The science of IFRS 9 and the art of Basel

(First of two parts)
IFRS 9 is an International Financial Reporting Standard (IFRS) promulgated by the International Accounting Standards Board on July 24, 2014. It addresses accounting for financial instruments and features three main topics: classification and measurement of financial instruments; impairment of financial assets; and hedge accounting. It will become effective in 2018 and replaces International Accounting Standards (IAS) 39 Financial Instruments: Recognition and Measurement and all previous versions of IFRS 9. In this article, IFRS 9 is referred to as a “science” because of its systematically organized body of information and measurements on specific topics.
Basel III (or the Third Basel Accord or Basel Standards) is a global, voluntary regulatory capital and liquidity framework agreed upon by the members of the Basel Committee on Banking Supervision (BCBS) in 2010-11. It was scheduled to be introduced from 2013 until 2015; however, the implementation has been extended to March 31, 2019. Another round of changes was agreed upon in 2016 and 2017 (informally referred to as Basel IV) and the BCBS is proposing a nine-year implementation timetable, with a “phase-in” period to commence in 2022 and full implementation to be expected by 2027. Basel III was developed in response to the deficiencies in financial regulation that came to light after the financial crisis of 2007-08. Basel III is intended to strengthen banks’ capital requirements, liquidity, maturity profile, and leverage. It also introduced macroprudential elements and capital buffers designed to improve the banking sector’s ability to absorb shocks from financial and economic stress; and reduce spillover effects from the financial sector to the real economy. Basel is an “art” form in the context of the need to perform skillful planning and creative visualization in fully comprehending its dynamic processes and uncertainties.
It is now mid-2018 and financial institutions have been coming to terms with the implementation of IFRS 9 and the ongoing wave of regulatory changes resulting from the Basel reforms.
To say that banks underwent a difficult IFRS 9 adoption journey is an understatement. There were real systems and data challenges in producing the reports and calculations, coupled with organizational anxiety about dealing with technical assumptions and the unintended interference of model approximations of investment strategies and credit quality. There is now a patchwork of models and estimation approaches developed for different purposes, from provisioning to portfolio evaluation, capital planning and pricing. This has led to the view that a key game-changing impact of IFRS 9 in the medium-term is the integration of the risk, finance and reporting functions into strategic and corporate planning.
For both provisioning and capital planning purposes, most banks have already built their overall modeling and calculation frameworks, introduced process changes and reviewed controls. Some have started the process of automating the calculation aspects of expected credit losses (ECL) after the major step in prior years of cleaning, collecting and aggregating data from both central and federated sources, including unstructured and proxy data that semi-spontaneously arose at the end-user level.
Others are in the process of enhancing their models and estimation approaches, after incorporating iterative and regular feedback from those tasked with governance over these calculations and underlying assumptions while thoroughly documenting the technical specifications and assumptions. Some have also started the process of reviewing their risk-finance data infrastructure in preparation for a revamp of their integrated stress testing initiatives and as part of their efforts to calculate notionally the capital usage (to cover both economic capital and “resilience capital buffer” for both the ICAAP and RRP requirements) at transaction and portfolio levels, while strengthening liquidity and stable funding defenses at the enterprise level.
Leaders of financial institutions need to ensure that these changes are well-thought out and smoothly implemented. Generally, there is a need for increased headcount and capability building, particularly on the current requirements for advanced data analytics skills, analytical ability, model-risk knowledge and testing capabilities, and communication and business decision support capabilities.
There is also a growing need for talent who can handle computational and data science functions, and digital implementation. Digital is expected to surge in the next eight to 15 months, especially as banks consider digitizing their middle and back offices and the risk function, embedding the balance between risk taking and risk discipline at the business level through dynamic pricing and capital allocation, and enabling risk management and decision support through automation, machine learning and artificial intelligence (AI). Some examples include the use of apps for risk-based pricing for front office people, chatbots for queries, visualization and dashboard designs to analyze and evaluate customer segments, and spatial techniques for geography-dependent strategies and products.
Concurrently, banks need to develop relevant strategic options such as cost management and capital structure optimization (after raising of equity and funding capital), to better manage business mix adjustments, customer profitability and strategic responses to disruptive forces. At the industry level, the major business responses related to IFRS 9 and Basel regulations cover mainly strategically and dynamically evaluating asset portfolios and more actively managing customer profitability, with varying degrees of exiting either strategies or lines of business to rationalizing legal entities (in the case of conglomerates). The goal is to be more lean and agile for growth, and not necessarily in response to carve-outs or dismantling of capital drags and traps.
These observations should be understood at the enterprise level and related to the wider economic context, especially with the signaling purpose now being served jointly by the overlay mechanism of IFRS and the counter-cyclical capital buffer under the macro-prudential regulations of Basel. In succeeding articles in this series, we will examine these signaling mechanisms, which require more art than math (or more mark-to-view rather than mark-to-model) as these should be designed to evoke or provoke an organizational response rather than just to be prescient about economic readings. In navigating these complex changes and uncertainty, banks may consider using an adept risk-adjusted performance measurement (RAPM) tool. This was previously discussed in this column on March 9, 2015.
To help stabilize the post-2018 implementation process of IFRS 9 and prepare for the upcoming round of supervision, the Board and Senior Management may want to revisit and raise relevant questions. A good start would be the document issued by the Global Public Policy Committee of the world’s six largest accounting networks, which listed the questions to ask for those charged with governance over IFRS 9.
In the next part of this article, we will continue the discussion of the impact of IFRS 9 and Basel on business models, risk models and stress testing, and parametric thinking.
This article is for general information only and is not a substitute for professional advice where the facts and circumstances warrant. The views and opinion expressed above are those of the authors and do not necessarily represent the views of SGV & Co.
 
Christian G. Lauron is a Partner of SGV & Co.