source: Bitcoin News
2016. May. 27. 21:00
Financial regulations are usually a way for the government to combat money laundering and terrorism funding in their jurisdiction. Thanks to the transparent nature of blockchain technology, Know-Your-Transaction protocols will become a lot easier to implement.
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Anti-money laundering (AML) and countering the financing of terrorism regulations are two common types of regulation in the financial world. These rules are designed to prevent criminal activity from happening, as well as identifying suspicious transactions as soon as they take place.
At the same time, it is important to note governments are not fighting these financial crimes alone, as they are aided by intermediaries. This forces financial institutions to implement their own AML and KYC guidelines to ward off criminal activity through their platforms. Bitcoin exchanges, for example, are all subject to these guidelines.
But these regulations are not enough to ensure no fraud or suspicious activity is taking place in the financial world. Governments and institutions are turning towards technological solutions, and the blockchain can become a valuable ally in this regard. With its transparent nature, the Bitcoin blockchain lends itself for analyzing transactions and tracking funds.
A recent post on Skry referred to “Know-Your-Transaction” (KYT) as a new procedure to the AML and CFT toolkit. Even though Bitcoin addresses are not linked to a user’s identity directly, it can be revealed through crawling the web for identifiers and building so-called lookup tables. To explain this a bit further: a lookup table would consist of patterns of activity associated with known suspicious cases.
The way KYT works is by taking a close look at all of the metadata associated with a Bitcoin transfer. Large amounts of funds changing hands would raise suspicion, especially if they always come from the same address. Skry did not make it clear what other types of information they want to collect during this process, though.
Solutions based on blockchain analysis will need to differentiate between legitimate and suspicious anomalies in the transaction patterns. Focusing on the volume per transaction, the frequency, or even the velocity alone is not enough to mark specific transfers as suspicious.While this may serve as statistical evidence, it will not always help in preventing future suspicious behavior.
Ultimately, preventing fraudulent activity from taking place is the end goal of financial regulation. Artificial Intelligence advances are making this process easier over time, as it can predict suspicious events in its current form. Integrating the Know-Your-Transaction factor into these measurements will add another layer of analytics to the table to make these solutions more robust.
Skry is one of the companies using Bitcoin technology to build predictive models for suspicious behavior, partially thanks to a Know-Your-Transaction implementation. While this is a very complicated process, the team has managed to establish a predictive risk score, which is used in the company’s Spectrum solution. Spectrum was created for the purpose of addressing transaction monitoring challenges for financial institutions in the Bitcoin world.
Establishing this predictive risk score requires constant tweaking, and should only be seen as a tool for decision-making, rather than being a factual decision itself. It is a tool for analysts to look into the background of new users, and determine whether or not their funds is coming in through legitimate sources.
Albeit governments and regulators may argue Bitcoin technology lacks two key components to assess financial risk the transparent nature of the blockchain negates that issue. This is because Skry feels the absence of identity and geography of users does not prevent law enforcement from fulfilling their investigations. However, it remains up to the individual companies in the Bitcoin world to conduct thorough background checks on their users.
Know-Your Transaction can be a powerful tool for law enforcement agencies when attempting to predict suspicious activity from taking place. Merging existing technologies with this new set of data will the challenge moving forward, as algorithms have to be optimized and implementing multiple data streams needs to be researched.
What are your thoughts on introducing Know-Your-Transaction in the world of financial analysis? Let us know in the comments below!
Source: Skry
Images courtesy of Skry, Shutterstock
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