Home Finance Artificial Intelligence Revamping the Bond Market

Artificial Intelligence Revamping the Bond Market

Artificial Intelligence Revamping the Bond Market
Images: Flickr Unsplash Pixabay Wiki & Others

When you enter a bank and have a robot greet you, that’s when you know artificial intelligence (AI) is becoming a key part of banking, and that’s exactly what’s happening to customers at Canadian Bank ATB Financial. But, it doesn’t stop there. These AI are also capable of transforming the entire bond market as we know it.

Since the financial crisis of 2008 bond trading desks has been struggling. AI, however, has the potential to turn that around. The way it works is like this: historical bond trading data is used to decide which customers trade with which banks, those they trade with most often, and what securities they trade.

That data is then analyzed by AI tools to then recommend who should be involved in the trade. Taking those recommendations into consideration brokers should be able to improve their performance and satisfy more easily the demands of their clients.

This kind of AI is the same kind that Netflix uses to recommend movies to its customers. Using AI analytics in a bond trading setting will eliminate much of the guesswork that’s currently used. Now traders can see exactly what customers bought the previous week. Dutch bank ING has been trying out this approach via an AI tool called Katana. JPMorgan Chase has also been playing with AI tools in order to help traders and sales staff predict how markets will flow.

READ MORE – Top 25 AI Software for the Banking Industry

READ MORE – 10 Applications of Machine Learning in Finance

And that’s just the beginning. Technology is advancing very quickly and soon will be able to do all the things we only ever dreamed of in the bond market. AI can help to facilitate trading across different market segments, bringing together buyers and sellers in a timely manner. But to get there banks will first have to clean up all the dirty data that’s in existence. This is data that could be unsorted or duplicated, or simply untrustworthy.

In order to make the most use out of AI, standards and best practices will need to be put in place in regards to how this data becomes normal. At the moment, a structured note, for example, could mean something completely different to two different dealers. Standardizing practices will make things much easier for everyone.

Earlier this year, at the Consumer Electronics Show, The New York Times stated that “the clear darling of this year’s show was not a gadget but the growing amount of artificial intelligence software”.

Source Bondbuyer

Previous articleAI Guru Andrew Ng Raises $175m To Invest in AI Startups
Next articleAmerican Express Acquires AI Startup Mezi
KC Cheung has over 18 years experience in the technology industry including media, payments, and software and has a keen interest in artificial intelligence, machine learning, deep learning, neural networks and its applications in business. Over the years he has worked with some of the leading technology companies, building and growing dynamic teams in a fast moving international environment.