The Asset Manager’s Challenge
Overwhelming volume of data
Given the plethora of data circulating the financial industry and the amount that asset management firms consume, it is no surprise that they are struggling to keep up. As per today’s increasingly digitized world, data flow into your organization is more akin to a build-up of waves that inevitably develops into an overwhelming tsunami. Without an adequate way to manage data, having more data is like having less. This constant data injection results in problems such as inability to find resources, duplication of data assets, untrustworthy and unusable data contaminating the information needed making them highly difficult to distinguish. Organization’s data landscapes as it is are already disjointed, existing in several silos across different departments, hence adding more data to manage at such a rate that worsens the problem.
Untrustworthy and unusable data
When raw data enters your systems, it is in various forms that are often unstructured and unusable. Furthermore, there is no assurance that the data is valid and accurate. This especially becomes a problem for asset management, when data is procured from a multitude of sources and third-party organizations. Given the decision-making nature of asset management, the value of having correct information and the major issues posed by unreliable data cannot be understated.
As par for the course, working in the financial industry necessitates conducting responsible practice. However, with today’s data demands ever increasing it is very easy for individuals within your firm to make mistakes, which may be very minor but extremely costly nonetheless. The industry standards of finance are very complicated, as asset management firms are often subject to multiple sets of stringent regulatory requirements across the globe.
The Global Investment Performance Standards (GIPS) serves as the leading standard by which asset management firms for performance reporting. Whilst buy-side firms must follow this, depending on their operation, they may be subject to other regulations such as the MiFID, ASIC, CSRC or SEBI, among a multitude of others. In addition to this, another layer of complexity is added as investment funds must consider regulations regarding liquidity, risk-reporting, and investments in derivatives. The International Financial Reporting Standards 8 (IFRS 8), Basel III, and Solvency II impose further compliance demands that undoubtedly affect the business models of firms.
These regulations are fully aware of, and designed in response to, the explosion of data that organizations face and the exposed, vulnerable data this entails, to force financial institutions to adapt accordingly. Therein lies the difficulty for investment funds as they must be aware of which regulatory requirements they must adhere to, know how to be compliant within the constraints they must operate in, and execute this whilst remaining profitable.
Regulators are not the only ones calling for increased transparency in the workings of buy-side firms. After the financial crisis of 2008, clients are more alert to the details of the financial institutions’ operations. Hence, in the asset management field, there is an even heavier emphasis on reporting.
The investment fund clientele is calling for greater functionality, granularity, and detail in their periodic reports. High net worth clients, especially, are demanding increased specialization. Portfolio analysis, performance calculations, and risk analytics, in particular, have turned out to be the most important areas of focus in order to win and secure client trust.
The Data Governance Solution
Traditional technology that investment funds use function to merely store data instead of consuming it. Storing data with limited means of using it renders it just as if there was no data at all. Given the slew of problems and pressures that asset managers face, it is nearly impossible for buy-side firms to be operationally efficient without a sound data management framework in place.
Resulting from the data demands of the times and the emergence of heavy regulation, asset management firms have scrambled to sort their data effectively. One common mistake for capital market firms was that they attempted to solve each problem, issue-by-issue. For example, using one tool as an inventory for their data, using another tool to try and analyze their data, and another for the security and privacy of this data. This approach proved to be inefficient, unmanageable, and costly. Ultimately, the solution is a data management platform that encompasses all the tools needed to holistically assess and govern data.
The term ‘enterprise data catalog’ is a major oversimplification of what the tool actually provides. One core principle of Alex is being ‘technologically agnostic’, meaning that it is purposely overloaded with all features necessary for specialty analytics of data in the financial industry. Automation is embedded into every aspect of Alex’s data governance tools to achieve both powerful functionality from a wide range of features, and simplicity in its operation designed for business users.
Automatic Data Management
As an enterprise data catalog itself, Alex is able to automatically scan any volume of data landscape of both structured and unstructured data. Armed with the world’s largest marketplace of plug-and-play metadata connectors out of the box, organizations with Alex are able to harvest the richest metadata with minimal effort. Data assets that may have been hidden, duplicate, or in forms that were unusable are integrated within the Alex Platform so that they are inventoried in a manner that is clear to oversee. With this, navigating data through Alex is quick and easy via its ‘Google-like’ search engine with advanced capabilities for more specific searches.
Alex allows you to easily build out ontology and create an enterprise-wide business glossary. Creating a shared business language for asset management is particularly useful as data is acquired from a vast array of sources which can result in clutter and confusion. This enables users to identify data assets quickly and eliminates ambiguity on what that data may be. In doing so, alignment is driven between business and communication teams allowing your whole organization to run smoothly and synchronized.
Ownership can be established to data assets with defined roles. This has the effect of attributing accountability to data assets so that they are handled with greater precision and care. Additionally, users who encounter certain data assets have a channel to contact data owners to ask questions or request permissions. Implementing a system of data ownership acts to increase the ability to create, access, protect, and consolidate data assets.
Alex is renowned for its data lineage, providing a comprehensive end-to-end view of data and all its transformations. Any data that ends up in a portfolio or report can be traced to any point in its lifespan, all the way back to the source. It is the only platform that enables users to perform real-time impact analysis of a piece of data, from anywhere within your data landscape, at any time. For the asset manager, these sort of functions are especially critical as it equips them with the best information possibly derived from their data, which in turn maximizes their decision making. Alex users do not need to worry about the accuracy and validity of their data and can focus on their investment strategies instead.
When Alex scans your systems it is able to detect all sensitive data such as but not limited to PII, PCI and PHI, to be profiled. Such data assets are flagged as ‘critical data elements’ or CDEs to signify their sensitive nature and can be imbued with specific policy controls that are compliant to all relevant regulations. This ensures that only users with permissions can access them and they can only be used appropriately. Alex data security is highly configurable to suit every situation perfectly and can be applied instantly, across the whole firm.
Furthermore, Alex utilizes usage and permissions heatmaps to autonomously and constantly monitor sensitive data whilst looking for data and systems that are at risk of exposure. When vulnerable data is discovered, data owners are notified for remedial actions to be undertaken. Alex’s data lineage allows for your data security team to pinpoint the exact moment and reason a data asset had become compromised. These circumstances are where Alex’s machine learning capabilities shine as the Alex Platform and its users learn from potentially exposed data to revise policy controls and build up an even more secure system.
If governing and managing data is one side of a coin, then analyzing it is the other. Alex equips you to do both at the highest level. From its inception, Alex’s mission has always been to provide the highest level of technical prowess whilst being intuitive by design. Given the financial industry’s data demands and generally business-oriented individuals, as opposed to technologically adept users, Alex’s marriage of powerful automation and simple operation is suited to investment funds. With these tools at an asset manager’s disposal, their focus can be on generating returns and investment outcomes, facilitated by unimpeded data access, high-quality information, and without the distraction of looming data privacy breaches.
Alex Solutions is highly experienced in working with buy-side firms, thus we can assist you achieve digital transformation and realize your business goals. To learn more about Alex’s data governance or how Alex can help you in asset management, please request a free personalized demo below.