In what seems like the ‘wild frontier’ of blockchain and cryptocurrencies that we are currently experiencing, there is almost only one thing that is certain; if someone writes an article about the price of the latest cryptocurrency then the article will likely to be out of date before it is even published! As I write this, most crypto currencies are going through one of their periodic bear-like downturns and this one looks bigger than those that have happened in the last 12 months. Who knows what will happen next? However, I hope that if some of the air does come out of the cryptocurrency bubble then 2018 can become the year where interest turns to the less hyped side of blockchain and more specifically towards distributed ledger technology (DLT).

The difference between the two is not so much a ‘difference’ but more of a super set. Cryptocurrencies are usually an instance of a blockchain, and blockchains themselves are an instance of DLTs. This is interesting in financial services (FS) because of the flaw (for the FS industry) of blockchains; namely that if blockchains work by replicating the same database across all participants in the network, then most financial institutions explicitly want the exact opposite! For example if Bank A trades with Bank B, then the last thing they want is details of the trade being accessible to Bank C. Even if the details are encrypted, financial institutions will be reluctant due to the encryption potentially being broken in the future.

So if pure blockchains (such as ethereum) are not the answer, then what is? The answer is private or ‘permissioned’ DLTs. These are either blockchains that try and resolve the shortcomings of the pure blockchains (such as Digital Asset Platform or Quorum), or not blockchains at all (e.g. Corda). These platforms are much more interesting for financial services since they offer the same disruptive potential as blockchain whilst operating within the constraints required by capital markets.

Unfortunately, these platforms are a) not for the faint hearted, and b) bleeding edge. For example many of the platforms use niche languages that will restrict your resource pool, and some have not yet demonstrated how they operate in a continuous delivery environment. As a result of this we need to ensure that the ‘problem’ we are seeking to solve warrants such an approach. As an aside, this is the fli side of the criticism often levelled at DLT and artificial intelligence (AI), that these are solutions looking for problems. So how do we triage a problem to see if it is worth the effort or risk? The answer is to examine how much of the advantages gained from potentially implementing a DLT are utilised. As a reminder these advantage arising from DLTs are:

Trust Boundary Extension; does your use case need trust between parties who would not normally trust each other? Does an agreement or consensus need to be reached?

Disintermediation; is there a middleman that is not adding value for money? Is a new business process being prohibited due to the lack of an authority figure?

Proof of provenance; are you seeking to prove that the supply chain that an asset has been on (or is going to be on) is valid and true?

Transfer of value; does your use case require instant transfer of value?

Embedded business logic; are you looking to add business logic into the transaction?

Efficiency; does your use case replace low value manual processes? Are you looking to remove reconciliations between parties with data in common? Do you need to remove exception queues?

The more questions that are answered ‘yes’, the more a DLT could be right choice for your use case. As you can see, something like a cryptocurrency meets many of these; which explains the focus on these right now. As a general rule, if you are meeting three or four of the categories, then it would be worth it. Alternatively if a use case can only achieve one of the benefits using a DLT, then this could be a good reason e.g. the funds that a client is using have not been involved in any money laundering activity.

The bottom line is that whilst it is still definitely early days for production use cases of DLTs, if the use case fits the current constraints well enough, and the benefits match up, then now is the definitely the time to be progressing with DLT!