On 2nd August, Elliptic, the blockchain analytics group that helps financial institutions and cryptocurrency companies meet regulatory compliance across the group released the Elliptic Data Set. As per the official Press Release, Elliptic targets to identify the digital asset transactions that are not compliant with the anti-money laundering laws.
The transactional data set comprises of 200,000 Bitcoin (BTC) transactions and value over $6 billion. Elliptic research has labeled the transactions made by criminal actors and this labeling will be used to develop and test predictive methods for identification of transactions associated with criminal acts. As per Elliptic, the data set is the largest set of labeled transaction data for any cryptocurrency that has been made available to the public.
The 203,769 bitcoin transactions and payment flows in the Elliptic data set have been represented as time-series graph. While 21% of the transactions have been labeled licit, only 2% have been found to be illicit. Rest of the transactions are under analysis and have been labeled as “Unknown”. The transactions labeled as illicit are associated with sanction violation, ransomware, funding terrorist activities or money laundering.
Elliptic, Massachusetts Institute of Technology (MIT) and tech giant IBM have partnered to make use of machine learning techniques to analyze the 200,000 bitcoin transactions in an effort to detect illicit bitcoin transactions. Once into production, the deep learning-based product could reduce criminal activities and compliance costs.
The analysis of the data set has been done using techniques like Logistic Regression, Random Forest, Multilayer Perceptrons, and Graph Convolutional Networks (GCN). Out of these machine learning techniques, Graph Convolution Networks (GCN) is the only one that is still a young class.
Mark Weber, the Co-author of the research paper drafted by Elliptic scientists and a researcher with MIT-IBM Watson team states that it is an early experiment with Graph convolutional networks but they are immensely powerful to identify the relational information especially when the datasets are so large and complex.
Co-founder of Elliptic, Dr. Tom Robinson told media that this effort will help the financial institutions and crypto exchanges in quick identification of illicit transactions so that they stay 100% complaint with anti-money laundering acts. As per Dr. Robinson, the pilot has been run for bitcoin and will be extended to other cryptocurrencies in the future.
Early May 2019, the Elliptic partnered with Binance to ramp up its compliance and regulatory ground. Binance plans to use the compliance support offered by Elliptic for its expansion plans in new jurisdictions. According to Samuel Lin, the Chief compliance officer of Binance, the partnership with Elliptic is a strategic move to combat money laundering.
The exchange has just partnered with blockchain analytics startup Elliptic to boost its compliance and security capabilities, Elliptic announced Thursday. The new partnership – the third relating to compliance in the last two months – will help Binance combat money laundering as it grows into new jurisdictions, the exchange’s chief compliance officer Samuel Lim said.
Elliptic’s compliance solutions have been a big success as they claim to have monitored money laundering risks that could cost organizations more than several trillion dollars.
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