You might have missed this highly informative report from the (EBA)聽 鈥� because the title 诲颈诲苍鈥檛听contain the popular buzzwords of Artificial Intelligence – AI聽or Machine Learning –聽ML (nor does the front cover have a picture of a robot!).
But for anyone who is trying to understand the challenges ahead for AI and broader data management in banking I think this report provides a rare unbiased, concise and highly educational deep dive into pretty much all of the key topics involved. I won鈥檛 give a synopsis here, just some reasons why I think you should read it:
It鈥檚 really all about AI in Banking!
鈥楢dvanced Analytics鈥� is the term the authors use for AI, ML tech.
BS Free
Provides most of the background you need to see through the smoke, mirrors and hype surrounding AI or聽Advanced Analytics.
It鈥檚 a great introduction
But not dumbed down 鈥� Great for business people who need a better understanding of the challenges their data scientists and AI professionals face, and great for data scientists who need to understand the broader applications and implications of this rapidly emerging technology in Banking. If you don鈥檛 know what kind of algorithm might be used for a particular business case this is for you. If you are trying to understand what a data scientist means by accuracy and a confusion matrix this is for you too.
Technologically Neutral
The report maintains technological neutrality and with so much information these days coming from vendors of proprietary tech, in a world where there are few common open standards, it鈥檚 hard to find information that doesn鈥檛 in some way implies vendor lock-in.
Holistic
This report covers pretty much everything including Data Quality, different types of ML, explainability and interpretability, ethics鈥� So many reports are very narrow focusing on one use case or tech, but this takes the whole horizon into account.
Pragmatic
It describes practical use cases for AI and the technology involved 鈥� I was particularly impressed with the technical content: accurate concise and easy to understand. More importantly, it also describes all the potential problems – things like how automated credit scoring could be 鈥榞amed鈥� by an institution鈥檚 sales staff and could coach uncreditworthy customers on how to be granted a loan!
Forward-thinking
The European Banking Authority covers the topics of ethics in AI and even security聽in AI. Ethics has obviously been talked about a lot in recent months (sometimes with slightly fanciful references to Asimov鈥檚 laws of Robotics!) but this report lays out some really good practical steps that need to be implemented to ensure ML solutions are fair. It鈥檚 also refreshing to see serious consideration to security (data poisoning, adversarial attacks, model stealing) a couple of years ago.聽It鈥檚 a bit like in the old days of software development when people didn鈥檛 really take things like SQL injection or cross-site scripting seriously, resulting in security breaches in many applications and web sites. If AI solutions aren鈥檛 built with security from the ground up, the next few years could see echoes of these past security breaches played out in the AI domain.
You can get the report
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