Blockchain Intelligence brings together blockchain analytics, data sharing and artificial intelligence
Information is the input, intelligence is the output
BlockchaIntelligence Forum brings together professionals whose activities are impacted by the blockchain technology
Information costs money, intelligence makes money
Blockchain Intelligence Forum
CALLS TO ACTION
What do we do?
What are our aims?
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01
Facilitate the development of a community of blockchain intelligence professionals
adhering to high professional standards and recognized good international practices; -
02
Promote blockchain intelligence awareness
by providing members with up-to-date information on the latest developments and trends in blockchain analysis & intelligence and methods of improving professional standards, policies, procedures and international regulations; -
03
Facilitate open discussion
on best practice in combating financial crime by providing an effective network for members to share ideas; -
04
Reduce illicit activity in the EU region
by enabling members to be better equipped to fight it.
Blockchain Intelligence
It all started in 2009..
Blockchain Intelligence tools & products have been developed since the launch of the Bitcoin blockchain. The first tools allowed to analyze blockchain data were the “Block(chain) Explorers”, in order to organize and present raw blockchain data, which helped retail investors look up their own crypto-assets transactions.
Blockchain analytics tools appeared later in 2015, combining raw blockchain data with a proprietary database of known addresses to link on-chain activity to real-world entities. These tools allow address classification, providing investigation tools, monitoring transactions and risk analysis in a “blacklist-based” model.
Blockchain Intelligence goes beyond the traditional “blacklist-based” approach of blockchain analytics, and dynamically identifies risks, opportunities and threats. This is similar to the evolution of spam detection, anti-virus, and fraud prevention, which evolved from ‘blacklist-based’ risk models, to dynamic assessment models that are effective to support decision making.