No doubt, blockchain adoption and deployment has been overly hyped, but the distributed ledger technology will ultimately prove useful – and even transformational – to many industries, including financial services.
In financial services, blockchain technologies will result in cost savings by reducing the need for reconciliation, improving audibility and reducing duplicate and inaccurate documentation. Almost 80 percent of financial services incumbents expect to adopt blockchain as part of an in-production system or process by 2020, PwC research shows. The list of potential uses for blockchain in financial services is vast, from settlements to smart contracts-computer programs running on the ledger-to share trading to simplifying cross border payments.
But to get the most from blockchain technologies, companies will first need to make sure their data is in order. In much the same way that artificial intelligence (AI) depends on good data to be useful, a proper blockchain implementation is also very dependent of quality data, perhaps even more so than AI.
Garbage In = Garbage Out
When it comes to data and blockchain, the old adage of garbage in equals garbage out looms particularly large for some of the more forward-thinking blockchain potential implementations. Lets take smart contracts as an example.
Loosely defined, smart contracts are pieces of code stored in a blockchain that automatically take certain actions when predefined conditions have been met. But if one is to trust that a machine, the blockchain, will settle the contract correctly, the data going into the blockchain has to be trustworthy. Thats where good data governance is critical. Whats more, the more complex the data going into the blockchain-such as terms and conditions of a derivative trade-the more important the governance of such data becomes.
After all, blockchains can only take responsibility for the accuracy and quality of data once it has been inputted into the blockchain.
You need to trust the data being pulled from organizations existing source systems is of good quality, writes Deloitte in a report, Blockchain & Cyber Risk. In that report, Prakash Santhana, a Deloitte managing director, is quoted as saying the biggest vulnerability in the blockchain framework will lie outside the framework in trusted oracles. A corrupted oracle could potentially cause a domino effect across the entire network.
If smart contracts can be trusted, it will also be because the data management processes around them (i.e. outside the blockchain) can be trusted. And it will be new and novel approaches to data governance that will ensure that such data is of suitable quality. When this happens, financial services firms will benefit by automating many processes, including paper intensive ones, reducing the time associated with settlement and clearing of transactions and improving accuracy and audit trails.
Good data governance is also critical to make sure that, if data goes to a public blockchain, certain things about the data are still kept private. In such cases, data governance processes enforce what can and what cannot go onto the blockchain.
Rethinking Data Governance
To get data in shape, however, companies of all types, and especially financial services, need to rethink how they approach data governance. After all, the concept of data governance itself isnt new. However to match the pace and quality expectations of newer technologies such as blockchain, some newer perspectives must be applied, such as:
–Data governance at the data level. To tap into opportunities associated with data automation, like blockchain capabilities, the metadata-the data about the data-should be stored with the data itself so that entities and regulators have a transparent view into where the data came from, when, how, and if it was changed. Historically, such metadata has not been stored with the data itself, if it had been stored at all. Thats because managing data lifecycle across a complex enterprise with varying data models and process flows has required data management flexibility that has not been possible with traditional database technologies. Newer database technologies, however, make it far easier to not only deal with such variability, but also make it easy for critical governance metadata to stay with the data.
–Data out of silos. In most companies, customer data, trade data and other data assets are stored in separate silos, often reflective of various lines of business or years of mergers and acquisitions. For this same reasons traditional governance has been a challenge – limitations of traditional database technology – so too has been legacy approaches to data integration. Again, this is where fundamentally different database technology makes a difference. By integrating and harmonizing such siloed data into a centralized and operational data hub – all the while maintaining governance at the data layer – organizations will finally be able to have a trusted operational view of their data assets across various states within the enterprise. Theyll also be faster at giving regulators a holistic view of data across any jurisdiction of operation.
–Data governance policies throughout. Companies need effective data governance policies, such as those that maintain access controls, metadata, data quality and security-in and outside the blockchain. Given that some data will be on public blockchains and other data will not, data governance policies will ensure that all data is handled consistently. This will be critical when regulators seek a holistic view of transactions.
Turning Regulation into Opportunity
Financial institutions are no stranger to regulatory oversight. However, the EUs recent $5 billion antitrust fine against Google may underscore a new regulatory intensity on technology and other powerhouse companies. Additionally, newer regulations for banks – regulations that are very data specific – also signal that regulators, at least in the European Union, are more serious about data governance, increased transparency, consumer privacy and investor and consumer protection. The EUs new MiFiD II regulation governing the securities markets and the General Data Protection Regulation, GDPR, governing consumer data, are forcing huge changes upon global companies that touch the EU, which includes many financial services firms.
For all companies to more easily meet regulatory requirements, now and in the future, they need to rethink some data fundamentals. This means that some of the old ways of handling data governance will not be applicable to todays challenges. Those who take a forward-thinking approach and implement data governance policies that are implemented inside of the DBMS at the first point of data integration will not only be better prepared to adjust to future regulations and market opportunities, but will also be better positioned to take advantage of new technologies, like blockchain, now and into the future.
Ken Krupa is Enterprise CTO at MarkLogic
