Even a firm specializing in predicting crypto-blockchain crime can benefit from other advanced technologies, such as ‘distributed native graph databases’
How can financial crime be prevented with not only predictive blockchain monitoring, but also a visualization tool to boost efforts to preempt such activities?
TigerGraph, a firm offering a technology called “scalable graph database” for enterprises, has partnered with Merkle Science, a predictive blockchain monitoring and investigative platform, to achieve this.
Merkle Science, with TigerGraph, will enhance how the former helps its customers, which include government agencies and financial institutions, stay one step ahead of criminals. This will be done via the construction of a cryptocurrency network graph using TigerGraph, giving Merkle Science the ability to analyze over 2.5TB of data in real time, delving five to 10 hops into the data to connect relationships that they were not able to do prior. This ability is expected to unlock deeper, wider and operational analytics at scale.
Crypto becoming vulnerable
As cryptocurrency and blockchain increasingly reach the mainstream, the ecosystem that surrounds and supports it will also develop rapidly, exposing it to financial crime.
As such, risk management is key. The cryptocurrency network graph that Merkle Science has constructed using TigerGraph enables their customers to run queries identifying the percentage of funds sent or received from different types of actors (such as Darknet, Exchanges, Scams and Smart Contracts) from a specific location or address, which is hugely advantageous in detecting and analysing potential criminal activity.
Said Nirmal Aryath Koroth, co-founder and Chief Technology Officer, Merkle Science: “The ability to handle large quantities of data coupled with the query language GSQL have enabled us to build a graph data-warehouse which we use to help our users understand flows of funds and determine their risk exposure. TigerGraph has proven to be invaluable in helping our users to differentiate between good actors and bad ones.”
Merkle Science’s cryptocurrency network graph, which currently contains over 2.5TB of data and consists of 5bn vertices and 36bn edges, supports a complete extract, transfer and load (ETL) each day that takes under an hour, with near-instant streaming updates.
Continued Koroth: “The GSQL software program is also the most sophisticated query language I’ve seen so far and its flexibility allows us to implement complex graph algorithms which would otherwise be impossible or take far longer to implement on other incumbents.”
According to Joseph Lee, Vice President (Asia Pacific & Japan), TigerGraph said: “As we continue our expansion across APAC, we look forward to unleashing data’s true potential to help more (organizations) drive business growth, make better decisions and achieve tangible benefits.”