Our IDM Solution

IDM (Investment Data Management) is a specialised branch of EDM (Enterprise Data Management), focussing specifically on data management within the investment industry.

The purpose of IDM is to provide the investment manager with a centralised set of tools to configure, execute and monitor the flow of data and associated processes. Once properly managed and integrated the investment data becomes the perfect platform for producing MIS and operational enquiry results, end-user dashboards, and template based reporting.

We allow our clients to focus on data usage and manipulation by providing them with a consolidated view of ALL required data and a powerful toolset to import and extract this data from and to systems. Once implemented, our product offering not only provides users with a powerful enquiry framework, but also allows companies to adopt a “plug and play” architecture in which best of breed systems can be implemented or substituted within weeks.

We have applied our IDM philosophy across the following types of companies within the investment industry:

• Asset managers
• Multi-managers
• Hedge fund managers
• Risk consultants

Asset Managers typically have a myriad of systems that contribute towards their data architecture e.g. client reporting, performance and attribution, front-office / portfolio modelling and trading.

The data links between these systems can become complex over time, often resulting in multiple dependencies between systems, and multiple yet inconsistent versions of data. Factor in the trend towards outsourcing the processes managed by these systems, and it becomes clear that having a central data store that resides between these systems can be highly beneficial.

Infovest’s IDM product offering allows asset managers to create a central data store for all shared data. This removes dependencies between systems, ensures that there is only 1 accepted version of each data element, and offers opportunities to perform true business intelligence.

Multi-managers are faced with the challenge of gathering positional, transactional and performance data from multiple sources, whilst simultaneously having to manage the complex relationships that give their investment products their hierarchy.

Without sophisticated tools to import, consolidate and version this data, processes such as client reporting, compliance, and risk monitoring become time consuming and susceptible to manual error.

Infovest’s IDM product offering allows multi-managers to perform these tasks, and our unique enquiry framework allows users to aggregate investment data at any level, and drill down into any data, from the client level right through the underlying stock level.

Managers of funds of hedge funds require detailed data relating to the funds in which they invest. This data typically has to be sourced from external fund managers, prime brokers, and/or fund administrators.

There is often a need to supplement this transactional and positional data with market or reference data e.g. to calculate exposures to index constituents.

Infovest’s IDM product offering allows hedge fund managers to consolidate this data and run rules to provide a layer of data consistency. It also gives them the tools to navigate through hierarchical data, looking through from a client level, fund of fund level, underlying fund level, right through to a stock level, even if that stock is held through a derivative or index.

Risk consultants rely on multiple external data sources to analyse data, generate reports and provide investment advice. Gathering, manipulating and consolidating this data manually can be time consuming and un-scalable. The task is made even more complex by the variety of formats in which data is received.

Infovest’s IDM product offering provides Risk Consultants with a robust and scalable set of tools to:

• Import data in virtually any format
• Verify and highlight data discrepancies
• Cater for precedence rules for multiple sources of the same information
• Version, consolidate and warehouse imported data
• Track data changes over time
• Create and maintain an instrument universe
• Set up “intelligent” extracts to other systems