Using graph technology to achieve cryptocurrency success

Dan McGary, senior sales executive for mid-market enterprise, East at Neo4j, discusses how graph technology can effectively lend itself towards cryptocurrency operations

There are two things that you really need to know about cryptocurrency if you’re a bank or a high-net-worth individual looking to store wealth in this relatively new instrument. Firstly, Bitcoin is a vast and complex network of connections. That complexity means any institution looking to work with cryptocurrency needs to understand its workings and its premise better. Firms also need to have a clear grasp of what a typical cryptocurrency transaction looks like compared to an unusual one to head off fraud in any interaction for a client.

Secondly, decentralised finance — the push to replace traditional finance approaches and structures using blockchain and cryptocurrencies — is gaining greater traction and mindshare. Now in 2022, individuals and corporations can lend, borrow, swap, margin trade, and even create a mini hedge fund on blockchain. The permissionless and trustless features of blockchain are becoming more attractive to the market.

Those that grasp the potential for decentralised finance to change our financial systems for the better draw parallels to knowing the full potential of the Internet in 1973.

There is a risk attached to cryptocurrency. Enabling users and businesses to harness the blockchain effectively and safely, while making the currency manageable from a regulatory point of view is a difficult task. So, caution abounds. Crypto exchanges and trading platforms know the risks. More conventional financial services players seeing the rise in interest in the approach also recognise the potential ‘gotchas’ in these new forms of currency. New entrants into retail and business banking are also highly cautious.

All parties agree that if trust can be established in the crypto value chain, the rewards could be significant.

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Modelling the blockchain in graph form

A US-based neobank, for example, wants to offer ways to bank using cryptocurrency to its three million customers.

The challenger bank is one the first of many customer centric financial services firms working at scale with the nascent cryptocurrency market. It won’t be the last. The reality is that digital asset owners need to meet the challenge to avoid competitive disadvantage or exclusion from this post-pandemic, digitised economy.

Fortunately, since its inception and before this bank started thinking about offering cryptocurrency-based services, it decided to base the data model for its core banking engine on graph technology. As a result, it says its cryptocurrency debut after six years of careful planning has been made easier. This is due to working with data in a connected way — something graph technology offers natively.

Managing crypto transactions

Despite the way it’s structured at the code level, the blockchain is still just a transaction. Alice has 50 Bitcoin on an output locked by her, either as a reward from mining a new block or because of another transaction that produced an output locked by her. Now, Alice wants to send 25 Bitcoin to Bob. To do that, she creates a transaction which uses the output locked by her as input and produces two outputs: one sending the 25 Bitcoin to Bob with the other 25 Bitcoin as change. The unlocked 50 Bitcoin output is considered ‘spent’, but the new outputs are ‘unspent’, so they can be used in further transactions. All that is very simple to encode into a graph database, with its built-in ability to handle nodes and the relationships between them. After all, it’s what developers do in the context of other graph database use cases — take data in one format (here, blockchain data) and convert it into another format (a graph database).

For example, nodes can easily be connected with an ‘Unlocked By’ relationship with a different node representing the transaction. Such interactions can be easily captured by a graph query language, such as Cypher. It’s also simple and intuitive to represent key crypto structures like Blocks, Transactions, and Addresses in a new graph database. Once you have imported a blockchain into a graph database, you can also perform analysis. For instance, you can follow a Bitcoin path to see if two different addresses are connected.

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Graph tech is helping fight crypto fraud

Organisations are leveraging graph technology to help them monitor illegal use of decentralised finance. PwC Germany has developed BETA, the Blockchain Explorer and Transaction Analyser. BETA supports its crypto-asset service by protecting firms from financial crime risks, while assuring that compliance and regulatory requirements are fulfilled.

One of the key advantages of BETA is the feature of explainable risk reporting. With over 300,000 transactions a day on the Bitcoin blockchain, and more than a million transactions a day on its sister cryptocurrency Ethereum, incoherent reporting poses enormous challenges. By being able to link local data of a crypto asset service provider, such as order history, KYC records, IP session logs, and other PII data, BETA integrates existing AML (anti-money laundering) scoring providers to create uniform, transparent, transaction-risk scoring levels.

The positive experiences of challenger financial institutions, PwC Germany, and other crypto-graph users show the huge potential for graph databases in crypto-finance. Graphs can encode blockchain in ways that make it safer, more transparent, and more monetisable.

Whether you’re a brand wanting to offer Bitcoin as a payment mechanism or a fintech looking to enter the cryptocurrency market, now is a great time to investigate how you can do so safely, efficiently and with the ability to scale using graph technology.

Written by Dan McGary, senior sales executive for mid-market enterprise, East at Neo4j

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