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오류신고를 진행 하실 데이터 정보를 담은 표입니다. 제목(Main) Synthetic Financial Datasets For Fraud Detection 제목(Sub) 저자 Edgar Lopez-Rojas; 제공처 국가연구데이터플랫폼 리포지터리 국가연구데이터플랫폼
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2021
해외
공개
CC-BY-SA
English
Synthetic Financial Datasets For Fraud Detection
Synthetic Financial Datasets For Fraud Detection Edgar Lopez-Rojas(EdgarLopezPhD);
Context
There is a lack of public available datasets on financial services and specially in the emerging mobile money transactions domain. Financial datasets are important to many researchers and in particular to us performing research in the domain of fraud detection. Part of the problem is the intrinsically private nature of financial transactions, that leads to no publicly available datasets.
We present a synthetic dataset generated using the simulator called PaySim as an approach to such a problem. PaySim uses aggregated data from the private dataset to generate a synthetic dataset that resembles the normal operation of transactions and injects malicious behaviour to later evaluate the performance of fraud detection methods.
Content
PaySim simulates mobile money transactions based on a sample of real transactions extracted from one month of financial logs from a mobile money service implemented in an African country. The original logs were provided by a multinational company, who is the provider of the mobile financial service which is currently running in more than 14 countries all around the world.
This synthetic dataset is scaled down 1/4 of the original dataset and it is created just for Kaggle.
There is a lack of public available datasets on financial services and specially in the emerging mobile money transactions domain. Financial datasets are important to many researchers and in particular to us performing research in the domain of fraud detection. Part of the problem is the intrinsically private nature of financial transactions, that leads to no publicly available datasets.
We present a synthetic dataset generated using the simulator called PaySim as an approach to such a problem. PaySim uses aggregated data from the private dataset to generate a synthetic dataset that resembles the normal operation of transactions and injects malicious behaviour to later evaluate the performance of fraud detection methods.
Content
PaySim simulates mobile money transactions based on a sample of real transactions extracted from one month of financial logs from a mobile money service implemented in an African country. The original logs were provided by a multinational company, who is the provider of the mobile financial service which is currently running in more than 14 countries all around the world.
This synthetic dataset is scaled down 1/4 of the original dataset and it is created just for Kaggle.
- #finance
- #KAGGLE
- #crime
- #KAGGLE
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