This may sound odd coming from an Enterprise Data Management (EDM) vendor, but stay with us: the fact is that there are situations where a financial data model can accelerate and de-risk a transformation program, even if you’re not looking for a full EDM platform.
Top two use cases for a financial data model rather than an EDM
There are two primary use cases for implementing a data model rather than an EDM Solution. The first is if a firm already has a home grown EDM system and is looking to add in another type of data; more specifically, if the firm is bringing in a new domain, such as issuer or ESG data, or a new asset class like derivatives. The second use case is if a firm either has an existing repository they want to expand or are looking to create a new one using the myriad tools currently available.
The biggest part of any of these data consolidation efforts is creating the data structures to store it in, and a data model can cut this time and effort down dramatically.
Benefits of a third-party data model
Data models can be implemented using technologies other than the provider’s default choice. Hosted and managed services have removed many such issues, but for firms that have rigid policies on technology, it’s always good to know that the logic of a data model is agnostic of the server.
On the topic of resource issues, using a third-party data model offers flexibility and cost savings. For investment banks and asset managers, the value of a person-year’s worth of work can be in the hundreds of thousands of dollars. Building a data model in-house will take longer than turning to an outside provider’s data model – usually several person-years of work, plus ongoing staffing commitment for maintaining that data model. Added to this, if the 3rd party data model is proven across the financial sector and has been crowd-sourced from all types of industry participants, you gain the added confidence that it’s comprehensive and robust.
Data governance capability is a large part of the success criteria for any data model. The best workflows will not compensate for a lack of ability to have access to the right data or to store it well. Firms trying to build something from the ground up may underestimate the importance or complexity of getting data governance baked into the model, while providers of mature data models have already navigated the pitfalls, with the model operating across business lines and in multiple jurisdictions. With COO’s and CDO’s driving data strategies that depend on good governance as a prerequisite, the reassurance of an established data model can be alluring.
Large sell-side firms, asset managers and hedge funds naturally want to protect their proprietary investment strategies and techniques. Though some firms feel using an industry standard data management platform might inhibit them from using their secret sauce (despite our best efforts to disabuse them of that notion), most will acknowledge that a comprehensive data model can be an accelerator to any data-centric project. And its flexibility will ensure that the firm-specific capabilities that get layered onto it will enable any proprietary methods to flourish in a controlled and easily maintainable way.
Firms may prefer adopting an existing data model rather than a ready-made EDM system if their policies dictate that they build data management software themselves or if they have concerns about the ability of a 3rd party system to deliver everything they need for their clients, whether institutional or retail. Building on a data model and having the freedom to customize everything around it supports this idea of independence and individuality. At GoldenSource we believe in developing comprehensive, standard software that firms can configure to support their individual strategies, policies and working practices. However, we acknowledge and cater to firms that think differently and are looking for components that will make their data management projects deliver a faster return on investment.
Choosing between investing in an EDM solution or a data model is like choosing to buy a car right from the showroom or building a car from a kit. To get the car to perform exactly the way you want, for all the purposes you need it, time and effort is always required. And it can pay off, with the resulting dream car for yourself, or ideal data operations for your firm, fit for purpose on your terms.