Data has Changed the World
Data has changed the world. If that seems like an exaggeration, consider this ICTC report that estimates the Canadian Big Data service market will generate more than $1.1 billion in revenue during 2019.
The financial services industry has a massive customer base, heavy regulation and is known for being hindered by ‘red tape’ decision making. As a result, the industry is primed to benefit from the use of big data to streamline both internal operations and decision making around investment strategies.
To understand how data (specifically Big Data) has created a massive shift in the financial services industry, it’s important to first understand Big Data and the 3V’s.
What is Big Data and the 3V’s?
Most people have experience working with, or seeing, data that has been organized into information. An example would be an Excel Spreadsheet of contact information for all attendees of a charity event that will be used to confirm their attendance. Therefore, information is when data is processed, organized, structured or presented in a given context so as to make it useful.
When someone refers to just data, they are talking about a specific set or sets of individual data points – the key being the specificity and manageable quantity of the data points. Traditional analysis tools and software can be used to “crunch” the data and, hopefully, provide meaningful insights for a business.
Although Big Data is still comprised of data points, it’s the difference in amount – specifically the Volume, Variety and Velocity – that characterizes it as Big Data. The rise of companies like Salesforce, Adobe and Facebook have led to the development of what is essentially a ‘data brokerage’ business model. These brands are dedicated to the collection, processing and selling of mass amounts of data to other businesses. An IBM Cloud Marketing Survey in 2017 found that 90% of the worlds data had been created over the past two years, and I’m sure it’s much more now. Our current way of processing data just couldn’t keep up with the pace, amount and variation of data being created today. Hence, we named this new wave “Big Data” and a multi-billion dollar industry was born.
Big Data Is An Evolving Term
Big Data continues to be an evolving term as more capabilities come into the market. This has been a global shift and Canada has been keeping up through in areas such as Montreal, a city that has become a global Artificial Intelligence (AI) hub. AI and it’s progress is fed by data, and the rise of Big Data has meant more funding, research and innovation for the industry.
The real win for any technology company is being able to show a real-world application for using Big Data to power AI, Machine Learning (ML) and other advanced analytics platforms. There are certain industries, such as the financial sector, that currently operate in conditions primed to benefit the most from Big Data capabilities. With Big Data investments from the Financial Services Industry projected to account for nearly $9 billion in 2018, it will be interesting to see how that number changes in 2019.
Financial Services & The Big Data Fit
The term Financial Services encompasses a variety of sub-industries that all impact our economy in different ways. Although risk management looks different on the surface than short selling, market conditions for these sub-industries have proven to be relatively similar.
While the following points are by no means an exhaustive list, they highlight the main reasons for the Financial Services industry as a whole to benefit from the rise of Big Data applications:
- Increasing volume of financial transactions
- Increasing complexity of financial transactions
- Heavy regulation focused on risk mitigation and management
Earlier in this post we outlined the three defining characteristics of Big Data as Volume, Variety and Velocity – seemingly a perfect fit with these three points about Financial Services. Out of the three features, Variety is the most important as it directly impacts future risk management. The future is what financial institutions are worried about, and it’s also the area we are currently lacking in the most – that is, regular old data can’t provide us the insight we want to make better decision for future performance.
The Next Big Push: From Trading to Trends
Some of the earliest investment in Big Data was to develop algorithmic trading that could perform highly complex financial transactions at a much greater speed and precision than human traders. In March of 2018 there were already articles saying, “Algorithmic based trading is therefore more precise, more accurate and faster than manual trading.” The promise of increased profits is exciting to both those who have investments along with those who manage them. As other trends in the HR space such as employee performance and engagement start to show an ROI, Big Data is posed a great candidate to understand why.
Tools and technology around Big Data are becoming more widely adopted in the Financial Services sector and we can expect the use cases to expand along side. We will likely see trends grow from pure risk mitigation to include a more in-depth mapping process of the customer and employee journey.
Big Data for The Big Picture
Independent of industry, the terms Customer Journey and Employee Experience have been cited in annual reports as being major areas of focus for C-suite level personnel. One could look at these two ‘areas’ as a new set of data points that could be processed using Big Data tools that will, ultimately, help financial businesses understand the relationship between resources and results.
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