Machine Learning in Finance: Challenges, Successes & Opportunities
AI or machine learning is changing the way industries across the spectrum interact with their customers, as well as develop their processes. And nowhere is this more evident than in the financial services business. #Machinelearning in finance is pushing the industry to the edge of technological advancement.
A new @insideHPC special report, sponsored by @Dell EMC and @NVIDIA, explores the benefits, challenges and considerations involved with adopting machine learning in finance.
The guide delves into recent key machine learning innovations in financial services to give readers examples of how the technology is being used today, what’s needed to leverage machine learning, what applications and technologies to use and more. It also offers ways to learn from recent successes in the field, as well as ways to connect with the broader machine learning community.
As financial institutions look to machine learning, they should first acknowledge the benefits, and challenges.CLICK TO TWEET
First up, when considering machine learning in finance solutions, one should start with reviewing the challenges involved to make sure to consider all options and scenarios. According to the guide, challenges include regulation and compliance, cybersecurity and fraud detection, risk management — and, of course, competition.
Next up, the report explores some of the technology behind machine learning in finance. Of all of the technological innovations that have made machine learning possible, GPUs have perhaps had the most impact.
Of course, after learning about the technology behind machine learning, a company needs to decide which solution is right for them. The special report goes into detail on some of these solutions, such as the Dell EMC PowerEdge C4140 server and NVIDIA Volta. Frameworks, such as Caffe, Tensorflow, Torch, Microsoft Cognitive Toolkit (CNTK), and Apache Mahout — used to support machine learning applications — are also explored.
After absorbing all this information, the guide offers case studies, information on professional organizations and further reading on machine learning. Research centers described in this guide include the Dell EMC Customer Solution Center, Dell EMC Machine Learning Knowledge Center and the NVIDIA Deep Learning Institute.
The guide is ideal for those in the financial services industry who are beginning to explore the potential of machine learning, as well as those looking to expand and maximize its use.