In this webinar, Michael Cummins, CFA takes a look at the impact on global hedge funds, from established shops to emerging start-ups and discusses why a solid data foundation can prepare for both regulatory and investor due diligence demands.
LUSID: Technology for Operations Teams
LUSID, the API-first, SaaS native investment data management system, gives you the tools, documentation, ecosystem, and reference implementations to integrate, extend, and create bespoke solutions around a consolidated source of your investment data.
Why use LUSID?
Open architecture enables easy integration with existing platforms via open APIs
Extend functionality with a marketplace of integrated solution and data providers
Easily extend or calculate properties on any object including transactions, investments, prices, etc.
Script bespoke portfolio simulations, analytics and valuation models
Zero capital outlays, no hardware or upfront build costs
Easily process, understand and control growing volumes of complex data
Create granular entitlements to control and permission data
Securely share data between clients, service suppliers and internal departments
Leverage an open ecosystem of developers, documentation, and code examples
How can I use LUSID
LUSID provides a comprehensive set of SDKs and example implementations to extend functionality beyond that of a standard portfolio management, investment risk, or enterprise data management system.
Easily load investment data from other systems
Reduce IT complexity and system maintenance. Consolidate investment data into one system
Get a consolidated view of your data
Perform n-way reconciliation, and on-the-fly position derivation on an event-driven, immutable data store that can reproduce any historical valuation and compare it to third party data
Strategy and idea backtesting
Improve your machine learning back testing strategies with a consolidated investment data set
Recreate any valuation or prior state of your records
Access all market and positional data along two-time dimensions, business validity (e.g. price date), and system validity (when data entered the system)
Eliminate separate Dev and UAT environments
Use our proprietary scopes and entitlements to mirror data from production and modify it within the same instance without impacting production
Collaborate with like-minded engineers
Work with our growing community of developers on GitHub with open source implementations in Jupyter notebooks to solve the most complex data challenges
Invested in security
FINBOURNE implements financial industry best practice built on top of AWS world class physical security.
Our Sandbox and QA environments all benefit from the same enterprise level security.
Start transforming how you manage investment data today.
Check out our APIs:API docs
Visit our knowledge base where you can find links to the swagger documentation for LUSID's sub-applicationsRead more
Events and insights
28 April 2022
A Tech Revolution: How Machines are Reshaping Hedge Fund Investment
11 May 2022
AFM and industry conclude high-level technical principles for a corporate bond consolidated tape
FINBOURNE Technology are pleased to have contributed to The Dutch Authority for the Financial Markets (Autoriteit Financiële Markten) technical principles, as part of our work in the AFM Innovation hub. We look forward to collectively striving towards a corporate bond consolidated tape in the EU.
AFME/ Finbourne study demonstrates need for longer deferrals for large and illiquid trades and shows transparency could be significantly improved for majority of smaller fixed income trades
3 May 2022 – The Association for Financial Markets in Europe (AFME) has today published a first of its kind study consolidating fixed income trading data from numerous sources for the period of March to December 2021. This shows that the majority of fixed income trades could be made transparent in near real-time, but also… Continue reading AFME/ Finbourne study demonstrates need for longer deferrals for large and illiquid trades and shows transparency could be significantly improved for majority of smaller fixed income trades