Artificial Intelligence is deemed to be the main driver of the 4th Industrial Revolution. IDC predicts that investment in AI will grow from $12bn in 2017 to $57.6 by 2021, while Deloitte Global predicts the number of machine learning pilots and implementations will double in 2018 compared to 2017. As a result, companies from every industry have been spurred on to seize the trend and innovate
from virtual assistants to cyber security to fraud detection and much more. The majority of C-level executives have identified and agree that AI will have an impact on their industry. However, only 20% of C-level executives admit they have already adopted AI technology in their businesses, according to research conducted by McKinsey. So, there is plenty of scope for change and improvement. The Finance industry is anticipated to lead the way in adoption of AI with a significant projected increase in spending over the next three years.
Until recently, practitioners have faithfully relied upon neo-classical models to measure performance, whether it’s in financial organisations or marketing corporations. AI is the new technology that offers an automated solution to these processes. It has the capability to replicate cognitive decisions made by humans and also remove behavioural bias adherent to humans.
Machine learning and sentiment analysis are specific techniques that are applied in AI. These techniques are maturing and rapidly changing the landscape of FINTECH. In order to process and understand the masses of data out there, machine learning and sentiment analysis have become essential methods that open the gateway to data analytics. To keep up with the ever-expanding datasets, it is only natural that the techniques and methods with which to analyse them must also improve and update.
This conference will help you to demystify the buzz around AI and differentiate the reality from the hype. Learn about how you can benefit from the unprecedented progress in AI technologies. Participants will be presented with real insights on how they can exploit these technological advances for themselves and their companies.
Topics Covered Include
- Fundamentals and applications of machine learning and deep learning
- Pattern classifiers, Natural Language Processing (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
- Behavioural and cognitive science
- The future of AI and its impact on industries
