Speaker "Elizaveta Lebedeva" Details Back



How to succeed with machine learning against fraud


Applying data science to predict fraud becomes an industry standard. But machine learning in fraud has its own specifics compared to other domains: highly imbalanced data, different cost of false positives and false negatives, interaction of ML models with the whole fraud system, etc. In my talk, I will share what to do with such caveats: how to choose the correct metric for model training based on business problems, how to improve models with undersampling methods, what to do in case of real-time fraud detection systems. Also, I will talk about an important business part: how to measure impact of ML models and why sometimes you need to let fraudsters in.
Who is this presentation for?
Give an overview of how ML is different when applied in fraud domain.
Prerequisite knowledge:
Basic understanding of machine learning
What you'll learn?
After the session, participants will: learn about specifics of machine learning in fraud domain, know how to deal with them and how to build more powerful models, understand why ab-tests are needed for fraud systems and what can be done with the results.


Elizaveta is a Senior Data Scientist at Bolt, leading European mobility platform. Her current focus is on commerce topics where she applies models and algorithms to reduce fraud and optimise payments; she is involved in the whole data science pipeline starting from problem definition and model prototyping to live ab-tests and model operations. Being passionate about math and having degrees in finance and quantitative economics, Elizaveta transitioned to Data Science from Business Analytics, marking her path with numerous math competitions and hackathons. Elizaveta is active in Data Science community in Estonia (organising and speaking at conferences and meetups). She is passionate not only about Data Science, but also about engaging more people into the tech industry (organizing Tallinn Django Girls workshop, speaking at events and camps for school kids about career in IT).