The list of challenges facing investment managers has grown.
A period of rapid change, coupled with the recent run of price volatility, hasn’t helped the list of challenges facing the investment management industry. That volatility has contributed additional regulatory augmentation, fee pressures, margin compression, and changing investor preferences and customer expectations. As a result, we thought it would be helpful to our prospects and clients to bring them all together for analysis and recommendations.
Here are 10 challenges facing the investment management industry that we regularly hear about from firms around the globe:
Operational Risk Management
Operational inefficiencies and the potential for manual errors increase with growth in assets under management (AUM), the client base, the variety of funds or the number of external fund managers. Many operational risks relate to manual processes:
- Launching new products and setting up new funds
- Maintaining complex policy trees, fund structures or taxonomies and allocations at various levels
- Monitoring allocations based on investment mandates and exposures
- Maintaining multiple fund hierarchies for numerous reporting scenarios
- Setting up exotic asset classes such as alternatives, private markets, infrastructure and complex derivatives
- Assembling, validating and cleansing accounting and investment data to support daily operations
Quality Data for Better Investment Decisions
- Dealing with the specifics of investing in private markets assets such as infrastructure or private equity
- Ensuring not only an accurate ABOR/accounting/custodian view, but also a detailed IBOR/investment/external manager’s view/latest adjusted view
- Easy access to different PBOR views to assess portfolio performance
- Providing a whole portfolio view for the investment team, sliced by sector, region, external fund manager, strategy, currency, market and time horizon to assess risk
- Peripheral front office and related critical data need to be mastered inhouse to internalise fund management as only appropriate data drives appropriate decisions
Whatever the operating model adopted by a firm, it is crucial to integrate and solve for the data flows from disparate feeder systems in FO/MO/BO areas, such as custody, performance & attribution, risk, OMS, exchange systems:
- Integrating systems and establishing a single source of truth for investment operations and investment management teams
- Establishing a hub for reporting, particularly in firms with any element of outsourced FO/MO/BO. A system that records flows between these systems and serves as a single source of truth.
- Creating a framework for sourcing, enriching, mastering, validating and reporting data in-house
Reporting driven by regulatory augmentation
Regulations are pushing reporting to new levels of consistency, completeness and accuracy:
- Compiling report data from multiple sources to comply with regulatory reporting within the stipulated timelines, such as for N-port in America, or the APRA (Australia) requirements to explain data.
- Look-through reports needed to assess overall exposure to a specific security directly or indirectly by owning other funds
- Drill-through reports to help with a detailed view of specific fund, benchmark, trust or private equity
- Creating a whole assets under management view across managers, asset classes, regions, portfolios, particularly for firms who have outsourced fund management to multiple external managers, challenge is to, etc.
Data Quality at Granular Levels for Accurate Aggregation
Data aggregation functions are needed at various levels of policy trees to assess firmwide risk and facilitate better investment decisions, and as part of the data quality framework to ensure effective custodial oversight.
- Managing data from multiple custodians to cater for public and private market needs. Firms often maintain a shadow accounting system to ensure checks and balances are in place. Reconciling exposures, fees, etc. becomes an essential part of operations. There is then a need to roll up and down exposures, fees across fund hierarchies to check and validate custodial function/calculation
- Linear and non-linear aggregations that can adjust for derivatives or long-short portfolios
System scale and performance:
- Accommodating growth and change in the business and its operating model
- Enabling automation and digitization
- Incorporating artificial intelligence and machine learning
- Improving analytics capabilities
Living with Spreadsheets
Many investment firms still primarily rely on spreadsheets. Those that do find themselves contending with:
- Addressing controls
- Avoiding and identifying human errors
- Incorporating data from spreadsheets in straight through processes (STP)
Data Governance Framework
Irrespective of a firm’s goal, growth phase and operating model, governance is required to ensure consistent, accurate and timely data for business decisions
- Establishing and maintaining rules, standards and controls, so that data is understood and used consistently across the firm
- Supporting the governance framework in daily operations, through appropriate data sourcing, mastering, validation, scrubbing and reporting
An Operating Model for Generating Alpha
As markets evolve, firms face challenges of generating alpha and adjusting their operations as needed:
- Becoming flexible at introducing new/alternative investment classes
- Identifying core and non-core activities to help shape an optimal target operating model
- Selecting managed or outsourced services, freeing up resources for strategic alpha generating activities.
Changing Investor Preference and evolving customer experiences
A quicker go-to-market has become an important aspect for survival in the era of changing investor preferences and evolving customer experiences.
- Launching new products fast, especially involving private market assets, with the complexities of set up, valuations and reporting
- Delivering a better user experience for customers in the form of services offered post sales, including fact sheet reports
All of these challenges have data as a common element.
Data management capabilities that contribute to solving for these challenges facing the investment management industry go a long way to supporting ongoing improvements in driving profitable business.