# Fasanara Capital > To be the institutional benchmark for fintech lending and digital investing Fasanara Capital is an alternative asset manager offering institutional investors fintech lending and digital asset investment strategies. Fasanara Capital is a London-based alternative asset manager focused on fintech lending and digital asset investing for institutional clients. It offers strategies spanning trade receivables, consumer loans, real estate credit, market-neutral crypto trading, and bespoke multi-asset portfolios. The firm operates a proprietary credit platform integrating a global network of fintech loan originators with machine learning analytics. - Type: Investor - Sector: Finance - Status: Active - Founded: 2011-01-01 - Profile: https://thegrid.id/profiles/fasanara_capital ## Products - [Fasanara Fintech Lending](https://thegrid.id/profiles/fasanara_capital): Fasanara Fintech Lending is an alternative credit fund providing institutional access to fintech lending strategies. Capital is deployed through fintech loan originators across trade receivables, consumer digital lending, real estate-backed credit, sports receivables, and a multi-strategy credit allocation known as FTAC. Credit assessment uses the proprietary Fasanara Credit Model (FCM), applying machine learning analytics, with individual loans assigned a Fasanara Debtor Rating (FDR). The fund targets short-duration, senior credit positions distributed across multiple geographies and originator networks. (Managed Fund, Live, Main Product) - [Fasanara Digital](https://thegrid.id/profiles/fasanara_capital): Fasanara Digital is a quantitative investment fund applying market-neutral trading strategies to digital assets. The fund targets returns derived from structural and instrument-specific inefficiencies in crypto markets through proprietary signal generation, execution tooling, and a multi-dimensional risk management framework. The fund also operates a Managed Account Platform (MAP), a multi-manager structure allocating capital across independent investment pods and providing institutional investors access to uncorrelated digital asset return streams. (Managed Fund, Live) - [Fasanara Open Quant](https://thegrid.id/profiles/fasanara_capital): Fasanara Open Quant is a multi-manager, multi-strategy quantitative hedge fund allocating institutional capital to systematic trading models across liquid markets. Strategies span Statistical Arbitrage, Relative Value, Option Structure, and Directional approaches, managed by both internal and independent external portfolio managers. A Flexible Asset Allocation framework ranks trading models by historical returns, volatility, and correlation to determine capital allocation within a single optimally leveraged portfolio. (Managed Fund, Live) - [Fasanara Ventures](https://thegrid.id/profiles/fasanara_capital): Fasanara Ventures is a venture capital fund investing in early-stage fintech platforms and marketplaces from Pre-Seed to Series A. The fund targets companies in consumer lending, SME lending, mobility, and Web 3.0 sectors including DeFi and blockchain. An incubation and acceleration program is offered alongside capital, through which portfolio companies may integrate into Fasanara's technology platform and originator network. (Venture Fund, Live) ## Links - [Main](https://www.fasanara.com) - [Blog](https://www.fasanara.com/insights/blog) - [Privacy policy](https://www.fasanara.com/legal) - [Twitter / X](https://x.com/FasanaraCapital) - [LinkedIn](https://linkedin.com/company/fasanara) - [YouTube](https://youtube.com/@FasanaraCapital) ## Legal This data is provided under two licensing models. Model 1 - open data. The open data core is licensed under the Open Database License (ODbL) — a copyleft/share-alike license allowing free use, modification, and sharing for any purpose. Attribution is required: include "Powered by The Grid" linking to https://thegrid.id wherever the data is used. Derivative databases must be shared under ODbL terms. Trademarks, logos, and brand names (marked "Special TPIP") are not covered by the ODbL. For ML/AI use: training datasets that substantially extract ODbL data are Derivative Databases and must be shared under ODbL if publicly used; models must be attributed in documentation. 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