Read on for an introduction from Bloomberg's CTO, Shawn Edwards, and explore the report contents and topics.
Contents
The impact of machine learning & AI on investment strategy > Topic tags as a key tool for optimizing sentiment analysis
The quest to mine true value from big data > Machine learning plays a critical role in improving data quality > Extracting value from social and news data
A new era of risk and regulation > Regulations are both an obstacle and a boon to AI adoption > From risk analysis to returns forecasts, machine learning is guiding investments
The changing role of the sales trader > Trading desks: Toward an augmented future. Lessons in disruption from the energy industry > Tech update from Bloomberg NEF
Diversity and the changing face of FinTech > Advice from the experts: How to grow the space for women in FinTech
Note from Bloomberg's CTO, Shawn Edwards
Automation, artificial intelligence and machine learning are poised to transform the financial services industry. These technologies are growing in sophistication and driving investment, influencing decision-making in areas such as data analysis, investment strategies and workflow automation. Featuring articles and insights from across Bloomberg, this report explores developments related to these technologies and their impact on the future of the industry.
As AI and other advanced technologies permeate the workplace, skills like critical thinking, creativity, and problem solving have become more and more important. Leading companies are recognizing that these technologies are most effective when they complement humans, instead of replacing them.
While education and retraining are critical to adapting to new technologies, there is no doubt of the value to be gained: AI and people are smarter together. We will look at the ways in which this combination of automation and critical thought is being used to rethink the value extracted from data.
For example, sentiment data is a major source of untapped value that can complement and augment traditional analysis of fundamental or technical data. Similarly, automated trading and trader augmentation tools can streamline time-consuming compliance, allowing for greater productivity and an increased focus on client services.
Financial services firms are also improving their compliance and risk management processes – with many putting AI to work to augment their current processes and better work within systems. And firms aren’t the only ones eyeing AI and machine learning: regulators are as well. Increased regulatory reach and complexity are motivating companies to anticipate potential roadblocks to using new technologies -- and are adjusting to avoid them.
Technology trends like these have the potential to disrupt and radically transform all industries. From investments in cloud computing to advances in machine learning, there are opportunities and lessons to be learned and applied across industries. We'll take a close look at the digitalization of the energy sector and growth of investment in sustainable technologies.
Despite efforts around diversity, women remain underrepresented in the technology sector. Bloomberg, in its role as a tech innovator, needs to tap into all potential talent and has seen that teams with members of diverse backgrounds perform better and produce more creative ideas. We see the implicit value in fostering a vocal and growing “Women in FinTech” community through events, networking and other initiatives. By encouraging collaboration and professional development, such groups inspire future leaders and further essential conversations about diversity and inclusion and offer ideas on ways to overcome outdated cultural norms.
For those looking to digitally disrupt and evolve their business, these innovations present a wealth of opportunity. I invite you to contact me regarding any of the topics raised, or to discuss how Bloomberg can further help you and your team.
Shawn Edwards, CTO, Bloomberg L.P.
