Must-reads to understand the impact of machine learning on fintech

Must-reads to understand the impact of machine learning on fintech

Machine learning is a concept currently in vogue. However, not all of us would be able to explain what it consists of.

16 Nov. 2018

These articles will get you up to speed with the latest machine learning developments and advances and how they affect and could add value to the fintech industry and open banking:

AI and Machine Learning in Fintech. Five Areas Which Artificial Intelligence Will Change For Good

In this article in Netguru, Timothy Clayton lists five areas in which artificial intelligence and, most specifically, machine learning are setting the tune for the development of new fintech products: customer service is redefined with bots and other AI interfaces; credit scores are faster and more reliable; trading and money management are enhanced; regulatory compliance is facilitated with automation; and the fight against bank fraud is made a lot easier.

Deep Learning in Finance

In Medium, Ted Moses explains the most recent developments in deep learning applied to trading. By now, we have all heard about the robotization of financial trading globally; in this case, however, we go into a new level of sophistication. Deep learning performs extraordinarily in establishing patterns from data and later identifying these patterns from large amounts of data. Moses talks about the research done by Babak Hodjat toward what is already called "deep trading," a concept you must look out for. You will start hearing it more and more often in the immediate future.

How is machine learning used in Fintech?

This thread in Quora is very interesting if you are looking for inspiration from very specific examples of how machine learning can be applied. The replies/contributions from the Quora community to this question include such issues as predicting business bankruptcy, cybersecurity, the backdrop and information surrounding a topic you need to make a decision on and which has financial consequences, etc.

Artificial Intelligence and Big Data applied to the banking business

This article posted on BBVA API_Market a few months ago describes the positive consequences for banks of the combination of artificial intelligence and big data: enhanced product definition and better fight against fraud. It contains loads of examples, applications and techniques.

And, lastly, a critical article to put your feet back on the ground amidst so much (justified) hype surrounding machine learning and artificial intelligence. Linda Zaikovska-Daukste, CFO/Co-Founder of UX Design Agency, looks critically at the (sometimes) unjustified emergence of interfaces and services based on machine learning derivatives such as chatbots. From the perspective of the User Experience, Linda explains that sometimes these are not the best option to achieve an appropriate client-centric strategy, which she adamantly defends. Interesting opposite view.

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