VINOD SUKUMARAN – “Agile Documentation: Balancing Speed and Knowledge Retention” For many project managers, it’s not a big stretch to understand how the Waterfall phases are turned into sprints—the same work is accomplished; it’s just organized in a different way. However, the removal of most documentation is a harder pill to swallow as it underlines a completely different way of working. It requires loosening the reins of control, embracing the unknown, and empowering the delivery team to make decisions on the spot.
Additional added October 4, 2019
What Is Agile Methodology: A Primer On Moving Fast
Larry Tabb – As a result, brokers are re-investing in their infrastructure and trying to leverage new technologies and data science to make their trading algorithms better, more efficient and more effective.
Monica Summerville – While financial institutions have invested billions of dollars, pounds and euros on implementing once-state-of-the-art systems, demands from both regulators and clients for ever-greater transparency into data and its analysis can mean tenfold increases – or more – in the amount of data generated. In addition, relying on “start of the day” or “end of day” data often is no longer acceptable. Instead, more functions are requiring near- or fully real-time access to data and analytics, which compounds the data architecture challenge.
Chris Skinner – Citi has backed 4 blockchain, 3 capital markets, and 3 payments & settlement startups since 2017. Generally, these investments fit into the banks’ larger strategy of building open banking infrastructure. In March, Citi announced plans to build a “digital consumer payments business for institutions,” and there are rumors Citi may launch a Banking-as-a-Service platform.
Kiran Vajapey – Today, the terms artificial intelligence (AI) and machine learning (ML) are often used interchangeably. While the terms are related, they mean different things. We map out how they all relate to one another, so your team can find the best candidates, best approaches and best frameworks as you embark upon your AI journey.
Campbell Peters – While buy-side firms have built out their technology and analytics teams considerably, most firms still outsource execution algos from their brokers. This is especially true for fundamental firms, as quantitative firms are more likely to develop some of their algos in-house. These quant firms have been the most willing to adopt emerging technologies, such as machine learning and AI, since they have the resources to develop and test the functionality in-house if needed.