The Power of Data-Driven Asset Management I Accenture

1 The Power of Data-Driven Asset Management Propelled by the Power of data to accelerate transformation with AI, analytics and cloud THE STAKES. Yet, if you asked Asset managers if their firm is truly data- driven if they can turn their data into an Asset to achieve a competitive edge only a few would say yes. In fact, according ARE HIGH. to Accenture research, 66 percent of Asset managers say that data Management at their company needs to be completely IN GETTING. Where are firms struggling regarding data? DATA RIGHT. In our work with Asset Management clients, we see some or all of the following: Data fragmentation and disparate versions of the truth.

2 Many Asset Management firms need a data reinvention developing the ability to analyze vast amounts of data, sometimes in real time, to fuel growth Proliferation of data sources and product innovation and deliver world-class customer service. The stakes are high in getting data right. Rising costs of data Management Lack of an enterprise data strategy THE Power OF Data-Driven Asset Management 2. Transforming data into a Build a strong data foundation differentiated Asset for the long term requires a focus Create an effective data Management program, which includes data governance, data quality on three interrelated and master data Management ; technology platforms and data architectures; and data actions across business, supply chain Management .

3 Technology and people: Harness advanced technologies Use artificial intelligence (AI), machine learning and analytics to glean critical insights from data. Create a Data-Driven culture Manage the people and cultural dimensions of advanced data Management . THE Power OF Data-Driven Asset Management 3. Building a strong data foundation A strong data Management program is key to transforming data into an Asset and successfully delivering on a firm's goals and complex projects. Whether Asset managers are transitioning 01 Data governance their entire operating model for investment accounting or keeping pace 02 Master data Management with changes in the industry, they may find themselves struggling to deliver 03 Data quality and veracity projects on time with the expected business value because they lack a comprehensive data Management 04 Technology platforms program.

4 A firm's data foundation is critical to facilitating data- 05 Data architecture powered business use cases and realizing tangible business value. Data supply chain 06. Management THE Power OF Data-Driven Asset Management 5. 01 Data governance Asset managers often struggle to take Data governance requires coordination across organization, a firmwide view of data, so their data process and technology: Management approach supports only specific, non-integrated requirements. ORGANIZATION: end-to-end data lifecycle from initial That approach creates a siloed It starts at the C-level, but structurally it data capture to the delivery of understanding of data which then is important to create a data council a analytical views where data has been causes a fracturing of the data formal governing body maintaining a normalized to support an enterprise structure and differing points of view cross-domain perspective that guides view of the Asset .

5 On reporting requirements across the firm's data strategy. Particular roles functional domains. are also important, including data TECHNOLOGY: stewards and business data owners Technologies and platforms enable the An effective data governance program who shepherd high-quality data assets governance process. Metadata establishes trusted, certified data for and promote data literacy throughout Management and data cataloging business users. It creates standards for the firm. detect and isolate redundant data and business data transparency, data identify data flow breakage and data protection and audit integrity.

6 Asset PROCESS: loss. Enterprise data governance managers realize the importance of Data governance policies and platforms provide capabilities including good governance: more than half (55 procedures help establish a policy Management tools, data percent) of the Asset managers that Management framework, but the glossaries, data lineage capabilities and Accenture surveyed recently said they process delivers the goods. Process is dashboards/reporting which provide have a data Management initiative organized into operating models which vertical and horizontal views of data. underway that aims to enhance support business and data governance and data transformation.

7 For example, operating models which support the complete, THE Power OF Data-Driven Asset Management 6. One global Asset manager wanted to organize for growth by enhancing BUSINESS CASE its reporting capabilities. Effective data governance was emphasized to ensure that data being reported was accurate and did not introduce A DATA reputational risks or the chance of incurring regulatory fines. GOVERNANCE Working with Accenture , the It achieved a reduction of AUTOMATION. company established an operational costs and risks by enterprise-wide data governance establishing common artifacts that SOLUTION and data quality capability using an automated solution.

8 The firm were shared across the organization. By automating key improved business decision- manual data integrations, the Asset making because it now had high- manager was able to enhance quality data and standard efficiency and decrease risk. taxonomies. The company achieved a reduction of operational costs and risks by establishing common artifacts that were shared across the organization. THE Power OF Data-Driven Asset Management 7. 02 Master data Management Master data Management (MDM) is a Transforming data into an Asset should centralized and controlled data be focused on having authoritative aggregation capability that incorporates sources for key data domains in Asset 83%.

9 End-user requirements and performs Management , namely: account/product, validations to verify that the data is security, price and index/benchmark. trustworthy and fit for purpose. Security reference data or security master defines the investments Accenture cross-industry research themselves and facilitates the found that 83 percent of companies Accenture cross-industry communication of discrete assets don't have enterprise-wide, multi- internally as well as with the market and research found that 83. domain MDM, while half of respondents third parties. percent of companies don't don't regularly reassess and update their have enterprise-wide, multi- data governance process Leading practices suggest that Asset managers should ingest any shared data domain MDM, while half of For the Asset Management industry, centrally for all data consumers and respondents don't regularly having an MDM strategy and the ability organize it by domain to create a final reassess and update their to change master data centrally can and complete master record.

10 This allows allow firms to adapt with minimal impact for multiple efficiencies in data data governance process during project implementations. acquisition, validation and enrichment. Ultimately, all sources are normalized and consolidated into a single, standard model that meets all data consumers'. requirements. THE Power OF Data-Driven Asset Management 8. 03 Data quality and veracity +80%. The ability to measure the quality of Data quality is intertwined with data data across the enterprise can be a governance. The data governance challenge for Asset managers. Across program supports the enterprise in industries, data scientists spend over making a firmwide commitment to set 80 percent of their time preparing and up and maintain a data quality scrubbing data to make it fit for use for framework.