At the height of the GFC, banks, governments, regulators, investors and corporations were all struggling to assess the amount of credit risk that Lehman Brothers represented to global capital markets and financial systems. One of the key lessons learnt from the Lehman collapse was the need to take a very different approach to identifying, understanding and managing counterparty risk – a lesson which fintech startups would be well-advised to heed, but one which should also present new opportunities.
In Lehman’s case, the credit risk was not confined to the investment bank’s ability to meet its immediate and direct financial obligations. It extended to transactions, deals and businesses where Lehman and its myriad of subsidiaries in multiple jurisdictions provided a range of financial services – from liquidity support to asset management; from brokerage to clearing and settlement; from commodities trading to securities lending. The contagion risk represented by Lehman was therefore not just the value of debt and other obligations it issued in its own name, but also the exposures represented by the extensive network of transactions where Lehman was a counterparty – such as acting as guarantor, underwriter, credit insurer, collateral provider or reference entity.
Before the GFC
Counterparty risk was seen purely as a form of bilateral risk. It related to single transactions or exposures. It was mainly limited to hedging and derivative positions. It was confined to banks, brokers and OTC market participants. In particular, the use of credit default swaps (CDS) to insure against the risk of an obiligor (borrower or bond issuer) failing to meet its obligations in full and on time.
The problem is that there is no limit to the amount of credit “protection” policies that can be written against a single default, much like the value of stock futures and options contracts being written in the derivatives markets can outstrip the value of the underlying equities. This results in what is euphemistically called market “overhang”, where the total face value of derivative instruments trading in the market far exceeds the value of the underlying securities.
As a consequence of the GFC, global markets and regulators undertook a delicate process of “compression”, to unwind the outstanding CDS positions back to their core underlying obligations, thereby averting a further credit squeeze as liquidity is released back into the market.
Counterparty risk is now multi-dimensional. Exposures are complex and inter-related. It can apply to any credit-related obligation (loans, stored value cards, trade finance, supply chains etc.). It is not just a problem for banks, brokers and intermediaries. Corporate treasurers and CFOs are having to develop counterparty risk policies and procedures (e.g., managing individual bank lines of credit or reconciling supplier/customer trading terms).
It has also drawn attention to other factors for determining counterparty credit risk, beyond the nature and amount of the financial exposure, including:
- Bank counterparty risk – borrowers and depositors both need to be reassured that their banks can continue to operate if there is any sort of credit event or market disruption. (During the GFC, some customers distributed their deposits among several banks – to diversify their bank risk, and to bring individual deposits within the scope of government-backed deposit guarantees)
- Shareholder risk – companies like to diversify their share registry, by having a broad investor base; but, if stock markets are volatile, some shareholders are more likely to sell off their shares (e.g., overseas investors and retail investors) which impacts the market cap value when share prices fall
- Concentration risk – in the past, concentration risk was mostly viewed from a portfolio perspective, and with reference to single name or sector exposures. Now, concentration risk has to be managed across a combination of attributes (geographic, industry, supply chain etc.)
Implications for Counterparty Risk Management
Since the GFC, market participants need to have better access to more appropriate data, and the ability to interrogate and interpret the data, for “hidden” or indirect exposures. For example, if your company is exporting to, say Greece, and you are relying on your customers’ local banks to provide credit guarantees, how confidant are you that the overseas bank will be able to step in if your client defaults on the payment?
Counterparty data is not always configured to easily uncover potential or actual risks, because the data is held in silos (by transactions, products, clients etc.) and not organized holistically (e.g., a single view of a customer by accounts, products and transactions, and their related parties such as subsidiaries, parent companies or even their banks).
Business transformation projects designed to improve processes and reduce risk tend to be led by IT or Change Management teams, where data is often an afterthought. Even where there is a focus on data management, the data governance is not rigorous and lacks structure, standards, stewardship and QA.
Typical vendor solutions for managing counterparty risk tend to be disproportionately expensive or take an “all or nothing” approach (i.e., enterprise solutions that favour a one-size-fits-all solution). Opportunities to secure incremental improvements are overlooked in favour of “big bang” outcomes.
Finally, solutions may already exist in-house, but it requires better deployment of available data and systems to realize the benefits (e.g., by getting the CRM to “talk to” the loan portfolio).
Opportunities for Fintech
The key lesson for fintech in managing counterparty risk is that more data, and more transparent data, should make it easier to identify potential problems. Since many fintech startups are taking advantage of better access to, and improved availability of, customer and transactional data to develop their risk-calculation algorithms, this should help them flag issues such as possible credit events before they arise.
Fintech startups are less hamstrung by legacy systems (e.g., some banks still run COBOL on their core systems), and can develop more flexible solutions that are better suited to the way customers interact with their banks. As an example, the proportion of customers who only transact via mobile banking is rapidly growing, which places different demands on banking infrastructure. More customers are expected to conduct all their other financial business (insurance, investing, financial planning, wealth management, superannuation) via mobile solutions that give them a consolidated view of their finances within a single point of access.
However, while all the additional “big data” coming from e-commerce, mobile banking, payment apps and digital wallets represents a valuable resource, if not used wisely, it’s just another data lake that is hard to fathom. The transactional and customer data still needs to be structured, tagged and identified so that it can be interpreted and analysed effectively.
The role of Legal Entity Identifiers in Counterparty Risk
In the case of Lehman Brothers, the challenge in working out which subsidiary was responsible for a specific debt in a particular jurisdiction was mainly due to the lack of formal identification of each legal entity that was party to a transaction. Simply knowing the counterparty was “Lehman” was not precise or accurate enough.
As a result of the GFC, financial markets and regulators agreed on the need for a standard system of unique identifiers for each and every market participant, regardless of their market roles. Hence the assignment of Legal Entity Identifiers (LEI) to all entities that engage in financial transactions, especially cross-border.
To date, nearly 400,000 LEIs have been issued globally by the national and regional Local Operating Units (LOU – for Australia, this is APIR). There is still a long way to go to assign LEIs to every legal entity that conducts any sort of financial transaction, because the use of LEIs has not yet been universally mandated, and is only a requirement for certain financial reporting purposes (for example, in Australia, in theory the identifier would be extended to all self-managed superannuation funds because they buy and sell securities, and they are subject to regulation and reporting requirements by the ATO).
The irony is that while LEIs are not yet universal, financial institutions are having to conduct more intensive and more frequent KYC, AML and CTF checks – something that would no doubt be a lot easier and a lot cheaper by reference to a standard counterparty identifier such as the LEI. Hopefully, an enterprising fintech startup is on the case.
Next week: Sharing the love – tips from #startup founders