Blockchain is a digital and decentralized public ledger with a system that records transactions across several computers linked to a peer-to-peer network. It was originally developed for cryptocurrency assets like Bitcoin, Dogecoin, Ethereum, etc., In recent years there are several new use cases have emerged in financial services. (See: Blockchain for Secure Healthcare Records, How Banks & Financial Institutions can use Blockchain Technology, Blockchain use cases)
As blockchain’s use cases go beyond cryptocurrency, including for government applications, healthcare, identity management, art, and IPR, the database of all blockchain transactions grow even more bigger, richer, and more valuable for banks – if they can use this data via data analytics and use these insights to build better services. The benefit of blockchain is its inherent transparency. The blockchain’s decentralized, open network allows banks to collect data from blockchain transactions.
The Rise of Data Analytics
Aside from all the aforementioned areas, blockchain also huge potential in analytics. Modern businesses have been benefiting from data analytics for several years now. Currently, the big problem with any data analytics is getting quality data from different sources and correlating them. There is the issue of whether there is enough of the right data.
This is where blockchain technology helps. Data recorded in a blockchain is irrefutable and can be easily cross verified from any node in the network. Having access to this large network that provides high quality data in a vast number of datasets is invaluable.
A good potential application will be blockchain analytics – to understand customers of cryptocurrency customers & traders. Bank’s asset & wealth management business and customer banking’s marketing organization can use these valuable analytics for future marketing campaigns and for managing cryptocurrency as an asset class in wealth management. This system can be used to forecast price movements for cryptocurrencies.
Today there are more than 100 digital assets including Bitcoin, Ethereum, ERC-20 tokens, and other crypto coins, representing over $200 billion worth of transactions per month.
Other use cases include risk analysis on crypto transactions: uncovering activities related to money laundering, terrorist fundraising, fraud, and other financial crimes. Blockchain analytics can de-anonymize funds flow by actively collecting millions of data points every week, and then implementing machine learning to its huge data pool to track flows to legitimate entities and also criminal activities.
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