Fasanara Capital is a London asset manager running fintech asset-based lending, digital asset and multi-manager quant strategies. Its stack pairs Python, Pandas and NumPy with on-chain tooling (Ethereum, Solana, Arbitrum, Uniswap, Aave, ethers.js), revealing in-house DeFi execution capability. Engineering-led hiring, now accelerating, targets an open quant platform and position ledger integration, alongside a new Commercial Lead to build distribution.
Notable leadership hires: Commercial Lead
Fasanara Capital, founded in 2011 and headquartered in London, is a privately held investment manager with 51–200 employees. It invests in fintech-originated asset-based lending through alternative credit funds, and runs a digital asset arm and a quantitative multi-manager platform that allocates to independent emerging managers. It serves institutional investors such as pension funds and insurers in Europe and North America. A proprietary technology platform connects it to fintech lenders across many countries, and it also backs early-stage fintech companies through venture vehicles.
Fasanara uses Python, Pandas, NumPy, Java, Kotlin, C++, Go, Rust, TypeScript and React, with MySQL, GitLab, Docker, Kubernetes and AWS, plus blockchain tools like Ethereum, Solana, Polygon and ethers.js.
Current projects include an open quant technology platform, position ledger integration, portfolio aggregation, risk analytics across asset-based finance strategies, and building a distribution engine and sales process.
Yes. Hiring is accelerating and engineering is the largest focus, alongside data, risk, finance, operations and sales roles, all based in the United Kingdom, including a Commercial Lead position.
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Fasanara Capital's technology stack, projects, and hiring signals are inferred from public hiring and company data — career pages, public listings, and company web presence — then clustered and de-duplicated. Figures are estimates that refresh over time. Read our full methodology →
This is not an official vendor or customer list. It is a technology-adoption signal inferred from public data, intended for B2B research.