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Predicting Fraud with Smart Machine Learning
Manage episode 445127079 series 3401658
As fraud becomes more sophisticated, businesses are turning to big data and advanced machine learning models to solve their fraud and identity challenges.
We’ll explore predictive analysis, how machine learning models adapt to new data, the importance of customization for different industries and how privacy is kept at the forefront.
Join our LexisNexis® Risk Solutions experts Olivier Everts, Data Science Manager and Anton Klippmark, Senior Manager, Market Planning as they discuss the power of predictive analytics in fraud detection.
DISCLAIMER: The information provided in this podcast is for informational purposes only and is not intended to and shall not be used as legal advice. The views and opinions expressed in this episode are solely those of the speaker/s and do not necessarily reflect the views or positions of LexisNexis Risk Solutions. LexisNexis Risk Solutions does not warrant that the information provided in this podcast is accurate or error-free.
42 episodes
Manage episode 445127079 series 3401658
As fraud becomes more sophisticated, businesses are turning to big data and advanced machine learning models to solve their fraud and identity challenges.
We’ll explore predictive analysis, how machine learning models adapt to new data, the importance of customization for different industries and how privacy is kept at the forefront.
Join our LexisNexis® Risk Solutions experts Olivier Everts, Data Science Manager and Anton Klippmark, Senior Manager, Market Planning as they discuss the power of predictive analytics in fraud detection.
DISCLAIMER: The information provided in this podcast is for informational purposes only and is not intended to and shall not be used as legal advice. The views and opinions expressed in this episode are solely those of the speaker/s and do not necessarily reflect the views or positions of LexisNexis Risk Solutions. LexisNexis Risk Solutions does not warrant that the information provided in this podcast is accurate or error-free.
42 episodes
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