The Data Revolution is Coming
The Data Revolution is coming, but first, 4 things need to happen in financial services
By Lisa Iagatta, Chair, International Securities Association for Institutional Trade Communication (ISITC)
The Industrial Revolution is a period of human history that marks a distinct turning point where technology dramatically transformed society. Advancements like the cotton gin, steam engine, and power loom advanced daily life and allowed civilization to flourish beyond what was previously conceived as possible. Two centuries later, another Revolution is on the horizon, and it’s being driven by data.
Technologies like artificial intelligence (AI), machine learning, and blockchain are primed to upend the financial services industry and society at large, but they would not be possible without a solid foundation of high-quality data. Phrases like “data is the new oil” are becoming clichés in our industry, underscoring how far we’ve come in acknowledging the value and power of data. Data offers insight into everyday mechanisms, actions, and processes that could change life as we know it.
But if the industry is going to survive the data revolution, it needs to discard the outdated infrastructure it relies on and embrace a completely different way of thinking about how we organize and interpret data. Otherwise, the industry will fall behind the groundswell of change.
How we understand data has to change
In order to capitalize on the value of data, the financial services industry needs to establish a uniform language when discussing and interpreting data. Although adopting the same language sounds like a solution, simplifying this complexity is a fool’s errand. While standards are necessary to organize data and certainly help the cause, looking to semantics ontologies is crucial, because the issue is a language barrier rather than a data barrier.
A new approach being formulated within ISITC by Rich Robinson takes lessons from the linguistics field to bring firms from all subsets of financial services to a common understanding, especially in regard to understanding where differences in language, data, and meaning exist. Although today’s languages evolved from cultural and geographic differences, linguistics has formal rules for differentiating languages, providing value by allowing society to use adapters between languages based on context and usage. A semantic representation of data allows you to look at the definition in context, facilitating data interpretation among various financial domains. A great example of this is EDM’s experimentation with FIBO and how it’s used to offer a Data Dictionary, Glossary, and Web Ontology Language (OWL) in a variety of file formats and dialects. Initiatives to start the industry on the same common ground while adapting to accommodate differences will be crucial for industry-wide comprehension of data.
New technologies necessitate new structures
Data is currently structured in rows and columns, which has been the standard for over 50 years. This structure, in addition to the report-based paradigm in which the industry provides regulatory reporting, was developed before computers were even invented. Although data does not change, technology certainly does, and it’s time to modernize financial services systems to take advantage of the innovation.
To be a frontrunner in fintech, you need to be able to understand your data and how they relate. By taking a semantic representation to data rather than the traditional linear format, you can look at data in a 3D representation. This provides a clearer understanding of how various data points are related, which enables insight for technologies like machine learning and AI. While much of the industry is focused on the possibilities of technologies like blockchain and AI, those mechanisms will never be attainable without the foundation of understandable, organized data in place to ground them.
The industry needs interoperability to pave the path to efficiency
Organizations need to deliver data interoperability in order to be more efficient as a business. If you share data while maintaining its meaning and relationship with other data, you don’t have to reinvent the wheel every time data is exchanged. One way to ease this interoperability is to change to a data-based paradigm rather than report-based paradigm, because if firms are equipped with the data, they can do their own analytics and use the data to their benefit.
Standards groups used to focus their efforts on creating standards that cover each specific domain of financial services. However, with technological and business changes taking shape, they’ve now begun to concentrate more on semantics to promote interoperability between the various segments of financial services and offer standards that can be related on an equivalent basis. Interoperability between standards will allow the standards to build off each other and operate within the same ecosystem.
Progress will be impossible without industry collaboration
All of the best players in the financial services industry need to be at the table to create real change. Look at the financial services ecosystem in its full context, and you’ll see a wide array of organizations that are all focused on a particular specialty. Leveraging every organization’s expertise allows the full ecosystem to benefit from each other. By bringing in subject matter experts from the ideation phase to execution, the whole industry wins.
In addition to creating mutually beneficial systems, industry leaders need to invite regulators into the conversation. By engaging regulators, organizations can determine if there is a way to define data sets once and report in a way that doesn’t necessitate retooling with each new regulation that emerges. A system that is able to adapt and accommodate new regulations would vastly increase efficiency industrywide. Additionally, applying data standards to regulation substantiates the industry’s uptake of the best data practices. Standards don’t work unless everyone is on board, and standardizing everyone under regulatory principle is an effective means to uniformity and consistency.
Technologies like blockchain, AI, and robotic process automation (RPA) all have the potential to transform the financial services industry as we know it, but that won’t be possible without the help of data. Like the Industrial Revolution, the Data Revolution is one that can optimize processes, cut costs, and increase efficiencies across the board. In order to harness its full potential, a common system to interpret, organize, and collaborate on it is imperative. Once our industry is able streamline data practices, the possibilities are endless.
New policy and regulatory changes are driving demand for better data.
The exchange's network will enable a range of market participants to access high-quality crypto data.
There is growing interest in actionable insights into market data.
ApeVue provides daily prices for around 100 non-public companies.
Limited competition for benchmarks and indices, credit ratings and trading data may increase costs.