5 Incredible Ways Big Data Has Changed Financial Trading Forever

The financial trading industry is undergoing a tremendous transformation as new advances in big data surface.
big data in financial trading
Shutterstock Photo License - By Phongphan

Big data is making a significant impact on the financial world. The market for big data in the banking industry alone is projected to reach over $14.8 million by 2023.

The impact it’s making is much more of a grandiose splash rather than a few ripples. This is primarily due to the fact the technology in the space is scaling to unprecedented levels at such a fast rate. The exponentially increasing complexity and generation of data are dynamically changing the way various industries are operating and it is especially changing the financial sector.

How Big Data is Taking the Financial Industry by Storm

At this very moment, the world is creating a whopping 2.5 quintillion bytes of data daily. This represents a very significant opportunity for leveraging the information in a variety of ways through processing and analyzing the growing troves of valuable data. An evolving nature of machine learning and unique algorithms are being leveraged within the financial trading industry to compute a large number of data sets to make better and more accurate predictions and to help humans make better and more prudent decisions.

Both finance itself and trading require a lot of accurate data on display to make the best models based on real analysis. In the past, these numbers had to be sorted through by real people. These decisions were based on the data they collected which has a lot of room for error. Nowadays, this entire process is calculated automatically by machines from start to finish. Because computers can go through the data and process it at a huge scale, much more accurate and up-to-date models and stock selections can be made.

In fact, recently, we watched an interesting piece on Trust TV from David Smith regarding the trusts, specifically HFEL. It discussed some interesting topics in light of determining value and stock selection and is worth a watch.

Anyhow, there are a lot of different ways big data is impacting financial trading. Here are the two of the main ways it’s doing so.

1. Financial Models

Nowadays, the analytics behind the financial industry is no longer just a thorough examination of the different prices and price behaviour. Instead, it integrates a lot more including trends and everything else that could impact the sector.

These analytics are much more accurate and include more data that allows better predictive models to be created. These things can end up resulting in much more precision in predictions which can help to minimize the risk associated with making financial trading decisions. 

There is trading at high-frequency that has been successful in the past. The computing timeframe easily trumps the older method of inputting because it comes with dramatically reduced processing times. However, the shift is changing as more and more financial traders are seeing the benefits that the extrapolations they can get from big data.

2. Real-Time Analytics

Algorithm trading is something that is buzzing around the financial industry right now. After all, machine learning has taken such a huge leap forward which is enabling computers to make much better decisions that a human would make. Likewise, machine learning can finalize trades much faster and at frequencies that humans would never be able to achieve. The business archetype is capable of incorporating the best prices and it can minimize the number of errors that could end up being caused due to inherent behavioural influences that would normally impact humans.

This real-time analytics can maximize the investing power that HFT firms and individuals have. After all, they will be able to provide better and more comprehensive analysis which has created a much more levelled playing field because more firms have access to the right information.

3. Risk Assessment

Big data is also very important for actuarial processes. Financial institutions can use data analytics to develop better predictive analytics models to identify the risks associated with lending and project the expected expenditures through insurance policies.

4. Better Cybersecurity

Cybersecurity is another very important area where big data can be particularly valuable. One study found 62% of all data breaches took place in the financial services industry last year, so this industry must be more vigilant than ever. Financial institutions are struggling with a growing threat of cybercrime, which means that they need to use the latest technology to thwart would-be hackers.

5. Recognizing Profitable New Markets

Financial institutions should also appreciate the changing nature of new markets. They will want to use big data to identify areas that they can expand, which should help them grow their revenue considerably.

Matt Bertram
MATT BERTRAM, C.P.C., is the Co-Host of the most popular SEO podcast on iTunes. He is the Lead Digital Marketing Strategist and CEO at eWebResults, a top internet marketing agency since 1999 focused on driving traffic though multi-channel marketing built on Organic SEO as the backbone.