Impact of AI & Machine Learning on Industry II
- TYPE: Track START DATE: Wednesday, September 18, 2019 START TIME: 14:00 LOCATION: maX 2
Date: Wednesday, September 18, 2019 Time: 14:00-15:00
Devil's in the Details: AI, Bad Guys, & Messy Data
Alex Detmering, Basis Technology
All the information that is needed to find and stop bad actors from entering our financial system already exists and is available to you today; it’s just buried in terabits of messy, unstructured data all over the internet. For those performing investigations and evaluating risk, this needle in a stack of needles problem is huge and growing: Unstructured data already dominates the web (growing exponentially year over year), and the traditional technology these departments use cannot...
Scoring Models, Fraud Detection, Customer Churn - will AI replace us? NO, but...
Eduard Singer, BeeInnTech
One of the main questions people ask about AI is about substitution: will come the time AI will undertake tasks humans do? It's very important to understand the difference between applied and generalized AI. Today and in the next 15-20 years we are talking about applied AI, means only special kind of tasks will be fulfilled by AI, but also when in maybe 20 years generalized AI will come (a machine will "think" like a human) there will be enough creative and "other" tasks for humans so that...
Date: Wednesday, September 18, 2019 Time: 15:00-16:00
Improve Business Results by Optimizing Your Decisions. Machine Learning 101
Murat Vurucu, Latentine GmbH
A.I. might be one of the newest hypes but it’s really helping you with the oldest problem: making a decision. Learning from our past projects we developed an introduction to machine learning that enables the audience to shift their focus from technology to their own decisions. By the end, listeners can point out where in their own realm A.I. is an option and where it is just buzz. Key takeaways: 1. Be able to better identify the false promises in today's overwhelming A.I...
Of Black Holes and Swans: AI for Context-Aware Quantitative Financial Risk Management
Dr. Stephan Werner, RISKLIO
A highly relevant use case of AI in finance is to provision new risk-related insights from data that enable improved decision making by man or machine. A recent example of how to use advanced analytics to foster insight is the creation of the first picture of a black hole from radio signal based on Bayesian updating. Similar approaches help financial market participants with managing the risk of low-probability / high-cost events, colloquially known as black swans. This will be highlighted...