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Cutter AdvantEdge
Issue 91, April 2013
Clients are increasing their demands on investment management firms. Clients want clearer reports, delivered faster. They want the investment manager's Web site to be easier to navigate, and access more highly sophisticated data, such as performance attribution and risk data. They want more value-added engagement, and better inquiry management from their client service representatives. To meet these demands, investment managers must ask themselves whether their client data is limiting the service they can provide.
Immaturity of Client Data
Investment managers have built data structures and established data teams to assure the consistency, accuracy, and timeliness of data. They typically invest significant time, money, and energy into data, primarily to provide the front and middle office with security data for trading and accounting purposes. But they generally devote less attention to data for sales, marketing, and client management purposes. Getting client data right can improve client experiences, help create scalable, efficient business processes, and improve employee experiences servicing prospects and clients. In these ways, good client data can help firms retain and gain clients and employees.
Client Data Domains
Client data supports the entire client lifecycle, including the processes to acquire, bring on-board, and service clients. For simplicity, we have divided client data into three domains: Client/Account data, Product data, and Operational data.
Client/Account Data
Client/account data encompasses information specific to the client and their accounts. This data is created when a client/account is brought on board. It changes when a client/account changes, and it is archived when a client terminates. The task of maintaining data is typically owned by groups with the best awareness of client/account structure changes, such as Relationship Management, Client Service, or Client Reporting groups.
Investment managers sometimes think of a Customer Relationship Management (CRM) system as the primary repository of Client/account data. But many firms have separate CRM systems with different data models for different Sales teams, different locations, or different business functions. This situation can make it difficult to have a holistic view of clients across the entire firm. A centralized source, known as a Client/Account Master, can help aggregrate data across multiple CRM systems.
Client/account data is often used in systems beyond the CRM, such as accounting systems, to create a new account. Without automation between the CRM system and these other systems, data must be manually entered and maintained in each system. Setup of these systems often occurs at different times, which can lead to data discrepancies and confusion about what data is accurate.
As firms are automating client reporting and communication, they also need to track several factors: how they engage clients, clients’ reporting requirements, and clients’ communication delivery preferences. Data elements for these tasks can exist in client contracts and can be stored in the CRM or in a client reporting tool. To accurately gauge the service level provided to a client, a common, central place to view the service level is needed.
Client/Account Data Examples
- Client Hierarchy (Parent, Legal Entity, Accounts)
- Account Reference Data
- Contacts Information
- Client Interaction Notes
- Client Reporting Requirements
- Communication Preferences
Product Data
Product data includes all information about the investment products offered by a firm, such as specific investment strategies offered as SMAs, collective funds, and 1940 Act Funds. Product data is used by prospects, clients, auditors, consultants, and others to understand what they have purchased or are considering purchasing. Product data is generally static, but it does change when products change. Automation of communication processes for clients and prospects can be limited when product data is inaccurate, incomplete, or unavailable, which is more likely at firms with no centralized source for storing product information, known as a Product Master.
Product data is used in a variety of communications such as marketing materials, Web sites, pitch books, and presentations. Different teams generate different materials that are reviewed on different timelines by different groups, such as Risk, Compliance, Product Management, and Product Development. Without a Product Master source, data discrepancies can lead to increased client inquiries and ultimately, to decreased trust.
Product Data Examples
- Investment Strategy Name
- Investment Guidelines
- Investment Philosophy & Process
- Standard Fee Schedule
- AUM & Breakdown
- GIPS Composite Data
- Investment Professional Data
- Footnotes & Legal Disclaimers
Operational Data
Operational data is used to describe an account or investment strategy, typically at a specific point in time or as a historical time series view, such as a holdings breakdown. While the data is usually shown at an account level, it may also be shown relative to a benchmark. Aggregating operational data can be a challenge, as many systems are sources of data, including systems for accounting, investment books of record (IBOR), performance measurement, performance attribution, and risk. Some firms use data warehouses to help with data aggregation.
While data accuracy and timeliness are important for all three data domains, it is most critical for operational data. Some data used for front office purposes or produced by the middle office may already be reviewed by a data team or by the team responsible for its generation. While this data may be appropriate for their own purposes, it may not be appropriate for all client-facing uses. Data accuracy and consistency issues tend to increase client inquiries, requests for custom reports, and demands for more face time.
Operational Data Examples
- Market Value
- Security Reference Data
- Pricing Data
- Holdings & Holdings Breakdown
- Transactions
- Performance (Returns)
- Characteristics & Risk
- Contribution/Attribution
Client Data Management - How to Get Started
Define Goals
Before you get started on a client data management project, think strategically about data for client facing purposes. What are you trying to accomplish? Are you trying to improve the overall client experience or improve the efficiency of data for client reporting only? Answers to these types of questions will help determine the likely scale of the project.
Complete a Current State Assessment
Once you establish your goals, it's a good idea to perform a current state assessment of your client data. In your assessment, find out what data is needed, where it is sourced from, who is responsible for data quality, and what data quality issues exist today. At a minimum, the assessment should create an inventory of the data elements and a list of data issues gathered from interviews with representative data users. Consultants can be valuable here because they can perform a detailed assessment quickly, they know what others firms are doing, and they can serve as an impartial party where there are differences of opinion within a firm.
Implement a Client Data Dictionary
These days, firms need to trace the lineage of key pieces of data, for clients as well as regulators. They want to know where data came from, how it was derived, whether it was changed along the way, and if so, who changed it. A client data dictionary can help track data lineage, and the initial list of data elements often becomes the first version of the dictionary. As new data elements are needed or source systems change, it is imperative to track the changes and keep the information up-to-date.
Establish Client Data Governance
Define the key client data governance roles such as owners, stewards, creators, and consumers. Responsibilities for each role must be clearly defined and understood, especially since some people perform more than one of these roles for different aspects of their job. And the roles and responsibilities may vary by the data domain.
Once early improvements and improved confidence begin to emerge for your client data, expect new business demands to arise. A client data governance committee can help prioritize tactical efforts, such as holding owners responsible for accuracy, adding data for new client lifecycle processes, and adding, modifying, or deleting data elements or sources. As your program matures, major changes to client data may be requested. A client data governance committee can also be responsible for reviewing the request, understanding the business value it creates, and assigning it a priority.
Conclusion
Client data management efforts can help investment managers meet increasing demands from clients and regulators. By managing client data through the client lifecycle, investment managers can enhance their client experience; create scalable, efficient business processes; and improve the employee experience in servicing prospects and clients. In times of limited differentiation, client data management can help you achieve competitive advantage.
Cindy Shields, CFA heads the Client Facing Consulting Practice for Cutter Associates. Her areas of responsibility include all aspects in the client lifecycle. She has helped firms with client strategies, client reporting, new client/account on- boarding, and client data management efforts. She has more than 24 years of consulting and industry experience with investment managers.