Fundstream helps asset and wealth managers consolidate and manage data, generate reports and build analytical models.
Before data collection can begin, vendor agreements need to be signed, a secure channel put in place and a security audit passed. We assist you with all steps of this process by tapping into our large network of contacts at the different data providers.
Data arrives in different formats and at different frequencies, and file formats can change without warning, causing loads to fail. Our data management team monitors every pipeline and contacts vendors when a data pipeline breaks.
Portfolios and instruments need to be mapped to master data records to prevent duplication, and family structures with their main members need to be configured.
Each provider sends its own classifications and transaction types, which must be mapped to your house view. We use a combination of AI and machine learning, internal rules and manual editing to ensure all records have been classified correctly and are ready for reporting.
We can integrate with any currency cross rates API which load automatically every day, allowing cross-currency conversions across every platform and portfolio. Our system also stores a full table of ISO currency codes, names, and symbols, which can be used on reports and dashboards.
Loading data gets you halfway there; the other half is automated data checks that run daily to pick up variances. Our data engineering team configures the checks to your tolerances so inconsistencies are caught early. Our system has a low code fully configurable rule builder that integrates with the data pipelines.
Fund-of-funds and multi-manager products hide underlying holdings. The Fundstream data management platform supports look-throughs with no limit to the level of drill-down. This allows classifications to be brought up to the top level.
Fundstream follows a three-tier architecture with bronze, silver, and gold layers. The bronze layer represents the raw files, the silver layer is the data warehouse where data is loaded and then validated and managed. It then gets pushed to the gold layer, which is a data mart ready for reporting and analysis.
The Fundstream data operations team sets up automated alerts and monitors pipelines that load data into the data warehouse. If a load is missing or fails, we communicate with the data provider to get new files or investigate failures.
During data loading, we run multiple validation checks to make sure there are no gaps in the data and that totals add up to expected amounts with thresholds.
Once data has loaded, the data operations team springs into action and classifies data (such as asset classes), maps transaction types to the internal house view, and links master data to create the required structures.
The reporting team creates bespoke reports based on your custom requirements, meeting your brand guidelines. The reporting system takes care of distribution to multiple channels.
Once data has been managed and checked, we set up semantic models for Power BI that can run locally or in the cloud. Dashboards can be shared across the team or customized per user.
We can build advanced calculation models such as performance (time and value weighted), compliance, and Black-Scholes valuations.
Don't see your platform? Let us know — we add new integrations continuously.
Riscura required a trade planning and execution system. We met with their team and reverse-engineered their process into a cloud-hosted platform. We load transactions and valuations every day, which allows the team to create a trade plan. In the trade plan, the team can trade to different targets, such as strategic and tactical asset allocations with cash projections. They can also do forex trading to fund the instrument's forex trades. The system automatically sends trade instructions to the relevant broker using the required formats.
Fundhouse required a complete rebuild of their fund modelling system, which is at the core of their business. Our business analysts sat with them for several weeks to define the requirements and understand how we could optimize their process. The new fund modelling system allows them to manage several hundred models and handle changes based on strategy, manage allocation, and internal house views across all affected models as a bulk process. The team has saved at least 50% on their time over the old system.
Imagi were required to build a new system to calculate value assessment scorecards. The system is a requirement of the FCA and is known as assessment of value. We created a complex and configurable calculation system that generated over 10,000 calculations monthly to rank performance fees, service delivery, and an overall assessment.
Constellation Capital were performing complex Black-Scholes calculations for derivative valuations using Excel workbooks. The process did not scale and was prone to error. We created an automated system that loads up derivative data and then performs a daily Black-Scholes calculation to forward-project derivative valuations, which are then uploaded back into a market system.
PPS required a complete overhaul of their data warehouse to consolidate insurance and asset management data. We deployed our data management solution into the environment and set up over 300 data pipelines. PPS now have a unified view across their insurance policies, asset management, brokers, and clients. The data has revolutionized access for their fund research team and allowed automated fund fact sheet generation.
Riscura required a high-volume, low-cost data warehouse platform to replace their existing system. We recommended using Databricks as it offers high scale at a relatively low cost. We worked with their team to set up a data lake with 150 data pipelines from both market data and asset managers on a daily basis. They now have a data lake that can scale into the future and support AI and machine learning.
Ready to simplify your data operations? We'd love to hear from you.