During July we attended the Federal Reserve Bank of New York, for the formation and launch of the Financial Stability Board’s (FSB) Legal Entity Identifier (LEI) Private Sector Preparatory Group.
The group was created by the FSB in response to a call from the leaders of the G20 countries to proceed with development of a, “unique identification system for parties to financial transactions.” [pdf]
Since then, over 100 institutions from around the world have been working together on the various aspects of the project: Governance & Legal; Operations; and Ownership & Relationship data.
For our own part, we are advising both the Governance & Legal and Operations workstreams.
Why is there a need for a Legal Entity Identifier? The LEI has been described as a “Linchpin for financial data”,
“The financial industry runs on information and data. Although financial data are made up of innumerable complex and idiosyncratic components, a fundamental building block for analysis is reference data about companies, organizations, and firms (henceforth referred to collectively as entities).
Reference data might include a number of things, but an essential component is a systematic structure or code that uniquely identifies entities and their legal relationships with parent companies and subsidiaries capable of tracking changes in these relationships over time and quickly incorporating information on newly created entities.
A universal, standard legal entity identifier (LEI) would likely provide a “public good” in that it could permit cheaper and more efficient analysis for all interested parties. It could also facilitate analysis that is currently incredibly difficult due to the plethora of proprietary entity identifiers.
An LEI could also be a critical component for measuring and monitoring systemic risk. The financial crisis demonstrated the extreme complexity of interrelationships and dependencies that exist between parties, counterparties, issuers, guarantees, and guarantors and how strains can rapidly spread through the financial network when one or more of the nodes within these horizontal or vertical relationships come under pressure.
In principle, a system of unique identification of every entity would help to map these types of (inter)relationships in the financial system and allow a better understanding of the key linkages in advance of a crisis…” [pdf]
The various aspects of “systemic risk” in today’s data dependent finance sector, and the need to create clarity on its “extreme complexity of interrelationships and dependencies” is something that we have discussed here on a few occasions.
To repeat a key point made in, “What explains the IT problems in banks?”,
“Globally, the fundamental problem facing banks, businesses, governments and people is that there are no standards for flows of data.”
Over time, this is one of the critical issues that will have to be solved by finance if the LEI is to be successful.
Why do we think that standards for data flow are so important in finance? As stated previously,
“Over 90% of money exists in electronic format as data. Banks and other financial institutions are basically data refineries. They ‘pump’ this data around the globe, through people, systems and hardware, trying to make a profit on various transactions.
However, when compared to the refineries of the Oil & Gas world, the banks have little clarity about how everything is put together to make the business work. By extension therefore, no-one knows precisely how the financial system works.”
Events like the 2010 ‘flash crash’ and the major IT problems at RBS last summer, demonstrate how economically damaging a lack of clarity on data flow can be.
Joris Luyendijk of The Guardian has published a great series of interviews that he conducted with people who work in diverse parts of the finance industry.
While not stating it explicitly, what many of his articles reveal is just how risky a lack of clarity in finance can be. Here are some examples:
A former Head of Structured Credit discusses how some of his departments ‘exotic’ financial products ‘turned toxic’ in the 2008 crash. Luckily, the parent company of the bank had sufficient resources to keep it going,
“Those were scary days…
In the years before, we’d know in our heads to within a few thousand what profit or loss we’d made for the day, then press F9 and have it confirmed by our systems. When the crisis hit we would press F9 and get a number that was totally unexpected…
Our models were based on what we saw as normal. Now we saw numbers behave in ways barely conceived possible…”
A Risk and Compliance Consultant spends most of the day in front of a computer screen studying spreadsheets,
“…I look at losses due to system errors or human errors, which is quite a task given the myriad systems.
You’d expect banks to have these super systems where you simply press a button and out comes what you need. In reality I have to do a lot of ‘manual reconstruction’…I’d have to go myself into several systems, lift out bits here and there, then assemble a picture. Given the complexity and vastness of computer systems at banks, it can’t be too difficult for ‘a rogue-trader’ to hide trades…”
The goal of a Senior Financial Services Authority Regulator is to understand the risks that banks’ internal management are taking,
“…Ultimately, as supervisors, we rely upon self-declaration, upon what is presented to us by a bank’s internal management. But often they don’t know what’s going on, because banks today are so vast and hugely complex.
The real threat is not a bank’s management hiding things from us: it’s the management not knowing themselves what the risks are, either because nobody realises it or because some people are keeping it from their bosses…”
An IT Consultant and Developer is astonished at the ‘level of disorganisation in banking’,
“…Even in one bank different divisions use different systems, many of which have been developed in a patchwork fashion; one addition on top of another…
If I ask for the very simplest sets of data, often they can’t get it together. And if they do, you go through these conversations like: ‘Well, thank you for the data but there are duplicates in it.’ And they go: ‘Well, what do we do about it?’ And I’m like: ‘Well, you take ‘m out!’…”
‘Nobody at a bank can have a complete overview any more’, says an External Auditor,
“…the sheer size of the data streams. You lose perspective. I lose perspective…
We check by sampling. This is worth emphasising. Operations of large firms have become so huge and complex, and none more so than those in this sector. A client may process transactions worth a trillion pounds a day…”
The inter-connectivity and the inter-relationships of financial institutions that make up the financial network are, by their nature, multi-dimensional and complex. As one regulator says,
“…Take the payment system that you and I rely on in our everyday lives, the plumbing of the financial system if you will. This has become so intricate and interconnected that contagion can spread rapidly. The payments system is like a giant spider’s web with the central bank at the centre with rings of banks going out. If several of these banks are suffering a crisis at the same time, you begin to worry about whether the day-to-day running of the economy is under threat…”
The LEI initiative has brought together governments, banks, regulators and private sector experts, in order to lay the first building block of a new way of working.
And that building block is not just the foundation stone for a new common system, but also the Rosetta Stone which allows each financial institution to be able to translate its own internal reference codes into a standard that every financial institution and regulator can understand.
Being able to accurately map the “giant spiders web” that is today’s global financial network will only be possible with the global adoption of the LEI as a common language with common data.
As Andrew Haldane, Executive Director of Financial Stability at the Bank of England, said in his speech “Towards a Common Language”, where he spells out the benefits of LEI,
“If data are not standardised, mapping complex networks is a high-dimension jigsaw puzzle. Understanding the underlying picture is taxing and time-consuming. Capturing the same data in a standardised way means that plotting the network becomes a much simpler game of join-the-dots.”