Mindmeld 2019: Buy Side Reaches Turning Point
Mindmeld 2019: Leaders in the Buy-Side Join to Discuss the Industry’s Most Critical Trends
Mindmeld, Indus Valley Partners’ annual buy-side conference held on April 11th, joined together some of the most notable CFOs, CTOs, CROs and CIOs across the alternative and traditional asset management industry for an opportunity to learn and discuss crucial trends related to finance, operations, technology and compliance.
This year’s event began with a special keynote presentation from New York Times best-selling author, Neel Doshi, on the key aspects of an effective operating model that, when properly implemented, can help build a high performing company culture. Following Neel’s presentation, the day consisted of three panels moderated by Indus Valley Partners subject matter experts, training sessions for newly upgraded and existing IVP solutions, and a fireside chat focused on cloud migration moderated by CEO Gurvinder Singh.
Each panel joined buy-side leaders from various roles to discuss and debate several trends that the industry will be faced with in years to come. Key findings from these discussions include:
Hyper Outsourcing is Here to Stay: In order to remain competitive in this ever-evolving environment, funds will have to adopt a model that can operate seamlessly with an increased number of service providers while maintaining a sense of internal flexibility and control. Gone are the days of the single outsourcing provider model. This archaic strategy is no longer suited for the majority of alternative assets that are being developed and traded privately on a continuous basis. It is now common to see a typical fund leveraging 10-15 outsourcing providers across its entire value chain. Digitalization and the rise of “digital-first” service providers has leveled the cost playing field. The ability to fully leverage technology platforms now enables funds to achieve similar cost efficiencies that in the past were only achievable by the largest asset managers.
Scaling Enterprise Intelligence and Analytics with a Comprehensive Data Strategy: Many funds, big and small, are finding that implementing an impactful data strategy is no small feat. As alternative data, data science and artificial intelligence grow in popularity, funds are beginning to realize they cannot achieve success with these new tools without first ensuring their core data sets are accurate. The panel highlighted some key steps to developing a successful path:
- Firms must first collect and secure core thought processes on data capture, governance and curation for data sets that need to be governed and curated (trades, securities, positions, PnL, counterparty, risk, performance).
- Funds are increasingly using base data sets for additional analytics, leading to definitions of a data layer that continuously expands and evolves without tech involvement. Regardless if implemented as a scalable data warehouse or data lake, clearing and segregating governed and curated data sets, as well as semi and non-governed data sets, is vital.
- One of the most critical aspects in the path to success is getting buy-in at a business level for treating data strategically. The most successful data initiatives have full strategic buy-in, which in turn enables transparency in governance, data lineage and cataloging, making implementation and change management much easier.
Critical Data Pathways: The volume, velocity and accuracy of data demanded by investors on a daily basis is showing no signs of slowing. Because of this, it is vital to have a process in place that allows funds to classify various asset types into a common set of attributes so that the data can be easily digested and used across the front, middle and back office. Funds can achieve this by building a flexible data layer that encompasses standard, curated and governed data sets. By building data governance capabilities to distribute the load of data governance to the exact users most familiar with data sets, funds can avoid overloading technology teams for the same information. Managers will also now have the ability to continuously ingest new data sets, derive analytics and report in insightful ways, all of which a critical core competency for asset managers. A practical path for funds dealing with any big data problems that require elastic compute and elastic storage is to leverage cloud capabilities, which provide success in a highly scalable manner. In order to combat any disorder, funds must have a holistic data governance team that consists of various representatives from each sector of the business in place to challenge and review data before it becomes classified.
Roadmap to the Cloud: As funds move away from their traditional data centers and begin migration to the cloud, it is important to keep in mind that a simple “lift and shift” approach is not the answer to success. A practical path was discussed as a case study for a large asset manager during the conference’s fireside chat. A large $50 billion AUM asset manager leveraged IVP EDM as a toolkit to migrate from a traditional data warehouse model to a scalable data layer concept. Harnessing the Azure version of IVP EDM, the fund was able to fully leverage cloud computing’s elasticity on storage and compute. With deep analysis executed on MPP vs. traditional SQL with columnar architecture, it was found that below 4-5 TB of data columnar performed similar. The fund is now able to offer users new analytic capabilities such as redoing ad hoc performance/XIRR calculations on 250MM rows of data in three to four seconds on any dimension.
Buy-side participants are finding that the industry has reached yet another unique turning point in its story line. As cost pressures and the demand for data reach an all-time high, education has quickly become one of the most, if not the most, effective ways in positioning funds for future success. With an annual gathering of prominent leaders in the space, IVP continues to strive to help buy-side firms harness the power of their data in order to generate insights, reduce risks, gain a competitive edge and discover alpha.
The new offering supports reconciliation, matching and exception management applications.
Wall Street gets a failing grade when classifying and naming crypto assets.
The bank's prime brokerage business is now live on the Global Exception Network.
A small step for trade breaks may lead to giant steps for other applications.
Advisors can create and curate models based on the client's risk tolerance and other factors.