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In the last sixteen years, I have had the privilege to be part of several great companies. Especially in the last ten years, I have had the opportunity to develop Data Teams, which have helped accelerate the development of the organisations that I have worked for leading to the introduction of new global payment products. As the first Data Scientist at Adyen, I was responsible for combining my extensive business background, with the latest Data Science techniques, to help develop features that were implemented in products like RevenueAccelerate, RevenueProtect, Predictive Interchange and Acquiring.
By joining Dimebox (acquired by Verifone) as their Head of Data, I was responsible for Data Product Development including core-platform features, like Data Analytics, the Fraud Engine, and the Billing & Settlement Engine. Currently, I am the Director of Data Science & Analytics at DataBright, where I lead a team of Data Scientists, Data Engineers and Data Analysts, who help companies modernize their Analytical Stack and use Data Science to develop new products and services.
Having started my “real” business at the age of 15, a Youth Events Management company, I have never stopped creating and developing businesses. Including a Marketing & Promotions, two Domino’s Pizza franchises, an Online Conversion Optimization Service, and currently a Data Science & Analytics Consultancy firm.
Besides building businesses, I have also had the opportunity to pursue several university degrees including a Bachelor of Science degree. in Information, Multimedia and Management and a Masters of Science degree in Information Sciences, from the VU University in Amsterdam.
Finally, I like to share my knowledge of Data Science and Payments, by being a mentor at Backstage Capital, an advisor to Zazuu, a Remittance App, on my Medium and personal blog, and as a speaker.
Below is an overview of the topics I provide talks about:
The Algorithmization of FinTech (FinTech is interchangeable for Payments, Lending, International Money Transfers, Personal Finance, Insurance)
This keynote discusses how the emergence of Modern Analytics, Machine Learning, and AI is impacting the FinTech industry. Most companies are just finishing up their Digitization space, and are now being confronted with the Algorithmization phase, which takes the Data generated both internally and externally and uses Algorithms to feed new products and services. (This can be adapted to the sub-categories of FinTech, or can be broad by sharing examples of the whole industry)
The New Business Model of the FinTech Industry (Payments, Lending, International Money Transfers, Personal Finance, Insurance)
The competition in FinTech is enormous, which leads to the Commoditization of FinTech, everybody is selling the same product, in Payments, Lending, International Money Transfers, Personal Finance, Insurance, the companies that will survive are the ones who adapt to the new business model. It not just about getting the most customers, it is about giving them the most value and monetising that in the right way.
Become Data-Driven or Perish: Why your company needs a Data Strategy and not just more Data People
The explosion of Data is still extremely underutilised. According to Gartner’s Research only 69% of companies do not consider themselves Data-Driven, 66% of companies still use Excel for the majority of their BI. Companies who don’t make Data a core Strategic objective will be outperformed by companies who do.
The Cold Start Problem with Artificial Intelligence
AI is the buzzword of the week, last year it was Machine Learning, before that Data Science and before that Business Intelligence. The Buzzwords and the opportunity are correct, however most companies want to skip the steps before they can get to AI. In this keynote we explore why most companies are failing with AI at this moment and how they can overcome it.
If you are interested in having me speak at your event or conference, feel free to reach out to Madeline McQueen at email@example.com.