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Blockchain Intelligence Group Launches World’s First Chinese-Language Crypto Investigations Training

Blockchain Intelligence Group, a global cryptocurrency compliance and risk intelligence company, owned by BIGG Digital Assets Inc. (“BIGG” or the “Company”)  is pleased to launch the world’s first Certified Cryptocurrency Investigator (CCI) training course in Chinese, available now.

Blockchain Intelligence Group’s CCI course in English is used by the top names in global law enforcement and Fortune 500 banks to train staff. The launch in Chinese opens access to a global market of regulators, law enforcement and financial professionals seeking advanced training in cryptocurrency.

“The launch of Chinese-language training is a milestone in Blockchain Intelligence Group’s growth,” said Lance Morginn, president of Blockchain Intelligence Group. “Certified crypto investigator training in Chinese is an industry first that offers superior training to Chinese speakers around the world to help them thwart crime involving crypto.”

Read : Global Fintech Interview with Mark Fidelman, Chief Executive Officer at SmartBlocks

Cryptocurrency adoption is growing globally, with more than 19 million Chinese cryptocurrency holders despite the government’s ban. CCI course is an industry-applicable, tool-agnostic training that equips government, law enforcement agencies, banks and more to investigate financial crime involving cryptocurrency. CCI provides a deep dive on topics such as anti-money laundering, cryptocurrency analysis, obfuscation techniques with crypto and uses on the Dark Web.

Now available in Chinese language, companies and individuals who pass the CCI also get a trial access to Blockchain Intelligence Group’s QLUE™, the best-in-class blockchain data visualization and investigation tool. QLUE™ analyzes crypto data at its most granular level, transaction-to-transaction for better evidence collection. Built-in case file management, NFT support and multi-chain graphing aids investigations.

The CCI course includes five on-demand modules:

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