What’s Next? Banks Explore Use of Blockchain Tools For Reference Data Management; ISIN, CUSIP, SEDOL..
(WSJ) 20 September–Some big banks are applying a bitcoin-style system to another technology pain point, the reference data identification tags attached to things they trade. Reference data includes securities identification numbers, including ubiquitous ISIN (International Securities Identification Number), CUSIP, SEDOL and independent constructs such as Bloomberg FIGI.
Banks including Citigroup Inc., Credit Suisse Group AG and HSBC Holdings PLC have used technology developed by startup Axoni to test a new way to share trade-reference data. They are doing so using a so-called blockchain network, the firms are set to announce Tuesday.
Such a network uses an encrypted distributed ledger that parties involved can see to track information, rather than maintaining their own, individual records. This is akin to the kind of network that marks all bitcoin ownership and trades.
The new application to reference data is the most recent of a series of projects in which big banks hope to take costs out of their complex, expensive, and often troubled back-office systems. Banks are working on tests involving international money transfers, derivatives, syndicated loans and agricultural commodities.
Created by firms such as Axoni, Digital Asset, and Symbiont, these networks differ from the universal public blockchain used by bitcoin. Instead, the networks are privately controlled by the banks involved.
ISIN Network is the leading U.S. entrepreneurial firm that specializes in assisting Issuers of securities (bonds, equities and structured products) secure reference data and securities identification numbers for use across the private and public markets. To learn more, please click here
Some early bitcoin developers have criticized these projects, saying they undermine bitcoin’s original promise of displacing intermediaries like banks. Banks, though, have focused on private ledgers given the confidential nature of much trade data.
And banks are struggling to find ways to grow revenues at a time of record-low interest rates, reducing trading volatility, and muted capital markets. So cost-cutting through new technology is seen as one of the best hopes for growing profits.
The reference-data prototype was used for corporate bonds. Via the network, the banks shared information such as the name of the issuer and how to calculate interest payments. R3, a bank consortium focused on blockchain applications, is working with the Securities Industry and Financial Markets Association to set standards and monitor further testing and potential implementation. Investment manager AllianceBernstein LP is also involved in the test.
In these networks, participants work off a single database, akin to a shared Google document, to mitigate expenses and the opportunity for errors or miscommunication when each bank maintains its own records.
Blockchains haven’t yet been put to live use in bank trading. But banks have bet millions of dollars through investments in startups that it can work, and have declared success in early tests such as with credit-default swaps.
Reference data is costly not only to constantly monitor and update, but banks also pay outside firms such as Bloomberg LP and Thomson Reuters Corp. to access data they collectively produce. If banks could automatically share the data among themselves, as well as update it, they could potentially reduce their reliance on those vendors. The banks could also maintain a measure of control over data that is now readily accessible to third-parties and rivals.
Though seemingly basic, reference data can also be rife with errors, especially in more complex trades, studies have found. A 2012 study by Capgemini Consulting said that faulty reference data is “one of the major contributors to…operational risk,” and makes up as much as 70% of the data used in trades. It said banks were spending $2 billion globally that year to integrate different data sources.
In one example, executives at Opus Global, a bank technology provider, earlier this year found that some Dow Jones Industrial Average components were marked differently in major databases. There were seven differences in name, spelling, abbreviations or punctuation for Goldman Sachs Group Inc., and six for DuPont Co.
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