What is a Complexitocracy?
Don’t bother looking it up in a dictionary… it’s not there. But it should be. If it were, the definition would be something like, “The governance or control of the global financial system by an elite of quantitative modellers”.
Complexitocracies in bank regulation stem from the notion that the safety and stability of the global financial system is associated with the capacity of banks’ capital to absorb extreme losses. To transform that notion into regulatory policy, a bank needs two things: (1) a method of estimating the largest likely loss a bank can be exposed to when operating in the most severely threatening conditions; and (2) the amount of capital it has available capable of absorbing such a loss. The theory is that the safety of the global banking system is assured if (1) is plausible, and (2) is greater than (1).
Modelling Statistical Probabilities
The banking sector concluded that estimating a largest likely loss – the so-called tail events aka ‘black swans’ – with an acceptable degree of risk sensitivity requires the modelling of statistical probabilities. Thus, the control over the regulatory capital framework’s agenda underwent a migratory process from accountants to mathematicians.
The first step occurred in 1988 with the Basel Committee’s first capital accord that heralded the arrival of the new regulatory metric the ‘Risk Weighted Asset’ or ‘RWA’. This was the metaphorical marching orders given to accountants to vacate the regulatory arena… Basel wanted to tame the risk beast on its own.
The RWA’s beginnings were innocuous. The 1988 accord required banks to organise their risk assets into five buckets with a fixed percentage applied to each bucket to determine their RWAs. Banks then had to ensure that a minimum amount of protective capital was set aside equal to 8% of their RWAs. What could be simpler?
What regulators didn’t know was the RWA’s nativity occurred when the banking sector was about to enter an era of unprecedented complexification. Market forces and the need for balance sheet rationalisation were obliging banks to progressively displace the traditional and relatively simple on-balance-sheet depositor/borrower dynamic with the more complex off-balance-sheet issuer/investor dynamic. This breathed life into the emerging derivative transaction that eventually escalated into a proliferation of increasingly complex risk intermediation products that, in turn, became the bedrock of equally complex trading structures. The transformation of the global financial operating landscape, from simple and benign to complex and treacherous was underway.
A New Type of Banker
This was the era of a new type of banker… the quantitative modeller. While accountants and auditors retreated into the background and focused their attention on reporting the past, quantitative modellers focused on projecting the performance of complex products and trading portfolios into the future.
The simple 1988 formulation of the RWA could no longer cut the mustard in the face of the inexorable complexification of the banking sector. If banking regulation were to remain relevant, the RWA needed to adapt. Banks robustly lobbied for an enhanced RWA by pitching their internal models as its benchmark. The result was Basel II which was the formal acceptance of quantitative modelling as the regulators’ preferred means of calculating RWAs.
The effect was dramatic. Regulators hired mathematicians in response to the revolutionary forces of complexification. Mathematical notation became a dominant language of regulatory capital adequacy policy. Accountants retreated even further into the background as audited financial statements became increasingly dislocated from reality through a refusal to contemplate how a bank’s risk position may be affecting its financial condition.
The complexitocracy was complete.
The RWA vs. Accounting Measures
We can only speculate how things would have been if, back in 1988, the Basel Committee had challenged the accountants to develop accounting measures for risk rather than going it alone with their RWA.
Accountants have the advantage of a ready-made authoritative source of controlled and audited financial data — the general ledger and its sub-ledgers — where all contractual obligations and the payments and receipts that emanate from them are registered. Accountants are skilled in categorizing and manipulating transactions and aggregating them to produce accounting measures such as profit, equity, net interest income, unit cost, return on investment and many more. Accounting measures provide a common language for the interpretation of financial information and ensure that decisions and actions affecting the business are safe. In short, their role is to make unobservable financial abstractions observable.
Taming the Monster Baby
The regulators have created their monster baby and are struggling to live with it. Maybe the accountants can help tame it. What is needed is the definition of accounting measures for risk that leverage the same accounting infrastructure, proven data sources and data aggregation paths that culminate in financial statements to also produce comprehensive risk analytics and risk-adjusted financial statements. The definition of such risk-based accounting measures is our mission at SERRAQ. We call it ‘Risk Accounting’.
The simple RWA, once easily understood by the many, has evolved into a complexitocracy intelligible to an elite few. It is time to restore simplicity to regulatory policy with something intelligible to the many.
About Peter Hughes
Peter is Chairman of the Risk Accounting Standards Board at SERRAQ. He is also a visiting fellow and advisory board member of the Durham University Business School’s Centre for Banking, Institutions & Development (CBID). He was formerly a banker with JPMorgan Chase.