Why Managers Should Demand Consolidated Positions Data
Consolidating positions data is a particular challenge to all Investment Managers. A common perception is that positions are reflected in the back office record keeping system that promotes a start of business feed to support the daily activity in the front office.
A dry subject to some, but there are many disparate customers of positions data that make this a key building block of an Investment Manager’s operation.
The need to transition to electronic trading and the drive for STP has seen many Asset Management companies implement integrated Order Management and Trading systems. These systems often support a variety of front office functions within an organisation: decision support, order management, compliance and the trading interface. To function efficiently OMS applications require accurate and timely position data at the security level.
With the acceptance in recent years that prevention is better than cure, there has been a much greater emphasis on pre-trade compliance. Despite this, most firms still engage in levels of post-trade compliance for certain types of limit checking. Many firms are using a comprehensive OMS system such as Charles River or Latent Zero that incorporate compliance functionality. These OMS systems are often implemented for a single asset class (e.g. FI only) or for one or two of their offices (e.g. used in London but not in Asia). These OMS systems can only evaluate accounts/positions that reside in the system therefore organisations typically use the OMS for specific compliance checks and then consolidate all holdings into a single repository to analyse concentrations across all holdings.
Reporting the total market value of investments managed has proved to be a difficult task for a number of organisations. The creation of a consolidated view of positions, avoiding any double counting typically thrown up by pooled investments is regarded as a necessary first step that supports the calculation of AUM (Assets Under Management) which is essentially a reporting function. AUM reporting has received widespread attention in recent years partially due to the creation of ethical standards to which asset management companies should comply. Due to the practice employed by some asset managers to charge management fees based on a percentage of AUM, it is understandable that this reporting requires both accuracy and transparency.
Performance Measurement requires the sourcing of appropriate position data and is a common challenge. If performance data is used by other functions with an asset manager it is important that a common source of position data is used. An example is client reporting (i.e. the performance figures must be calculated on the same position values that will show on the client report).
Risk Management is closely aligned to performance. In some Asset Managers they are handled by the same group while other organisations have performance and risk as separate groups. Calculation of risk characteristics is now a common process within Asset management companies (e.g. Value At Risk). For this there may also be a requirement to source and store data explaining the historic relationship between stocks, sectors, industries and asset classes (i.e. covariance data).
Cash Management throws up two main drivers for consolidated positions data. The first, cash inflows and outflows need to be passed to the front office to ensure the required investment/disinvestments occurs in a timely fashion. This process supports management of subscriptions and redemptions of unitised funds, dividend and coupon income and any transitioning to/from the manager of client moneys. This can be a complex process with information potentially coming from different sources (e.g. outsourced back office, Internal Transitions Team, Fund Administrator) and at different times of the day.
The second area is the management of discrete cash funds which will typically seek to outperform a given index (e.g. Stg 3-month Libor). These funds will typically invest in cash or near cash instruments (CD’s, CP) with a tenor of up to 1 year. They may well look to arbitrage between cash and derivatives markets in order to boost returns (e.g. FRA/futures arbitrage).
Baskets of assets are committed as collateral to back derivative positions. These maybe individual securities or cash balances or groups of assets. These positions need to be maintained individually, but also as consolidated positions where a basket of assets is used as collateral. This information is used in the front office and is typically fed into back office systems and relevant third parties. One aspect of collateral management is to ensure that held/pledged collateral is (or is not) included in fund valuations and is marked as unavailable for trading dependent upon any rehypothercation agreements entered into. Consolidated reporting is also required to support operational tasks and reconciliation v counterparties.
The temporary exchange of securities against collateral is a widely used, low-risk yield enhancement strategy. The costs of operating a comprehensive lending program are driving some firms to consider the outsourcing of this service.
Initial and variation margins need to be maintained v clearing brokers for futures contracts. Again this is primarily a reconciliation function that drives the need for consolidated positions - Positions need to be aggregated to the level at which the reconciliation v the third party (or other internal system) holds positional data.
Fee Billing is an area that is particularly important where the Asset Manager has large volumes of discrete clients, either institutional or private client. The process of updating and managing client data (names, addresses, contact points) along with details of the billing calculations themselves (fee rates on unitised products held, fee scales dependent upon fund size - either AUM or number of holdings- and periodicity of billing) has come in for scrutiny in the last few years. Many large fund managers have implemented specialised billing systems to automate the process. It is not unheard during these implementations for fund managers to discover clients which had been under-billed or not billed at all. Having all this billing data within one system or easily extracted and combined with other data into a data hub can provide accurate and timely management information and can be used to model the impact of shifts in variables impacting cashflows (e.g. fee rates, market index levels).
Client reporting is seen by some Asset Managers as a significant differentiating factor to their competition. Asset Managers have various types of clients and often have different approaches to reporting to them. Highly graphically printed client reports are still the predominant model used within European Asset Management. The process of producing client reports tends to have many steps and review points (i.e. a series of processes linked into a workflow, culminating in a reporting pack being produced).
Collation of position data from around an Asset Management organisation is one of the first and fundamental steps in the whole process. Unlike many of the processes within Asset Management, Client Reporting is focused on a significant point in time rather than the latest set of information. The typical points in time are month, quarter and year end. Accurate and complete information is priority to Client reporting.
Asset Managers obtain the majority of their institutional, pension or insurance clients by responding to RFP’s. An RFP typically needs to include analysis of the Asset Managers existing funds. Although each RFP is unique, the majority of the information required is common across all of them. The challenge for asset managers is to be able to ‘slice and dice’ information in a variety of ways to suit the demands of the RFP. Without a consolidated view of all of the investment management companies assets this is at best ‘a challenge’ for those involved in this sales process. In some instances, where information is not available at a sufficiently granular level, questions cannot be answered accurately.
To provide meaningful responses to RFP’s 3 main data groups are required; Accounts and associated account structures, position values and performance returns at the security level and security attributes necessary to ‘slice and dice’ the information.
The depth and diversity of the customer base for positions data has to dictate that achieving accurate, consistent and accessible consolidated positions data must produce significant economies of scale for any asset manager, large or small.