Featurespace recognised as a leader in fraud prevention
It's been a busy week for Featurespace. Not only has it warned about rising types of fraud, but now it has been recognised by Gartner as a representative vendor.
Featurespace | Don Riddick, Chief Legal Officer
In this video interview, Don explains why he joined Featurespace and the industry challenges that our technology is solving: “When you combine great people with absolute brilliance and a desire to delight the customer, you have lightning in a bottle. It’s a rare and unique combination of characteristics inside of a business – and I wanted to be a part of that.”
Don previously served as VP of Corporate Legal at TSYS, prior to and following its acquisition by Global Payments. Prior to TSYS and Global Payments, he worked at IBM as an Advisory Project Manager, Consulting Sales Specialist and Contracts Executive Leader, leading legal negotiations for financial services, technology, and other customers.
“Don brings a powerful blend of expertise that encompasses financial services law, regulatory compliance, vendor segmentations and innovation, making him a vital addition to the Featurespace team,” said Dave Excell, founder of Featurespace. “His experience and legal counsel will be crucial to us and our expanding clientele.”
Featurespace | Adaptive Machine Learning for Enterprise Financial Crime
Globally, the financial services industry is undergoing a period of transformative change, and Asia Pacific is no exception. Criminals are constantly looking to find the institutions with the weakest links.
Join this exclusive webinar where Dave Excell, Featurespace’s Founder will share insights into why Machine Learning (ML) is the future of fighting financial crime.
Featurespace’s ML-enabled enterprise financial crime prevention platform runs inside some of the world’s largest banks, payment processors, acquirers and merchants, assisting financial crime professionals in keeping one step ahead of criminals while providing a profitable balance between customer protection and seamless experience.
– Why this is the right time for Adaptive Machine Learning for financial crime professionals – Adaptive Machine Learning versus rules and traditional Machine Learning
– Outsmarting risk – how unique models in financial crime detection is helping in understanding individual behaviors at speed and scale
– Real-life cases showcasing how Adaptive Machine Learning has transformed enterprise financial crime prevention
– How financial institutions can empower their own data science teams within an Open Modeling Environment
LDSS 2017 – Building a Real-time Banking Fraud Detection System – Dr Karthik Tadinada, Featurespace
If you enjoyed this talk join us and are interested in learning more about bank fraud detection and other data science applications, visit our website: https://cambridgespark.com/
Application Fraud in a Digital-First World: Overcoming the Challenges
Criminals are rapidly evolving their tactics to imitate genuine customer behavior and evade detection. In the world today, circumstances have forced a noticeable acceleration of digital transformation programs within many financial services organizations. The driver being the need to protect customers from criminals in a world that has become digital–first overnight.
Application fraud is an example of one of the fastest growing types of fraud. Aite Group found that credit card losses from Synthetic Identity fraud reached $968m in 2018 and projected this to reach $1.26 billion in 2020.
Julie Conroy, Research Director at Aite Group and Chip Kohlweiler, VP Security at Navy Federal Credit Union discuss the growing challenges of application fraud and offer advice on the best methods to detect new attacks and how to spot more sophisticated frauds, such as synthetic identities, while balancing the need to enable a positive customer experience.
In this session you will:
– Learn about best practices for keeping pace with identity fraudsters
– Have actionable takeaways on how to reduce customer friction
– Discover how the rapid shift to digital has increased the significance of addressing these fraud types