As we near the end of 2020, I reflect on the challenges we faced as individuals and as an industry. Life was upended and the future was uncertain, but together we pushed on in the search for a better tomorrow.
Our frontline healthcare providers, first responders and scientists who are helping to save lives are true heroes. They, along with the tireless efforts of essential workers to maintain global supply chains, have shown us what compassion, persistence and determination truly are.
As new challenges emerged from the pandemic, we also witnessed the global financial industry, and the numerous services, solutions and networks that support its function, put to the test. Facing intense pressure to quickly adapt, managers focused heavily on solving these challenges across their funds’ internal operations through the acceleration of their digital transformation.
The year ahead will likely pose a number of new challenges but will also open the door to new areas of opportunity, evolution and growth for the financial industry. From here, success and further growth will stem from a sustained focus on innovation as the industry pushes ahead with its transformation.
We hope you and your loved ones continue to remain safe and healthy during this unprecedented global health crisis and, together, we will emerge stronger in a post-COVID world.
- Gurvinder Singh, CEO of Indus Valley Partners
Digital Metamorphosis Accelerates Through COVID
Traditional and alternative managers have faced numerous challenges over the past year spanning firm-wide operations, data and infrastructure. The quick shift to a decentralized work environment, due to the sudden rise in COVID-19 cases that brought forth unforeseen levels of market volatility and economic uncertainty, enhanced a number of existing industry issues like cost compression while introducing new challenges like business continuity and communications.
Over the last nine months, it became clear that the managers who had previously implemented a digital-first operating model, leveraging digital-first outsourcing partners, integrated digital workflows and strong in-house data management, fared much better than those who were not “digitally organized.” As a result, many firms were forced to find ad hoc solutions to overcome the operational bottlenecks that coincided with the decentralized work environment, increasing the potential for error and friction in manual workflows over email along with headcount reduction to cut costs.
However, these challenges were met with increased innovation by solutions providers taken up by some forward-looking firms willing to use the opportunity afforded by the crisis to make strategic technology investments. According to a study by Greenwich Associates, “over a third of the managers surveyed plan to increase their technology budgets in the future, with the largest increases expected by midsize firms and North American managers,” noting the pandemic as a driving factor for this shift in sentiment1. With that being said, we have identified three trends that are beginning to emerge and will continue to develop in the year ahead as managers look to strengthen their core processes and remain competitive through the application of technology, ultimately accelerating their digital metamorphosis further:
Data as a Service (DaaS) Becomes Mainstream: Frequent failures of data projects to deliver quantified value has caused a noticeable fatigue in the industry as firms have had to implement solutions and processes that are never fully in sync. For many, tangible results have yet to be seen, despite implementing these projects over multiple years, due to their ad hoc nature, lack of a proper data management foundation and attempts to implement multiple solutions to achieve their goals. Coinciding with this failure to deliver by internal dynamics, a growing appetite has begun to take shape for Data as a Service (DaaS) that is digital-first in nature from firms seeking data that is cleansed and normalized by providers on a fully managed basis. With this type of offering, managers can receive fully processed and cross-referenced mastered data straight into their operational data store (ODS) or cloud layer, thereby allowing them to focus their energies on deriving meaningful insights.
As a result, we will begin to see players, both large and small, shift toward this type of model so long as they have good digital-first providers enabling this service in an auditable manner and an internal scalable data layer to consume/stitch the datasets together for fast and more accurate analytics.
An Established Design Pattern to Build a Scalable Analytics Workbench Becomes Mainstream for Asset Managers: With an industry continually seeking new ways to tap a competitive edge, many have implemented data in all shapes and sizes, from big datasets to alternative datasets. This influx of information over the years has led many to realize that they can derive faster analytics with the concurrent rise of native cloud platforms like Azure Synapse, AWS Redshift and Snowflake, making information accessible to users firm-wide with the front office being the latest to hop on board. However, analysts are finding that 1) there is far too much noise in raw datasets to be of value, 2) data in its raw form needs to be wrangled before analysis and 3) data needs to be combined and cross-referenced with clean operational data so that the portfolio impact can be assessed. Because of this, the need for an “analytics workbench” in the user’s cloud platform of choice has emerged where firms can combine clean/wrangled big datasets with internal clean, cross-referenced and normalized operational data. In this emerging architecture, the classic operational data store (ODS) plays a “fulcrum” role in enabling the front-office analytics workbench for fast analytics and the quick onboarding of datasets. Most buy-side firms are creating scalable cloud data layers to create their IBOR and are leveraging the ODS for the ABOR in a cohesive, synchronized architecture that creates a scalable, flexible data management capability for their end users.
Allure of Private Markets Continues to Increase Through the Pandemic: The COVID-19 pandemic and ensuing near-zero or negative interest rates have created a strong disincentive to sit on piles of cash, leading many to look to private markets for a safe target return-type strategy to deploy their leftover capital. Especially now, private debt and other private fund strategies, like private equity, infrastructure and real estate, have continued to attract capital due to their consistency in returns through various market cycles. To further showcase the attraction of these markets for investors, “Preqin predicts that global private equity AUM will reach $9.11 trillion by 2025,” and “private debt is expected to grow 11.4% annually to $1.46 trillion in five years2.” Unfortunately the firms in this space, however, tend to suffer from fragmented workflows and spreadsheet-driven processes, causing managers to struggle as they scale their businesses. More and more private fund managers are now starting to leverage technology to help increase their flexibility and reduce operational risk as these strategies scale. As a starting point, firms will have to invest in their core automation and accept the need to consolidate their datasets into one golden source to eliminate the back and forth that is currently involved using manual spreadsheets. By having a single “golden source,” firms will become more automated, efficient and accurate in their day-to-day processes as it provides a single source of truth for all key teams, including operations, risk, compliance and investor relations. Unique capabilities are also made available from the maintenance of a golden source, such as looking at actuals vs. projections and how they have changed over time, thereby leading to the potential for AUM growth. This digital organization will be the true indicator of success amongst managers as this area continues to attract assets.
Looking to 2021 and beyond, it is hard to predict exactly what will play out as the arrival of the pandemic earlier this year is a perfect example of just that. However, one constant that remains true is asset managers’ growing desire to take their digital transformation to the next level by introducing technology and automation to achieve new efficiencies and operational continuity. By traveling farther down this path, not only will firms be better prepared for any challenges the future may have in store, but they will also find new areas of growth hidden within their current processes, allowing them to continue operating seamlessly and efficiently in the ever-evolving work environment.
Master Data Management for the Buy Side: Spotlight
Moving up the data maturity curve to harness competitive insights and propel forward
Asset managers have quickly come to realize their need to implement a comprehensive data layer or centralized data repository as the foundation of their firm in order to continue operating efficiently and retain their competitive edge. However, most have yet to reach data maturity, meaning that they are not operationally equipped to deal with data in a fluid manner and the many factors that coincide with its proper management to ultimately reach a place where they can leverage data science to generate insights. In fact, according to a poll of participants in a recent IVP webinar, 20% are still currently in the “Data Chaos” stage of their data journey with 40% in the “Isolated Data Projects” stage, both residing on the earlier side of the data maturity curve where data insights delivery is in far reach.
Challenges associated with mastering new datasets beyond traditional operational ones
As data’s volume, velocity, variety and veracity evolves, the demands on data layers are also changing fast, leading many who are in these preliminary stages of their journey to continually face issues that span data consistency, consolidation, transparency and governance of both operational and new alternate datasets. In IVP’s webinar poll, 77% of participants claimed they lack a centralized place within their organization for key functions like data discovery and consumption, causing them to continue to struggle to move up the data maturity curve.
Additionally, when asked how quick and easy it is for them to set up integration with a new source system, 38% of poll participants cited that the process is “hard and slow,” which means their organizations lack the flexible architecture needed to continue onboarding new datasets easily and efficiently. With this, managers are beginning to realize that they can no longer function in such a decentralized and fragmented way, especially within our ever-evolving remote work environment.
Data Maturity Curve
A reference architecture for a scalable and flexible data layer emerges
With IVP’s Master Data Management (MDM) solution that implements IVP’s reference architecture for the buy side by combining both an operational data store (ODS) and a scalable cloud MPP data warehouse, asset managers can now move away from their use of patchwork, opaque systems that were not designed to work together and, instead, turn their attention to a comprehensive and integrated platform that provides the ability to flexibly and rapidly add new datasets using low-code/no-code GUIs. IVP’s reference architecture enables buy-side firms to marry a traditional ODS containing all of its calculations and datasets and merge them seamlessly with alternate market, non-numeric datasets in cloud platforms like Snowflake, Azure and Redshift. From here, managers can tap fast analytics when they start crossing into big data territory (> 6 TB).
In essence, this reference architecture allows managers to solve many of today’s data challenges by organizing, categorizing and localizing their diverse datasets with an integrated solution. By providing data processing, federated governance, lineage, catalog and distribution with a no-code implementation model, key business users are enabled to set up data flows and productionize them rapidly.
IVP’s Master Data Management cloud-based suite includes all of the solutions asset managers need to successfully acquire, process, store, move and keep track of any mix of data throughout its life cycle. Comprised of Security & Reference Master, Entity Master, Enterprise Data Management, Polaris and Decision Science, managers can leverage IVP MDM to move further up the data maturity curve as they look to tap competitive insights in their search for alpha. Learn how here.
Enhanced AI/ML Suggestion Engine
New algorithms allow users to dive into past actions and open break volume, recognize patterns and predict the next probable action with a higher degree of confidence
Automatic Posting to Upstream & Downstream Systems
Seamlessly integrates with OMS and accounting systems such as Geneva, VPM, Trader, etc.
Posts missing transactions directly from the break blotter across transaction types
Smooth Business Continuity & Operational Success Amid COVID-19
Serves as a center for teams to collaborate
Provides secure and protected access anytime, anywhere
Access to IVP’s Managed Services & Support teams 24/7
Low interest rates mean increased liabilities for insurance providers. Therefore, investment allocations to private equity, private debt, CLO managers and hedge funds will need to increase to manage asset-liability mismatch. Investment in alternatives also adds liquidity risk, which means insurers need to maintain adequate regulatory capital.
As a result, insurers must strengthen or upgrade their legacy systems to enable efficient operational data management, portfolio management and risk management.
How automation technology reduces manual work, improves control and mitigates operational risk
Collateralized loan obligations (CLOs) are special purpose vehicles designed to invest in, hold and manage pools of leveraged loans as a fund.
CLO managers are responsible for diligence and must take care of credit strategy and performance management along with non-investment functions in the middle and back office, which tend to be challenging and most intense during month-end.
Credit/Loan instruments, and reconciling asset servicing transactions such as interest, paydowns and expenses, can be extremely complex as they tend to have unstructured and inconsistent transaction descriptions.
Making the business case for agile data infrastructure in private equity
In the last few years, private equity firms have rapidly started adopting new technology and digitization initiatives, which enabled them to replace manual processes and improve efficiency.
For the successful adoption of new technologies, firms are taking a closer look at their operating platforms for both IT and data warehousing, making a unified data layer fueled by a mix of well-governed datasets the need of the hour.
COVID-19 has dramatically impacted the sector outlook for the year, putting private funds, their investment strategies and their portfolio companies to the ultimate test. Through the many challenges faced by these funds, a common theme that has emerged is the stronger drive towards digitization with transparency and ESG taking a more pivotal role.
Heading into 2021, the drive for greater transparency remains an absolute priority for private funds and their stakeholders, particularly regarding portfolio performance. With this, ESG considerations have also escalated in importance, specifically in terms of how firms run themselves and the companies in which they invest, leading many to employ smarter technologies and digitization to drive operational efficiencies that support the push for greater transparency and new investment opportunities.
Automated Tracking & Management of Portfolio Company Data
Automated processes to manage and monitor diverse datasets
Approval workflow processes with multiple levels of data validations for better data control
Seamless communication enabled within the firm and across portfolio company contacts
Portfolio Transparency & Analytics
360-degree views and analytics for deals/funds
Insights generation based on a cognitive engine and exhaustive calculation library
Power BI supported by customizable analytics generation
ESG-focused data tracking and insights for funds
Data & Process Governance
Golden copy of deal data with bitemporal data management
Operational processes supported from pipeline to deal exit
Custom management for KPIs, covenants and documents for the investment portfolio
Accelerating Your Adoption of a Digital-First Model
IVP’s on-demand webinar series will take you through the benefits of being digital-first in various fund processes
IVP in the News
Awards & Recognitions
We are pleased to have been recognized this year for our best-in-class services and solutions
2020 Hedgeweek US Awards Best Treasury Management Solution Provider
2020 Alt Credit US Services Awards Best Portfolio Management System (IVP Credit)
2020 IMD & IRD Awards Best Data Governance Solution
2020 HFM US Services Awards Best Treasury Management Solution
2020 Data Management Insight Awards Best Data Governance Solution, Best Buy-Side Data Management Platform & Best Buy-Side Managed Services Solution