Revolutionizing a bank: Introducing service mesh and a secure container platform
February 26, 2020
For years, Janna Brummel and Robin van Zijll have been told no to any external hosting. They've always lost time by not being able to use open source and cloud native products without adjustments. All because they work for a bank. Things are changing now: Janna and Robin are proving it's possible to run APIs in a secure container platform in the public cloud.
Dont beat the market; beat the bots: Adversarial networks in finance
February 24, 2020
Automated investing has brought an immense amount of stability to the market, but it has also brought predictability. Garrett Lander and Al Kari examine if an adversarial network can game the behavior of automated investors by learning the patterns in market activity to which they are most vulnerable.
AI for financial time series forecasting and dynamic assets portfolio optimization
February 21, 2020
Real business usage of most advanced methods for financial time series forecasting (based on winning methods from M4 competition) and assets portfolio optimization (based on Monte Carlo Tree Search with neural networks - Alpha Zero approach). Complete investments platform with the AI workflow and real time integration with the brokers. Real usage demo.
Assumed risk versus actual risk: The new world of behavior-based risk modeling
February 16, 2020
Viridiana Lourdes explains how banks and financial enterprises can adopt and integrate actual risk models with existing systems to enhance the performance and operational efficiency of the financial crimes organization. Join in to learn how actual risk models can reduce segmentation noise, utilize unlabeled transactional data, and spot unusual behavior more effectively.
How disruptive tech is reshaping the financial services industry
February 13, 2020
The financial services industry is increasingly using disruptive technologyincluding AI and machine learning, edge computing, blockchain, mobile and mixed reality, virtual assistants, and quantum computing to name a fewto enhance the customer experience and personalize their interactions with customers. Swatee Singh outlines how the same is true at American Express.
Machine learning in data quality management
February 12, 2020
Jennifer Yang discusses a use case that demonstrates how to use machine learning techniques in the data quality management space in the financial industry. You'll discover the results of applying various machine learning techniques in the four most commonly defined data validation categories and learn approaches to operationalize the machine learning data quality management solution.
Your easy move to serverless computing and radically simplified data processing
February 7, 2020
Most analytic flows can benefit from serverless, starting with simple cases to and moving to complex data preparations for AI frameworks like TensorFlow. To address the challenge of how to easily integrate serverless without major disruptions to your system, Gil Vernik explores the push to the cloud experience, which dramatically simplifies serverless for big data processing frameworks.
Executive Briefing: Rigorous application of domain insights in AI projects
February 5, 2020
Domain insights are crucial for successful AI/ML initiatives. This talk discusses three areas of concerns: clarification of business context, awareness of nuances of data sources, and navigating organizational structure.
Democratizing fintech: Enabling financial services for all through open source banking
January 30, 2020
A convergence of trends and technologies is enabling the democratization of financial servicesbig data, AI, the cloud, smartphone ubiquity, national IDs, blockchain, and open banking. However, there's one missing factoropen source bankingthat will scale the movement and unlock financial services for all, from the unbanked in India to the underbanked in America.
Finding your North Star
January 10, 2020
The Financial Times hit its target of 1 million paying subscribers a year ahead of schedule. Cait O'Riordan discusses the North Star metric the company uses to drive subscriber growth, detailing how it's embedded across the organization and within the engineering and product teams she's responsible for.
Mutant tests too: The SQL
January 8, 2020
Elliot West and Jay Green share approaches for applying software engineering best practices to SQL-based data applications to improve maintainability and data quality. Using open source tools, Elliot and Jay show how to build effective test suites for Apache Hive code bases and offer an overview of Mutant Swarm, a tool to identify weaknesses in tests and to measure SQL code coverage.
Accelerate innovation in the enterprise with distributed ML and DL (sponsored by BlueData)
January 4, 2020
Nanda Vijaydev shares practical examples ofand lessons learned fromML/DL use cases in financial services, healthcare, and other industries. You'll learn how to quickly deploy containerized multinode environments for TensorFlow and other ML/DL tools in a multitenant architecture either on-premises, in the cloud, or in a hybrid environment.
Transforming a financial services data infrastructure for the modern era by building a PCI DSS-compliant data platform from the ground up on AWS
January 4, 2020
Eoin O'Flanagan and Darragh McConville explain how NewDay built a high-performance contemporary data processing platform from the ground up on AWS. Join in to explore the company's journey from a traditional legacy onsite data estate to an entirely cloud-based PCI DSS-compliant platform.
Deploying deep learning models on GPU-enabled Kubernetes clusters
January 1, 2020
Interested in deep learning models and how to deploy them on Kubernetes at production scale? Not sure if you need to use GPUs or CPUs? Mathew Salvaris and Fidan Boylu Uz help you out by providing a step-by-step guide to creating a pretrained deep learning model, packaging it in a Docker container, and deploying as a web service on a Kubernetes cluster.
Keynote: Blockchain Balance: Exploring the Evolving Roles of Permissioned, Public and Hybrid Networks in the Financial Market
December 27, 2019
As enterprise blockchain moves deeper into the finance market, most organizations are looking at where, when and how to deploy the technology. In evaluating the role of blockchain, its important to k …
Cloud Native Business: Optimizing Your Business Value Stream Using Container Platforms
December 26, 2019
Your software development pipeline is one of the most important drivers to your success. You know you want to move faster and invest in innovation to bring value to your customers, but legacy patterns …
Dilated neural networks for time series forecasting
December 25, 2019
Dilated neural networks are a class of recently developed neural networks that achieve promising results in time series forecasting. Chenhui Hu discusses representative network architectures of dilated neural networks and demonstrates their advantages in terms of training efficiency and forecast accuracy by applying them to solve sales forecasting and financial time series forecasting problems.
How to protect big data in a containerized environment
December 23, 2019
Recent headline-grabbing data breaches demonstrate that protecting data is essential for every enterprise. The best-of-breed approach for big data is HDFS configured with Transparent Data Encryption (TDE). But TDE is difficult to configure and manageparticularly when run in Docker containers. Thomas Phelan discusses these challenges and explains how to overcome them.
Interpretable and resilient AI for financial services
December 23, 2019
Financial services are increasingly deploying AI services for a wide range of applications, such as identifying fraud and financial crimes. Such deployment requires models to be interpretable, explainable, and resilient to adversarial attacksregulatory requirements prohibit black-box machine learning models. Jari Koister shares tools and infrastructure has developed to support these needs.
Managing data science in the enterprise
December 22, 2019
The honeymoon era of data science is ending, and accountability is coming. Successful data science leaders must deliver measurable impact on an increasing share of an enterprise's KPIs. Joshua Poduska, Kimberly Shenk, and Mac Steele explain how leading organizations take a holistic approach to people, process, and technology to build a sustainable competitive advantage.