Introducing Data and Analytics Solutions

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Introducing Data and Analytics Solutions

May 2020

By Charles Teschner

Starting from a position of strength, this new initiative will enhance the management of data, improve data accessibility, and deliver high-quality data content and applications.


The need of investment management organizations to perform well on multiple dimensions—such as investment returns (alpha, beta, absolute), fees earned, efficiency ratios, and overhead and compliance costs—has never been higher. At the same time, their business and operating models are also evolving as new types of technologies, employees, and client, stakeholder, and regulatory requirements emerge. Specifically, cloud technology, data scientists, and digital information delivery systems are gaining attention on the management and board agenda.


What do all these factors have in common? Data. Data as a competitive advantage; data management as a capability; data, arguably, as an asset class in its own right. At BNY Mellon, our mission is to enable the success of our clients, and we have created an integrated suite of new capabilities to support our clients in managing the new data-driven world: BNY Mellon Data and Analytics Solutions.


Formed last year, BNY Mellon Data and Analytics Solutions combines the capabilities and resources of our market-leading Eagle product suite, our Intermediary Analytics business, and a host of new and existing talent, technology, and data assets. Our expanded continuum of solutions offers more capabilities for compiling data and transforming it into higher alpha and cheaper beta, with lower cost and less risk.


At Data and Analytics Solutions, we know that for many investment organizations, reaching the point at which the realized value of data lives up to its promise is not easy. The infrastructure and associated services are what empower organizations to use data for competitive gains, and the underlying framework and tools for acquiring, analyzing and managing data matter.


Today, investment organizations need access to multi-tenant cloud solutions, capable of ingesting, tagging, and fingerprinting multi-format, multi-sourced data. They need to empower users across the enterprise to engage with and collaborate on data. Data science demands specific skillsets and tools for utilizing machine learning and artificial intelligence (AI) capabilities that can validate, cleanse, and analyze data. Moreover, given the accelerating pace of innovation, in order to attain a sustainable advantage, buy-side firms must have a dynamic library of applications that are inclusive of third-party solutions to address mission-critical demands and challenges as they emerge.


Recently investment managers have followed one of two paths as they digitize and evolve their technical capabilities. They have either evolved into high-tech firms by hiring programmers, data scientists, and data engineers, or they have outsourced all the technology and analytics to third-party providers. Our vision in creating Data and Analytics Solutions is to serve both types of firms. Our solutions are based on a growing well of data and expansive relationships—the extent of which are available to only the very largest global institutions. We couple these capabilities with the agility and innovation of a fintech, one with industry-leading technology already at its disposal.


More important, BNY Mellon is already using our client-centric solutions to provide value to clients. At the same time, we are extending the solutions while collaborating with leading technology providers to support the vast needs of investment managers and bring the data to where people are making decisions. The result—and really it’s just a starting point for our more expansive goals—is a fintech within a bank that delivers cutting-edge technology and has the backing of an institution with a 235-year track record of transformation and reinvention.


One of the technologies we are now developing involves prescriptive analytics. The difference between descriptive and prescriptive analytics can range from a sunk cost, with negative value, to a billion-dollar insight that drives a business. We contemplate which factors will most contribute to long-term client success through this lens. Using the power of data and analytics, we believe that by helping our clients succeed, we can create a world-class solution.


Building off a Data Management Foundation


Eagle Investment Systems has been the data management, investment accounting, and performance measurement solutions vendor within BNY Mellon Asset Servicing since 2001. In launching Data and Analytics Solutions, we are extending Eagle’s continuum of technology, software, and services. We are also building upon the information and expertise of BNY Mellon’s Intermediary Analytics and broader BNY Mellon technology, services, and data assets. From this strong foundation, we offer more software and content, as well as more cloud capabilities and computing power.


Eagle products have traditionally supported the middle and back offices. As Data and Analytics Solutions, new capabilities will continue to support technology departments and operations while expanding support to the front office and aiding the data science teams that now exist within every corner of an organization. The front office, for instance, benefits from new content and applications that extend current data solutions to inform new product development, investment strategies, or distribution opportunities. Within the back and middle office environments, new applications and services democratize data, thereby bringing capabilities and content to those outside of the data science or technologist functions. Additionally, because our solution set is inclusive of third-party capabilities and has one universal touchpoint, we make content and next-generation tools available to more users within an organization, as well as to different consumers throughout it.


Among the first cloud products that soon will be available to clients is a Data Vault, a data store capable of ingesting, tagging, and fingerprinting multi-format, multi-source data. Application programming interfaces, or APIs, allow users to access relevant structured and unstructured data, while pre-built adapters streamline the ingestion of external data across a wide range of sources. A catalog within the Data Vault will help ease navigation for data stewards, engineers, or analysts. Meanwhile, validation and enrichment rules will ensure data veracity, as the volumes, velocity, and varieties of data continue to increase or accelerate exponentially.


Content & Applications


The launch of Data and Analytics Solutions also enables us to see and build upon distinct synergies—both within our organization and with our clients. As one of the largest global custodian banks, BNY Mellon handles approximately 25% of the world’s total assets under custody and administration. Via an opt-in model to explore anonymized data sets flowing through BNY Mellon’s broader business, we can collaborate with clients on how we can best leverage this information.


Our ingrained culture of partnership, which enables us to collaborate with clients, also enables us to cooperate and make the most of our inherent strengths. Specifically, Data and Analytics Solutions builds on Intermediary Analytics’ insights into the geographies, strategies, and styles of attracting capital. BNY Mellon’s broker dealer clients and asset managers already utilize this business intelligence to track fund flows for setting priorities around product launches and for understanding how to position new funds or products against incumbent peers. As we move forward, we plan to use this data to support predictive analytics that reveal how changes to the market or competitive environment may alter future fund flows. Moreover, institutions may leverage prescriptive business intelligence to refine and optimize sales performance, due diligence activities, and any other oversight efforts, continually.


To engender this kind of value, however, users need to engage with, and easily manipulate, literally billions of rows of available data. Data and Analytics Solutions will roll out tools to query, analyze, and visualize available data. Beyond ingesting and validating raw data at scale, users can refine and manage their statistical models, generate actionable analytics under tight timeframes, and leverage machine learning and AI applications to discern otherwise imperceptible patterns. We will also automate data collection, while making integration and analysis functions accessible through intuitive interfaces designed to accommodate both sophisticated data consumers and business users leveraging apps with predefined rules and logic.


Not to be overlooked, our managed and professional services offerings already allow organizations to either outsource fully or complement their existing data and technology teams with experienced professionals. These experts know the technology and understand the data demands of buy-side organizations. Their mandate, outside of adding valuable capacity to scale quickly, is to assist clients with getting the most out of their data and technology solutions.


An Open Ecosystem


To realize a competitive edge, buy-side firms used to develop a proprietary, all-in-one technology customized to their unique needs, but, as with all technology, the fintech world has changed dramatically over the last ten years. Imagine if your Apple iPhone couldn’t access Google Maps or your Mac couldn’t open or share Word documents. The pace of innovation, the democratization of new fintech solutions, and the power of co-creation have conspired to turn detachment and strategic isolation into a costly disadvantage.


Hence, Data and Analytics Solutions’ open architecture in developing technology and open ecosystem in leveraging BNY Mellon’s extensive client relationships, technology collaborations, and strategic alliances both guide and create a strong foundation. Our extensive applications library can consume data and analytics from internal and external sources to serve a range of constituencies—from operational and distribution roles to the C-suite, investment teams, and other key stakeholders.


Data as a Competitive Advantage


The fourth industrial revolution can seem overwhelming when one considers the pace of developing technology, inundation of data, disruption to prevailing business models, and changes to how companies and assets are being valued. Wall Street, heretofore, wanted to find the disruptors to invest in; now some asset managers are concerned the disruptors will find them. Against this changing backdrop, the difference between winners and losers will be determined by those who recognize the opportunity that exists versus those who do not.


We understand that the immense and growing volumes of data demand transparency in order for buy-side firms to access a “true view” of their positions and performance. This is the ante simply to compete today. Analytics and increased efficiencies through automation, however, will become necessary to gain an informational edge and the operational advantages that allow buy-side firms to address problems and opportunities quickly and with conviction. This, of course, can take form any number of ways, but it may ultimately translate into a firm’s competitive advantage.

Charles Teschner

Global Head of Data and Analytics Solutions

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