Bitcoin is currently trading at over $1250 and if you are someone who invested a grand in bitcoins back in 2011, your investments are potentially worth over $600K. The most valuable contribution of the bitcoin community is not in the financial returns itself, but in the introduction of blockchain technology.

Blockchain is a distributed database system that serves as an “open ledger” to record and manage transactions. Each record in the database is called a block and contains details like the transaction timestamp as well as a link to the previous block. This makes it impossible to alter information about the records retrospectively. Also, since the same transaction is recorded over multiple, distributed database systems, the technology is secure by design.

How Blockchains Change Fintech

At present, digital transactions take place with the help of tokens. This is a unique code generated by a third party (such as Visa or Mastercard, for example) and is shared with the token requestor (the retailer you are shopping from) and the account issuer (the customer’s bank). Tokens make online transactions more secure by concealing actual customer-identifying data. Since the token is generated by a third party which by itself does not have information regarding the transaction, there is no scope for any sort of data for a data scientist to play with.

This changes with blockchain technology. Here, it is theoretically possible to get a hold of every transaction that has ever happened and this provides data scientists with everything they need to analyze trends and patterns with online transactions.

To be fair to cryptocurrencies like bitcoins, they were designed on the exact opposite premise of providing a secure and confidential transaction mechanism. While that hasn’t changed, blockchains provide banks and financial institutions with the technology needed to mine more useful data from their customer transaction history. Beyond financial institutions, blockchain as a technology also has use-cases across several industries including healthcare and gaming where it is making possible for data scientists to dig through massive troves of data that were hitherto unavailable for mining.

Opportunities for Big Data Analytics

Recently, a consortium of 47 Japanese banks signed up with a company called Ripple to allow money transfers between bank accounts using blockchain. The main reason behind the move is to allow real-time transfers at a significantly low cost. One of the reasons traditional real-time transfers were expensive was because of the potential risk factors. Double-spending (a form of transaction failure where the same security token gets used twice) is a real problem with real-time transfers. With blockchains, that risk is largely avoided. Big data analytics makes it possible to identify patterns with consumer spending and identify risky transactions a lot quicker than they can be done with current day technology. This reduces the cost with real-time transactions.

Outside of banking too, the main drive for blockchain adoption has been security. Across healthcare, retail and public administration, establishments have started using blockchain to handle data to prevent hacking and data leaks. In healthcare, a technology like blockchain can make sure that multiple “signatures” are sought at every level of data access. This can prevent a repeat of the 2015 attack that led to the theft of over 100 million patient records.

But businesses expect to see other benefits from this adoption as well. And like with healthcare, in gambling too, blockchain analytics tools are viewed as handy tools to define gambling patterns and identify patterns of frauds that casinos can use to dig out loopholes.

Possibilities in real-time analytics

Up until now, real-time fraud detection has only been a pipe dream and banking institutions have always relied on using technologies to identify fraudulent transactions retrospectively. Since blockchain has a database record for every transaction, it provides a way for institutions to check for patterns in real-time, if need be. Companies like Chainalysis and Coinalytics (acquired by Bloq) use this real-time intelligence to make decisions about pseudonymous data.

But all of these possibilities also raise questions about privacy and this in direct contradiction to the reason why blockchain and bitcoins became popular in the first place. Several industry experts have expressed concern that a technology that can provide a record of every transaction can be exploited for everything “from customer profiling to less benign reasons”.

But to look at this from another perspective, blockchains improve transparency in data analytics. Unlike previous algorithms, the blockchain technology rejects any input that it can’t verify and is deemed suspicious. As a result, analysts in retail industries only deal with data that is completely transparent. In other words, the customer behavior patterns that blockchain systems identify are likely to be a lot more accurate than it is today.

The future

Although blockchain offers great promise for data science, the truth is that we do not have too many blockchain-based technology systems deployed at industrial scale in the first place. As a result, the real dangers and threats with blockchain may not be apparent for at least a few more years until blockchain becomes more mainstream.

For data scientists, this means two things. One, it is still going to be a while before the treasure trove of data that blockchain promises to offer is made available to them across various industries. But more importantly though, as the flaws in the technology become more visible, blockchain is at threat of being regulated or being replaced with traditional systems. That is something that data scientists may not want.

Like this article? Subscribe to our weekly newsletter to never miss out!

Image: Shiaron James, CC BY 2.0

Previous post

The Business Implications of Machine Learning

Next post

How to do time series prediction using RNNs, TensorFlow and Cloud ML Engine