Where is IFRS 9 taking the cost of funding of banks?

Mahmoud Fatouh

IFRS 9 versus IAS 39

In 2018, IFRS 9 came into effect, replacing IAS 39. IFRS 9 has important implications especially for banks, as they mostly hold financial assets. IAS 39 is based on the incurred-loss model, which allows recognition of credit losses (in the form of provisions) only when there is objective evidence of impairment, dividing loans into performing and impaired loans (Figure 1). IFRS 9 introduces the more forward-looking expected loss model, under which provisions are equal to the expected credit losses. As illustrated in Figure 1, IFRS 9 classifies loans into three stages: Stage 1 loans (performing loans), Stage 2 loans (underperforming loans) and Stage 3 loans (nonperforming loans).

Figure 1: IAS 39 versus IFRS 9 loan stages

How IFRS 9 affects the level of equity capital

As Figure 2 demonstrates, IFRS 9 increases the level of credit loss provisions, reducing after-tax profit and retained earnings (the main component of equity capital resources) of a bank. Hence, to maintain pre-IFRS 9 levels of leverage and capital ratios, banks have to hold higher level of equity capital for a given asset portfolio under IFRS 9, compared to what they would have held under IAS 39.

Figure 2: Impact on P&L account and the balance sheet (IAS 39 versus IFRS 9)

We borrow the impacts of IFRS 9 on the level of equity capital from previous analyses that quantified the impact of IFRS 9 on capital ratios, such as the European Banking Authority’s (EBA) report on impact assessment of IFRS 9 (July 2017), and Mazars’s quantified impacts of IFRS 9 (March 2018). Table A presents some details about the impact of IFRS 9 on capital ratios of European banks.

Table A: Impact of IFRS 9 on capital ratios of European banks(1)

Notes:

(1) The impact of IFRS 9 varies significantly across banks. Hence, we include further details (the maximum and minimum impacts) to provide a better picture of that impact.
(2) Report on Results from the Second EBA Impact Assessment of IFRS 9.
(3) Quantified Impacts of IFRS 9: Initial Findings.
(4) The estimates for Santander UK parent (Banco Santander SA) are used.

How IFRS 9 affects the cost of funding

As shown above, banks would hold more equity capital under IFRS 9, compared to IAS 39. In a standard Modigliani-Miller environment, the higher level of equity capital should not affect the overall cost of capital. The increase in equity capital reduces bankruptcy risk. This lowers the cost of equity and debt sufficiently to offset the effects of the larger share of equity in the capital structure, leaving the weighted average cost of capital (WACC) unchanged. This proposition would hold in efficient and integrated capital markets. However, researchers have observed a number of frictions (inefficiencies) in actual capital markets. The low-risk anomaly in share markets is one of these frictions. This anomaly refers to the empirical observation that risk differentials between shares do not fully translate into return differentials. In other words, historical returns and realised cost of equity are relatively higher for shares with low betas and relatively lower for shares with high betas. Researchers generally attribute the low-risk anomaly to a combination of irrational demand for risker (high beta) shares and limited arbitrage. The anomaly has been observed in each of the G7 countries, and across 23 developed economies. The presence of the low-risk anomaly for banks’ equity means that the above mentioned increase in equity capital would increase the cost of funding (WACC) of banks. This is because the cost of equity would not fall sufficiently to compensate for the higher share of equity in the capital structure.

Does the low-risk anomaly exist for banks’ equity?

Our sample includes 75 publicly traded banks from six European countries. It includes 10 UK banks, 8 German banks, 8 French banks, 9 Spanish banks, 17 Italian banks, and 23 Swiss banks. We use daily on banks’ share price, market indices, and the yield of 10-year government bonds (as the risk-free rate) as well as quarterly balance sheet data between 1997 and 2017. Table B displays descriptive statistics of return data.

Table B: Summary statistics of return data (1997–2017)

Source: Refinitiv Eikon.

To check whether the low-risk anomaly exists for banks’ equity, we adopt a modified version of CAPM (capital asset pricing model), following Baker and Wurgler (2015). Specifically, we add an additional term (alpha) to the security market line equation used to estimate the cost of equity in the model. This alpha term would be a decreasing function of equity beta, and the slope of this function would represent the magnitude of the low-risk anomaly. This is because the anomaly implies that low-beta shares outperform their CAPM benchmark, whereas high-beta shares under-perform it.

We estimate the magnitude of the anomaly by plotting alphas and betas of three size-based portfolios for each country. The three portfolios are large banks (30% largest banks), small banks (the smallest 30%), and medium banks (the remaining 40%). We estimate alpha and beta for each portfolio by regressing excess returns on the portfolio on market excess returns (alpha is the intercept and beta is the slope in that regression).

To ensure robustness, we repeat this estimation using different cuts (portfolios) across banks in each country. The results are consistent across different estimations, and indicate that low-risk anomaly exists for banks’ equity in the six countries in our sample, except France.

Table C shows our baseline estimates of the magnitude of the low-risk anomaly in the six countries. The strongest anomaly of 15 basis points appears for German banks’ equity. This means that for every 1 percentage point increase in the share of equity in the capital structure, the cost of funding for German banks can rise by about 0.15 percentage points. A similar change in the capital structure would increase the cost of capital by around 0.11 percentage points for UK and Spanish banks, 0.03 percentage points for Italian banks, and 0.02 percentage points for Swiss banks.

Table C: Estimated annual magnitude of the low-risk anomaly

Impact of IFRS 9 on cost of funding of European Banks

Finally, we estimate the impact of IFRS 9 on the cost of funding for banks by multiplying the magnitude of the low-risk anomaly for each country (Table C) by the average impacts of IFRS 9 on the levels of equity capital extracted from the EBA’s report 9 and Mazars’s study (Table A). As Table D shows, IFRS 9 slightly affects the cost of funding of banks in the six countries. For instance, IFRS 9 may increase the cost of funding of UK banks by 5 basis points. This represents less than 1% of the real cost of equity for banks in the UK estimated by King (2009) at 6.6%.

Table D: Estimated average impact of IFRS 9 the cost of funding of banks (in basis points)

It is important here to note that we should interpret these estimates as the ‘day 1’ impact of IFRS 9 on the cost of funding. Their validity as estimates for the longer-term impact of IFRS 9 relies on two main factors. First, the impact of IFRS 9 on the level of equity capital may differ across different stages of the credit cycle. Hence, our estimate could overestimate the impact of IFRS 9 on the cost of funding or underestimate it. Moreover, our analysis does not account for the potential impact of the increase in asset quality transparency under IFRS 9 on the level of equity capital, when the market fully adapts to IFRS 9. If the increase in transparency raised the implicit maximum level of leverage, our estimates would have overstated the impact of IFRS 9 on the cost of funding of banks.


Mahmoud Fatouh works in the Bank’s Prudential Policy Division.

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