AI, Machine Learning and Sentiment Analysis Applied to Finance
14 Mar 2017 - 15 Mar 2017
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Technology innovations meet greatest success in business when these are entirely 'client focussed'. Developments in the retail sector, which is consumer-led, are addressing client demand for more personalised, faster and competitive services. Artificial Intelligence, Machine Learning and Sentiment Analysis are changing the way in which these services are offered. In particular Financial Organisations are creating and leveraging such innovation in the domain of wealth management. This trend is now being taken on board by multiple innovators: academia, start-ups, technology companies and financial market participants.
AI and Machine Learning have emerged as a central aspect of analytics which is applied to multiple domains. AI and Machine Learning, Pattern classifiers and natural language processing (NLP) underpin Sentiment Analysis (SA); SA is a technology that makes rapid assessment of the sentiments expressed in news releases as well as other media sources such as Twitter and blogs. Theconference addresses and explains how to extract sentiment from these multiple sources of information and showcases the advances that have taken place in the field of financial innovation.
Along with many of the highest-ranking speakers from our London events, we are inviting some new presenters; the focus is on the latest research and includes presentations by leading subject experts from all over the world, as well as a number of applications/case studies.
Day 1 - Full day conference tailored for the finance industry
Day 2 - Half day of Tutorials, covering three different aspects of Sentiment Analysis
After the great success of the London and Singapore events, we are now bringing the conference to Hong Kong. Its reputation as one of the world's leading international financial centres makes it an excellent setting for any event aimed at the finance sector.
Topics to be covered include:
- Pattern classifiers, NLP and AI applied to data, text, and multi-media
- Sentiment scores combined with neo-classical models of finance
- Financial analytics underpinned by qualitative and quantitative methods
- Predictive and normative analysis applied to finance
- Applications in Financial Markets