IRB – From the outside

ECB Targeted Review of Internal Models

The European Central Bank recently (April 2021) released a report documenting what had been identified in a “Targeted Review of Internal Models”(TRIM). The TRIM Report has lots of interesting information for subject matter experts working on risk models.

It also has one item of broader interest for anyone interested in understanding what it means for an Australian Authorised Deposit Taking Institution (ADI) to be “Unquestionably Strong” per the recommendation handed down by the Australian Financial System Inquiry in 2014 and progressively being enshrined in capital regulation by the Australian Prudential Regulation Authority (APRA).

The Report disclosed that the TRIM has resulted in 253 supervisory decisions that are expected to result in a 12% increase in the aggregate RWAs of the models covered by the review. European banks may not be especially interested in the capital adequacy of their Australian peers but international peer comparisons have become one of the core lens through which Australian capital adequacy is assessed as a result of the FSI recommendation.

There are various ways in which the Unquestionably Strong benchmark is interpreted but one is the requirement that the Australian ADIs maintain a CET1 ratio that lies in the top quartile of international peer banks. A chart showing how Australian ADIs compare to their international peer group is a regular feature of the capital adequacy data they disclose. The changes being implemented by the ECB in response to the TRIM are likely (all other things being equal) to make the Australian ADIs look even better in relative terms in the future.

More detail …

The ECB report documents work that was initiated in 2016 covering 200 on-site model investigations (credit, market and counterparty credit risk) across 65 Significant Institutions (SI) supervised by ECB under what is known as the Single Supervisory Mechanism and extends to 129 pages. I must confess I have only read the Executive Summary (7 pages) thus far but I think students of the dark art of bank capital adequacy will find some useful nuggets of information.

Firstly, the Report confirms that there has been, as suspected, areas in which the outputs of the Internal Models used by these SI varied due to inconsistent interpretations of the BCBS and ECB guidance on how the models should be used to generate consistent and comparable risk measures. This was not however simply due to evil banks seeking to game the system. The ECB identified a variety of areas in which their requirements were not well specified or where national authorities had pursued inconsistent interpretations of the BCBS/ECB requirements. So one of the key outcomes of the TRIM is enhanced guidance from the ECB which it believes will reduce the instances of variation in RWA due to differences in interpretation of what is required.

Secondly the ECB also identified instances in which the models were likely to be unreliable due to a lack of data. As you would expect, this was an issue for Low Default Portfolios in general and Loss Given Default models in particular. As a result, the ECB is applying “limitations” on some models to ensure that the outputs are sufficient to cover the risk of the relevant portfolios.

Thirdly the Report disclosed that the TRIM has resulted in 253 supervisory decisions that are expected to result in a 12% increase in the aggregate RWAs of the models covered by the review.

As a follow-up to the TRIM investigations, 253 supervisory decisions have been issued or are in the process of being issued. Out of this total, 74% contain at least one limitation and 30% contain an approval of a material model change. It is estimated that the aggregated impact of TRIM limitations and model changes approved as part of TRIM investigations will lead to a 12% increase in the aggregated RWA covered by the models assessed in the respective TRIM investigations. This corresponds to an overall absolute increase in RWA of about €275 billion as a consequence of TRIM and to a median impact of -51 basis points and an average impact of -71 basis points on the CET1 ratios of the in-scope institutions.
European Central Bank, “Targeted Review of Internal Models – Project Report”, April 2021, (page 7)

Summing up

Interest in this report is obviously likely to be confined for the most part to the technical experts that labour in the bowels of the risk management machines operated by the large sophisticated banks that are accredited to measure their capital requirements using internal models. There is however one item of general interest to an Australian audience and that is the news that the RWA of their European peer banks is likely to increase by a material amount due to modelling changes.

It might not be obvious why that is so for readers located outside Australia. The reason lies in the requirement that our banks (or Authorised Deposit-Taking Institutions to use the Australian jargon) be capitalised to an “Unquestionably Strong” level.

There are various ways in which this benchmark is interpreted but one is the requirement that the Australian ADIs maintain a CET1 ratio that lies in the top quartile of international peer banks. A chart showing how Australian ADIs compare to this international peer group is a regular feature of the capital adequacy data disclosed by the ADIs and the changes being implemented by the ECB are likely (all other things being equal) to make the Australian ADIs look even better in relative terms in the future.

Tony – From the Outside

The dark art of measuring residential mortgage risk

Residential mortgages are one of the seemingly more plain vanilla forms of bank lending. Notwithstanding, comparing capital requirements applied to this category of lending across different types of banks can be surprisingly complicated and is much misunderstood. I have touched on different aspects of this challenge in a number of mortgage risk weight “fact check” posts (see here and here), focussing for the most part on the comparison of “standardised” capital requirements compared to those applied to banks operating under the “internal rating based” (IRB) approach.

A discussion paper (“A more flexible and resilient capital framework for ADIs”, 8 December 2020) released by the Australian Prudential Regulation Authority (APRA) offers a good summary (see p27 “Box 2”) of the differences in capital requirements not captured by simplistic comparisons of risk weights. However, one of the surprises in the discussion paper was that APRA chose not to address one of these differences by aligning the credit conversion factors applied to off-balance sheet (non-revolving) residential mortgage exposures.

Understanding why APRA chose to maintain a different treatment of CCFs across the two approaches offers some insights into differences in the way that the two approaches recognise and measure the underlying risks.

Before proceeding we need to include a short primer on “off-balance exposures” and “CCFs”. Feel free to skip ahead if you already understand these concepts.

Off-balance sheet exposures are the difference between the maximum amount a bank has agreed to lend and the actual amount borrowed at any point in time.
The CCF is the bank’s estimate of how much of these undrawn limits will in fact have been called on (converted to an on balance sheet exposure) in the event a borrower defaults.
In the case of “non-revolving” residential mortgages, these off-balance sheet exposures typically arise because borrowers have got ahead of (“pre-paid”) their contractual loan repayments.

APRA noted that the credit conversion factor (CCF) currently applied to off-balance sheet exposures was much higher for IRB banks than for standardised, thereby partially offsetting the lower risk weights applied under the IRB approach. It had been expected that APRA would address this inconsistency by applying a 100% CCF under both approaches.

Contrary to this expectation, APRA has proposed to revise the CCFs applying to (non-revolving) off-balance sheet residential mortgage exposures as follows:

Current

Standardised 0-50%

IRB 100%

Proposed

40%

100% (unchanged)

The interesting nuance here is that APRA is not saying that standardised banks are likely to experience a lower percentage drawdown of credit limits in the event a borrower defaults. In the “Response to Submissions” that accompanied the Discussion Paper, APRA noted that “Borrowers do not typically enter default until they have fully drawn down on their available limit, including any prepayments ahead of their scheduled balance.”

However, APRA also noted that loans with material levels of prepayment are also likely to be lower risk based on the demonstrated greater capacity to service and repay the loan.

Under the IRB approach, the greater capacity to repay the loan is generally recognised through a lower PD estimate which the IRB formula translates into lower risk weights reflecting the lower risk. In the absence of some equivalent risk recognition mechanism in the standardised approach, APRA is proposing to use a concessional CCF treatment to reflect the lower risk of loans with material levels of prepayment. It notes that the concessional CCF treatment will also contribute to ensuring the difference in residential mortgage capital requirements between the standardised and IRB approaches remains appropriate.

Summing up:

Looked at in isolation, 100% is arguably the “right” value for the CCF to apply to off-balance sheet exposures for a non-revolving residential mortgage irrespective of whether it is being measured under the standardised or IRB approach
But a “concessional” CCF is a mechanism (fudge?) that allows the standardised approach to reflect the lower risk associated with loans with material levels of prepayment

Tony – From the Outside

Low Risk Residential Mortgage Risk Weights

I have posted a number of times on the question of residential mortgage risk weights, either on the general topic of the comparison of the risk weights applied to the standardised and IRB ADIs (see here) or the reasons why risk weights for IRB ADIs can be so low (see here).

On the question of relative risk weights, I have argued that the real difference between the standardised and IRB risk weights is overstated when framed in terms of simplistic comparisons of nominal risk weights that you typically read in the news media discussion of this question. I stand by that general assessment but have conceded that I have paid insufficient attention to the disparity in risk weights at the higher quality end of the mortgage risk spectrum.

A Discussion Paper released by APRA offers a useful discussion of this low risk weight question as part of a broader set of proposals intended to improve the transparency, flexibility and resilience of the Australian capital adequacy framework.

In section 4.2.1 of the paper, APRA notes the concern raised by standardised ADIs…

A specific concern raised by standardised ADIs in prior rounds of consultation has been the difference in capital requirements for lending at low LVRs. Stakeholders have noted that the lowest risk weight under the standardised approach would be 20 per cent under the proposed framework, but this appears to be significantly lower for the IRB approach. In response to this feedback, APRA has undertaken further analysis at a more detailed level, noting the difference in capital requirements that need to be taken into account when comparing capital outcomes under the standardised and IRB approaches (see Box 2 above).

But APRA’s assessment is that the difference is not material when you look beyond the simplistic comparison of risk weights and consider the overall difference in capital requirements

APRA does not consider that there is a material capital difference between the standardised and IRB approaches at the lower LVR level. For loans with an LVR less than 60 per cent, APRA has estimated that the pricing differential that could be reasonably attributed to differences in the capital requirements between the two approaches would be lower than the differential at the average portfolio outcome.

In explaining the reasons for this conclusion, APRA addresses some misconceptions about the IRB approach to low LVR lending compared to the standardised approach

In understanding the reasons for this outcome, it is important to understand the differences in how the standardised and IRB approaches operate. In particular, there are misconceptions around the capital requirement that would apply to low LVR lending under the IRB approach. For example, it would not be appropriate to solely equate the lowest risk weight reported by IRB ADIs in market disclosures with low LVR loans. The IRB approach considers a more complex range of variable interactions compared to the standardised approach. Under the standardised approach, a low risk weight is assigned to a loan with a low LVR at origination.

One of the key points APRA makes is that IRB ADIs do not get to originate loans at the ultra low risk weights that have been the focus of much of the concern raised by standardised ADIs.

In particular, IRB estimates are more dynamic through the life of the loan, for example, they are more responsive to a change in borrower circumstances or movements in the credit cycle. Standardised risk weights generally do not change over the life of a loan. For an IRB ADI, the lowest risk weight is generally applied to loans that have significantly prepaid ahead of schedule. A low LVR loan on the standardised approach is not necessarily assigned the lowest risk weight under the IRB approach at origination.

APRA states that it is not appropriate to introduce “dynamic”factors into the standardised risk weight framework.

APRA is not proposing to include dynamic factors in determining risk weights under the standardised approach for the following reasons:
– the standardised approach is intended to be simple and aligned with Basel III. For the standardised approach, APRA considers it more appropriate to focus on origination rather than behavioural variables as this has more influence on the quality of the portfolio and leads to less procyclical capital requirements; and
– the average difference between standardised and IRB capital outcomes is much narrower at the point of origination, which is the key point for competition. While the difference between standardised and IRB capital outcomes could widen over the life of the loan, APRA has ensured that the difference in average portfolio outcomes remains appropriate

But that it does intend to introduce a 5 per cent risk weight floor into the IRB approach to act as a backstop.

That said, APRA is proposing to implement a 5 per cent risk-weight floor for residential mortgage exposures under the IRB approach, to act as a simple backstop in ensuring capital outcomes do not widen at the lower risk segment of the portfolio. This is consistent with the approach taken by other jurisdictions and will limit the difference in capital outcomes between the standardised and IRB approaches for lower risk exposures. This risk-weight floor is in addition to other factors that will reduce the difference in capital outcomes between standardised and IRB ADIs, such as the higher CCB for IRB ADIs and lower CCF estimates for standardised ADIs.

As always, it remains possible that I am missing something. The explanation offered by APRA however gives me confidence that my broad argument about the overstatement of the difference has been broadly correct. Equally importantly, the changes to residential mortgage risk weights proposed in the Discussion Paper will further reduce the gap that does exist.

Tony – From the Outside

RBNZ COVID 19 Stress Tests

The RBNZ just released the results of the stress testing conducted by itself and a selection of the larger NZ banks to test resilience to the risks posed by COVID 19.

The extract below summarises the process the RBNZ followed and its key conclusions:

 COVID-19 stress test consisted of two parts. First, a desktop stress test where the Reserve Bank estimated the impact on profitability and capital for nine of New Zealand’s largest banks to the impact of two severe but plausible scenarios. Second, the Reserve Bank coordinated a process in which the five largest banks used their own models to estimate the effect on their banks for the same scenarios.
 The pessimistic baseline scenario can be characterised as a one-in-50 to one-in-75 year event with the unemployment rate rising to 13.4 percent and a 37 percent fall in property prices. In the very severe scenario, the unemployment rate reaches 17.7 percent and house prices fall 50 percent. It should be noted that these scenarios are hypothetical and are significantly more severe than the Reserve Banks’ baseline scenario.
 The overall conclusion from the Reserve Bank’s modelling is that banks could draw on their existing capital buffers and continue lending to support lending in the economy during a downturn of the severity of the pessimistic baseline scenario. However, in the more severe scenario, banks capital fell below the regulatory minimums and would require significant mitigating actions including capital injections to continue lending. This reinforces the need for strong capital buffers to provide resilience against severe but unlikely events.
 The results of this stress test supports decisions that were made as part of the Capital Review to increase bank capital levels. The findings will help to inform Reserve Bank decisions on the timing of the implementation of the Capital Review, and any changes to current dividend restrictions.
“Outcome from a COVID-19 stress test of New Zealand banks”, RBNZ Bulletin Vol 83, No 3 September 2020

I have only skimmed the paper thus far but there is one detail I think worth highlighting for anyone not familiar with the detail of how bank capital adequacy is measured – specifically the impact of Risk Weighted Assets on the decline in capital ratios.

The RBNZ includes two useful charts which decompose the aggregate changes in CET1 capital ratio by year two of the scenario.

RBNZ Desktop Results – Pessimistic Baseline Scenario

In the “Pessimistic Baseline Scenario”(PBS), the aggregate CET1 ratio declines 3.7 percentage points to 7.7 percent. This is above both the regulatory minimum and the threshold for mandatory conversion of Additional Tier 1 Capital. What I found interesting was that RWA growth contributed 2.2 percentage points to the net decline.

The RBNZ quite reasonably points out that banks will amplify the downturn if they restrict the supply of credit to the economy but I think it is also reasonable to assume that the overall level of loan outstandings is not growing and may well be shrinking due to the decline in economic activity. So a substantial portion of the decline in the aggregate CET1 ratio is due to the increase in average risk weights as credit quality declines. The C ET1 ratio is being impacted not only by the increase in impairment expenses reducing the numerator, there is a substantial added decline due to the way that risk weighted assets are measured

RBNZ Desktop Results – Very Severe Scenario

In the “Very Severe Scenario”(VSS), the aggregate CET1 ratio declines 5.6 percentage points to 5.8 percent. The first point to note here is that CET1 only remains above the 4.5% prudential minimum by virtue of the conversion of 1.6 percentage points of Additional Tier 1 Capital. Assuming 100% of AT1 was converted, this also implies that the Tier 1 ratio is below the 6.0% prudential minimum.

These outcomes provide food for thought but I few points I think wroth considering further before accepting the headline results at face value:

The headline results are materially impacted by the pro cyclicality of the advanced forms of Risk Weighted Asset measurement – risk sensitive measures offer useful insights but we also need to understand they ways in which they can also amplify the impacts of adverse scenarios rather than just taking the numbers at face value
The headline numbers are all RBNZ Desktop results – it would be useful to get a sense of exactly how much the internal stress test modelling conducted by the banks varied from the RBNZ Desktop results – The RBNZ stated (page 12) that the bank results were similar to its for the PBS but less severe in the VSS.

As always, it is entirely possible that I am missing something but I feel that the answer to bank resilience is not just a higher capital ratio. A deeper understanding of the pro cyclicality embedded in the system will I think allow us to build a better capital adequacy framework. As yet I don’t see this topic getting the attention it deserves.

Tony – From the Outside

The case for low mortgage risk weights

I have touched on residential mortgage risk weights a couple of times in this blog, most recently in a post on the Dutch proposal to increase residential mortgage RW. This post explores the question of why residential mortgage RW under the Internal Rating Based (IRB) approach can be so low. More importantly, can we trust these very low risk weights (and the banks generating them) or is this yet more evidence that the IRB approach is an unreliable foundation for measuring bank capital requirements? It also touches on some of the issues we encounter in cross border comparisons of capital strength.

It has to be said at this point that IRB modelling is not an area where I claim deep expertise and I would welcome comments and input from people who do have this subject matter expertise. However, it is an important issue given the role that residential mortgage lending plays both in the economy as a whole. If nothing else, the post will at least help me get my thoughts on these questions into some kind of order and potentially invite comments that set me straight if I have got anything wrong. Notwithstanding the importance of the issue, this post is pretty technical so likely only of interest if you want to dig into the detailed mechanics of the IRB approach.

Recapping on the Dutch proposal to increase mortgage risk weights

First a recap on what the Dutch bank supervisor proposes to do. Residential mortgage RW in the Netherlands are amongst the lowest observed in Europe

DNB:Financial Stability Report Autumn 2019

The Dutch banks can of course cite reasons why this is justified but, in order to improve the resilience of the banking system, the Dutch banking supervisor proposes to introduce a floor set at 12% on how low the RW can be. The 12% floor applies to loans with a dynamic Loan to Value (LTV) of 55% or lower. The RW floor increases progressively as the LTV increases reaching a maximum of 45% for loans with a LTV of 100% or more. DNB expects the application of the measure to increase the average risk weights of Dutch IRB banks by 3-4 percentage points (from 11% to 14%-15%).

What drives the low end of the IRB Mortgage RW?

None of the discussion set out below is in any way intended to challenge bank supervisors seeking to apply limits to the low mortgage risk weights we observe being generated by the internal models developed by IRB banks. That is a whole separate discussion but the move to higher RW on these exposures broadly makes sense to me, not only for reasons of systemic resilience, but also with regard to the way that it reduces the disparity between IRB RW and those the standardised banks are required to operate against. It is however useful to understand what is driving the model outcomes before citing them as evidence of banks gaming the system.

This extract from Westpac’s September 2019 Pillar 3 Report shows a weighted average RW of 24% with individual segments ranging from 6% to 137%. The CBA Pillar 3 shows a similar pattern (RW range from 4.4% to 173.5%). I won’t get too much into the technical detail here but the effective IRB RW is higher when you factor in Regulatory Expected Loss. The impact on the RW in the table below is roughly 16% on average (I divide REL by .08 to translate it to an RWA equivalent and then divide by RWA) but this effect only becomes material for the 26% and higher RW bands).

Source: Westpac Pillar 3 Report – Sep 2019

I am very happy to stand corrected on the facts but my understanding is that the 6% and 14% RW bands in the table above capture “seasoned” portions of the loan portfolio where the Loan to Valuation (LVR) ratio has declined substantially from the circa 80% plus typically observed in newly originated loans. The declining LVR is of course a natural outcome for Principal and Interest loans which is the kind traditional prudent banking prefers.

What at face value looks like an incredibly thin capital requirement starts to make more sense when you consider the fact that the borrowers in these segments have demonstrated their capacity to service their loans and, perhaps more importantly, have built up a substantial pool of their own equity in the property that will absorb very substantial declines in property prices before the bank is likely to face a loss.

Australian owner occupied borrowers have an incentive to repay as fast as possible because their interest is not tax deductible (making the mortgage repayment one of the best applications of surplus cash) and they typically borrow on a floating rate basis. The natural amortisation of loan principal is also likely to have been accelerated by the progressive decline in interest rates in recent years which has seen a large share of borrowers apply the interest saving to higher principal repayments.

Comparing Dutch and Australian Mortgage Risk Weights

Looking at the Dutch RW provides some perspective on the mortgage RW of the Australian IRB banks and the initiatives APRA has implemented to increase them. I will only scratch the surface of this topic but it is interesting none the less to compare the 14-15% average RW the Dutch IRB banks will be required to hold with the 25% average RW that Australian IRB banks must hold.

The Dutch banks cite a favourable legal system that supports low LGD by allowing them to quickly realise their security on defaulted loans. That is a sound argument when you are comparing to a jurisdiction where it can take up to 3 years for a bank to gain access to the security underpinning a defaulted loan. That said, the Australian banks can make a similar argument so that does not look like a definitive factor in favour of lower Dutch RW.

The Australian LTV is based on the amortised value of the loan compared to the value of the property at the time the loan was originated. The Dutch LTV as I understand it seem to includes the updated value of the property as the loan ages. Again I don’t see anything in the Dutch system that renders their residential mortgage lending fundamentally less risky than the Australian residential mortgage.

The other positive factor cited by the Dutch banks is the tax deductibility of mortgage interest which applies even where the property is owner occupied. In Australia, interest on loans for owner occupied property is not tax deductible. The Dutch banks argue that the tax deduction on interest enhances the capacity of the borrower to service a loan but my guess is that this advantage is highly likely to be translated into higher borrowing capacity and hence higher property prices so it is not clear that there is a net improvement in the capacity to repay the loan.

I obviously only have a very rudimentary understanding of Dutch tax rules but my understanding is that tax deductibility of interest expense in some European jurisdictions is quid pro quo for including the implied value of rental on the property in the owner’s taxable income. If that is the case then it looks like tax deductibility of interest is a zero sum game from the lending bank perspective. Qualified by the caveats above, I will provisionally take the side of the Australian mortgage in this comparison. It seems equally likely to me that the the absence of a tax deduction creates an incentive for Australian borrowers to repay their loan as quickly as possible and hence for a greater proportion of loans outstanding to move into the low LVR bands that insulate the bank from the risk of loss. There does not seem to be the same incentive in the Dutch system, especially where the loans are fixed rate.

Summing up

The purpose of this post was mostly to help me think through the questions posed in the introduction. If you are still reading at this point then I fear you (like I) take bank capital questions way too seriously.

There are two main points I have attempted to explore and stake out a position on:

What at face value looks like an incredibly thin capital requirement for some parts of the residential mortgage portfolio start to make more sense when you consider the fact that the borrowers in these segments have demonstrated their capacity to service their loans and have built up a substantial pool of their own equity in the property that will absorb very substantial declines in property prices before the bank is likely to face a loss.
Cross border comparisons of capital are complicated but mortgages are a big part of the Australian bank risk profile and I still feel like they stack up relatively well in comparison to other jurisdictions that cite structural reasons why theirs are low risk.

If you have some evidence that contradicts what I have outlined above then by all means please let me know what I am missing.

Tony

Capital geeks take note – the IRB scaling factor strikes again

Capital

Another reminder on the importance of paying attention to the detail courtesy of a story that I picked up reading Matt Levine’s “Money Stuff” column on Bloomberg.

This extract from Matt’s column captures the essential facts:

Here, from Johannes Borgen, is a great little story about bank capital. Yesterday Coventry Building Society, a U.K. bank, announced “a correction to its calculation of risk weighted assets” that will lower its common equity Tier 1 capital ratio from 34.2% to 32.6%. That’s still well over regulatory requirements, so this is not a big deal. But the way Coventry messed up is funny:
“The Society uses Internal Ratings Based (“IRB”) models to calculate its Risk Weighted Assets (“RWAs”) and is seeking to update these models to ensure compliance with upcoming Basel III reforms. During the process of transitioning models, the Society has identified an omission in connection with its historic calculation of its RWAs. Specifically, the necessary 6% scalar was not applied to the core IRB model outputs. The core IRB models themselves are not impacted.”
For banks that use Internal Ratings Based models, the way the Basel capital rules work is that you apply a complicated formula to calculate the risk weights of your assets, and then at the end of the formula you multiply everything by 1.06. That’s kind of weird. (The Basel capital regime for banks using IRB models “applies a scaling factor in order to broadly maintain the aggregate level of minimum capital requirements, while also providing incentives to adopt the more advanced risk-sensitive approaches.”) It’s weird enough that in the “upcoming Basel III reforms” regulators plan to get rid of it: The 1.06 multiplier is a kludge, and if you measure your risk-weighted assets a bit more accurately and conservatively, you shouldn’t have to multiply them by 1.06 at the end.
Matt Levine, “Money Stuff”, Bloomberg

For anyone new to this game who wants to dig a bit deeper into how the advanced capital requirements are calculated, the Explanatory Note published by the BCBS in July 2005 is still a good place to start. I published a note on that paper on my blog here. The RBNZ also produced a useful note on how they used the IRB function in the portfolio modelling work they used to support their recent changes to NZ capital requirements.

It should be noted however that none of these documents discuss the 6% scaling factor. I open to alternative perspectives on this but my recollection is that the 6% scaling factor was introduced post July 2005 in one of the multiple recalibration exercises the BCBS employed to ensure that the IRB function did not reduce capital requirements too much relative to the status quo operating under Basel I. It is effectively a “fudge” factor designed to produce a number the BCBS was comfortable with (at that time).

Tony

Mortgage Risk Weights – revisited

I post on a range of topics in banking but residential mortgage risk weights is one that seems to generate the most attention. I first posted on the topic back in Sep 2018 and have revisited the topic a few times (Dec 2018, June 2019#1, June 2019#2, and Nov 2019) .

The posts have tended to generate a reasonable number of views but limited direct engagement with the arguments I have advanced. Persistence pays off however because the last post did get some specific and very useful feedback on the points I had raised to argue that the difference in capital requirements between IRB and Standardised Banks was not as big as it was claimed to be.

My posts were a response to the discussion of this topic I observed in the financial press which just focussed on the nominal difference in the risk weights (i.e. 25% versus 39%) without any of the qualifications. I identified 5 problems with the simplistic comparison cited in the popular press and by some regulators:

Problem 1 – Capital adequacy ratios differ
Problem 2 – You have to include capital deductions
Problem 3 – The standardised risk weights for residential mortgages seems set to change
Problem 4 – The risk of a mortgage depends on the portfolio not the individual loan
Problem 5 – You have to include the capital required for Interest Rate Risk in the Banking Book

With the benefit of hindsight and the feedback I have received, I would concede that I have probably paid insufficient attention to the disparity between risk weights (RW) at the higher quality end of the mortgage risk spectrum. IRB banks can be seen to writing a substantial share of their loan book at very low RWs (circa 6%) whereas the best case scenario for standardised banks is a 20% RW. The IRB banks are constrained by the requirement that their average RW should be at least 25% and I thought that this RW Floor was sufficient to just focus on the comparison of average RW. I also thought that the revisions to the standardised approach that introduced the 20% RW might make more of a difference. Now I am not so sure. I need to do a bit more work to resolve the question so for the moment I just want to go on record with this being an issue that needs more thought than I have given it to date.

Regarding the other 4 issues that I identified in my first post, I stand by them for the most part. That does not mean I am right of course but I will briefly recap on my arguments, some of the push back that I have received and areas where we may have to just agree to disagree.

Target capital adequacy ratios differ materially. The big IRB banks are targeting CET1 ratios based on the 10.5% Unquestionably Strong Benchmark and will typically have a bit of a buffer over that threshold. Smaller banks like Bendigo and Suncorp appear to operate with much lower CET1 targets (8.5 to 9.0%). This does not completely offset the nominal RW difference (25 versus 39%) but it is material (circa 20% difference) in my opinion so it seem fair to me that the discussion include this fact. I have to say that not all of my correspondents accepted this argument so it seems that we will have to agree to disagree.

You have to include capital deductions. In particular, the IRB banks are required to hold CET1 capital for the shortfall between their loan loss provision and a regulatory capital value called “Regulatory Expected Loss”. There did not appear to be a great awareness of this requirement and a tendency to dismiss it but my understanding is that it can increase the effective capital requirement by 10-12% which corresponds to an effective IRB RW closer to 28% than 25%.

The risk of a mortgage depends on the overall portfolio not the individual loan. My point here has been that small banks will typically be less diversified than big banks and so that justifies a difference in the capital requirements. I have come to recognise that the difference in portfolio risk may be accentuated to the extent that capital requirements applied to standardised banks impede their ability to capture a fair share of the higher quality end of the residential mortgage book. So I think my core point stands but there is more work to do here to fully understand this aspect of the residential mortgage capital requirements. In particular, I would love get more insight into how APRA thought about this issue when it was calibrating the IRB and standardised capital requirements. If they have spelled out their position somewhere, I have not been able to locate it.

You have to include the capital required for Interest Rate Risk in the Banking Book (IRRBB). I did not attempt to quantify how significant this was but simply argued that it was a requirement that IRB banks faced that standardised banks did not and hence it did reduce the benefit of lower RW. The push back I received was that the IRRBB capital requirement was solely a function of IRB banks “punting” their capital and hence completely unrelated to their residential mortgage loans. I doubt that I will resolve this question here and I do concede that the way in which banks choose to invest their capital has an impact on the size of the IRRBB capital requirement. That said, a bank has to hold capital to underwrite the risk in its residential mortgage book and, all other thinks being equal, an IRB bank has to hold more capital for the IRRBB requirement flowing from the capital that it invests on behalf of the residential mortgage book. So it still seems intuitively reasonable to me to make the connection. Other people clearly disagree so we may have to agree to disagree on this aspect.

Summing up, I had never intended to say that there was no difference in capital requirements. My point was simply that the difference is not as big as is claimed and I was yet to see any analysis that considered all of the issues relevant to properly understand what the net difference in capital requirements is. The issue of how to achieve a more level playing field between IRB and Standardised Banks is of course about much more than differences in capital requirements but it is an important question and one that should be based on a firmer set of facts that a simplistic comparison of the 39% standardised versus 25% IRB RW that is regularly thrown around in the discussion of this question.

I hope I have given a fair representation here of the counter arguments people have raised against my original thesis but apologies in advance if I have not. My understanding of the issues has definitely been improved by the challenges posted on the blog so thanks to everyone who took the time to engage.

Tony

Mortgage risk weights fact check revisited – again

The somewhat arcane topic of mortgage risk weights is back in the news. It gets popular attention to the extent they impact the ability of small banks subject to standardised risk weights to compete with bigger banks which are endorsed to use the more risk sensitive version based on the Internal Ratings Based (IRB) approach. APRA released a Discussion Paper (DP) in February 2018 titled “Revisions to the capital framework for authorised deposit-taking institutions”. There are reports that APRA is close to finalising these revisions and that this will address the competitive disadvantage that small banks suffer under the current regulation.

This sounds like a pretty simple good news story – a victory for borrowers and the smaller banks – and my response to the discussion paper when it was released was that there was a lot to like in what APRA proposed to do. I suspect however that it is a bit more complicated than the story you read in the press.

The difference in capital requirements is overstated

Let’s start with the claimed extent of the competitive disadvantage under current rules. The ACCC’s Final Report on its “Residential Mortgage Price Inquiry” described the challenge with APRA’s current regulatory capital requirements as follows:

“For otherwise identical ADIs, the advantage of a 25% average risk weight (APRA’s minimum for IRB banks) compared to the 39% average risk weight of standardised ADIs is a reduction of approximately 0.14 percentage points in the cost of funding the loan portfolio. This difference translates into an annual funding cost advantage of almost $750 on a residential mortgage of $500 000, or about $15 000 over the 30 year life of a residential mortgage (assuming an average interest rate of 7% over that period).”

You could be forgiven for concluding that this differential (small banks apparently required to hold 56% more capital for the same risk) is outrageous and unfair.

Just comparing risk weights is less than half the story

I am very much in favour of a level playing field and, as stated above, I am mostly in favour of the changes to mortgage risk weights APRA outlined in its discussion paper but I also like fact based debates.

While the risk weights for big banks are certainly lower on average than those required of small banks, the difference in capital requirements is not as large as the comparison of risk weights suggests. To understand why the simple comparison of risk weights is misleading, it will be helpful to start with a quick primer on bank capital requirements.

The topic can be hugely complex but, reduced to its essence, there are three elements that drive the amount of capital a bank holds:

The risk weights applied to its assets
The target capital ratio applied to those risk weighted assets
Any capital deductions required when calculating the capital ratio

I have looked at this question a couple of times (most recently here) and identified a number of problems with the story that the higher risk weights applied to residential mortgages originated by small bank places them at a severe competitive disadvantage:

Target capital ratios – The target capital adequacy ratios applied to their higher standardised risk weighted assets are in some cases lower than the IRB banks and higher in others (i.e. risk weights alone do not determine how much capital a bank is required to hold).

Portfolio risk – The risk of a mortgage depends on the portfolio not the individual loan. The statement that a loan is the same risk irrespective of whether it is written by a big bank or small bank sounds intuitively logical but is not correct. The risk of a loan can only be understood when it is considered as part of the portfolio the bank holds. All other things being equal, small banks will typically be less diversified and hence riskier than a big bank.

Capital deductions – You also have to include capital deductions and the big banks are required to hold capital for a capital deduction linked to the difference between their loan loss provisions and a regulatory capital value called “Regulatory Expected Loss”. The exact amount varies from bank to bank but I believe it increases the effective capital requirement by 10-12% (i.e. an effective RW closer to 28% for the IRB banks).

IRRBB capital requirement – IRB banks must hold capital for Interest Rate Risk in the Banking Book (IRRBB) while the small standardised banks do not face an explicit requirement for this risk. I don’t have sufficient data to assess how significant this is, but intuitively I would expect that the capital that the major banks are required to hold for IRRBB will further narrow the effective difference between the risk weights applied to residential mortgages.

How much does reducing the risk weight differential impact competition in the residential mortgage market?

None of the above is meant to suggest that the small banks operating under the standardised approach don’t have a case for getting a lower risk weight for their higher quality lower risk loans. If the news reports are right then it seems that this is being addressed and that the gap will be narrower. However, it is important to remember that:

The capital requirement that the IRB banks are required to maintain is materially higher than a simplistic application of the 25% average risk weight (i.e. the IRB bank advantage is not as large as it is claimed to be).
The standardised risk weight does not seem to be the binding constraint so reducing it may not help the small banks much if the market looks through the change in regulatory risk measurement and concludes that nothing has changed in substance.

One way to change the portfolio quality status quo is for small banks to increase their share of low LVR loans with a 20% RW. Residential mortgages do not, for the most part, get originated at LVR of sub 50% but there is an opportunity for small banks to try to refinance seasoned loans where the dynamic LVR has declined. This brings us to the argument that IRB banks are taking the “cream” of the high quality low risk lending opportunities.

The “cream skimming” argument

A report commissioned by COBA argued that:

“While average risk weights for the major banks initially rose following the imposition of average risk weight on IRB banks by APRA, two of the major banks have since dramatically reduced their risk weights on residential mortgages with the lowest risk of default. The average risk weights on such loans is now currently on average less than 6 per cent across the major banks.”
“Despite the imposition of an average risk weight on residential home loans, it appears some of the major banks have decided to engage in cream skimming by targeting home loans with the lowest risk of default. Cream skimming occurs when the competitive pressure focuses on the high-demand customers (the cream) and not on low- demand ones (the skimmed milk) (Laffont & Tirole, 1990, p. 1042). Cream skimming has adverse consequences as it skews the level of risk in house lending away from the major banks and towards other ADIs who have to deal with an adversely selected and far riskier group of home loan applicants.”
“Reconciling Prudential Regulation with Competition” prepared by Pegasus Economics May 2019 (page 43)

It is entirely possible that I am missing something here but, from a pure capital requirement perspective, it is not clear that IRB banks have a material advantage in writing these low risk loans relative to the small bank competition. The overall IRB portfolio must still meet the 25% risk weight floor so any loans with 6% risk weights must be offset by risk weights (and hence riskier loans) that are materially higher than the 25% average requirement. I suspect that the focus on higher quality low risk borrowers by the IRB banks was more a response to the constraints on capacity to lend than something that was driven by the low risk weights themselves.

Under the proposed revised requirements, small banks in fact will probably have the advantage in writing sub 50% LVR loans given that they can do this at a 20% risk weight without the 25% floor on their average risk weights and without the additional capital requirements the IRB banks face.

I recognise there are not many loans originated at this LVR band but there is an opportunity in refinancing seasoned loans where the combined impact of principal reduction and increased property value reduces the LVR. In practice the capacity of small banks to do this profitably will be constrained by their relative expense and funding cost disadvantage. That looks to me to be a bigger issue impacting the ability of small banks to compete but that lies outside the domain of regulatory capital requirements.

Maybe this potential arbitrage does not matter in practice but APRA could quite reasonably impose a similar minimum average RW on Standardised Banks if the level playing field argument works both ways. This should be at least 25% but arguably higher once you factor in the fact that the small banks do not face the other capital requirements that IRB banks do. Even if APRA did not do this, I would expect the market to start looking more closely at the target CET1 for any small bank that accumulated a material share of these lower risk weight loans.

Implications

Nothing in this post is meant to suggest that increasing the risk sensitivity of the standardised risk weights is a bad idea. It seems doubtful however that this change alone will see small banks aggressively under cutting large bank competition. It is possible that small bank shareholders may benefit from improved returns on equity but even that depends on the extent to which the wholesale markets do not simply look through the change and require smaller banks to maintain the status quo capital commitment to residential mortgage lending.

What am I missing …

How much capital is enough? – The NZ perspective

The RBNZ has delivered the 4th instalment in a Capital Review process that was initiated in March 2017 and has a way to run yet. The latest consultation paper addresses the question “How much capital is enough?”. The banking industry has until 29 March 2019 to respond with their views but the RBNZ proposed answer is:

A Tier 1 capital requirement of 16% of RWA for systemically important banks and 15% of RWA for all other banks
The Tier 1 minimum requirement to remain unchanged at 6% (with AT1 capital continuing to be eligible to contribute a maximum of 1.5 percentage points)
The proposed increased capital requirement to be implemented via an overall prudential capital buffer of 9-10% of RWA comprised entirely of CET1 capital;
- Capital Conservation Buffer 7.5% (currently 2.5%)
- D-SIB Buffer 1.0% (no change)
- Counter-cyclical buffer 1.5% (currently 0%)

The increase in the capital ratio requirement is proposed to be supplemented with a series of initiatives that will increase the RWA of IRB banks:

The RBNZ proposes to 1) remove the option to apply IRB RW to sovereign and bank exposures, 2) increase the IRB scalar (from 1.06 to 1.20) and 3) to introduce an output floor set at 85% of the Standardised RWA on an aggregate portfolio basis
As at March 2018, RWA’s produced by the IRB approach averaged 76% of the Standardised Approach and the RBNZ estimate that the overall impact will be to increase the aggregate RWA to 90% of the outcome generated by the Standardised approach (i.e. the IRB changes, not the output floor, drive the increase in RWA)
Aggregate RWA across the four IRB banks therefore increases by approximately 16%, or $39bn, compared to March 2018 but the exact impact will depend on how IRB banks respond to the higher capital requirements

The RBNZ has also posed the question whether a Tier 2 capital requirement continues to be relevant given the substantial increase in Tier 1 capital.

Some preliminary thoughts …

There is a lot to unpack in this paper so this post will only scratch the surface of the issues it raises …

The overall number that the RBNZ proposes (16%) is not surprising.It looks to be at the lower end of what other prudential regulators are proposing in nominal terms
But is in the same ball park once you allow for the substantial increase in IRB RWA and the fact that it is pretty much entirely CET1 capital
What is really interesting is the fundamentally different approach that the RBNZ has adopted to Tier 2 capital and bail-in versus what APRA (and arguably the rest of the world) has adopted
- The RBNZ proposal that the increased capital requirement take the form of CET1 capital reflects its belief that “contingent convertible instruments” should be excluded from what counts as capital
- Exactly why the RBNZ has adopted this position is a complex post in itself (their paper on the topic can be found here) but the short version (as I understand it) is that they think bail-in capital instruments triggered by non-viability are too complex and probably won’t work anyway.
- Their suggestion that Tier 2 probably does not have a role in the capital structure they have proposed is logical if you accept their premise that Point of Non-Viability (PONV) triggers and bail-in do not work.
The RBNZ highlight a significantly enhanced role for prudential capital buffersI am generally in favour of bigger, more dynamic, capital buffers rather than higher fixed minimum requirements and I have argued previously in favour of the base rate for the counter-cyclical being a positive value (the RBNZ propose 1.5%)
- But the overall size of the total CET1 capital buffer requirement requires some more considered thought about 1) the role of bail-in structures and PONV triggers in the capital regulation toolkit (as noted above) and 2) whether the impacts of the higher common equity requirement will be as benign as the RBNZ analysis suggests
I am also not sure that the indicative capital conservation responses they have outlined (i.e. discretionary distributions limited to 60% of net earnings in the first 250bp of the buffer, falling to 30% in the next 250bp and no distributions thereafter) make sense in practice.
- This is because I doubt there will be any net earnings to distribute if losses are sufficient to reduce CET1 capital by 250bp so the increasing capital conservation requirement is irrelevant.
Last, but possibly most importantly, we need to consider the impact on the Australian parents of the NZ D-SIB banks and how APRA responds. The increase in CET1 capital proposed for the NZ subsidiaries implies that, for any given amount of CET1 capital held by the Level 2 Banking Group, the increased strength of the NZ subsidiaries will be achieved at the expense of the Australian banking entities
- Note however that the impact of the higher capital requirement in NZ will tend to be masked by the technicalities of how bank capital ratios are calculated.
  - It probably won’t impact the Level 2 capital ratios at all since these are a consolidated view of the combined banking group operations of the Group as a whole
  - The Level 1 capital ratios for the Australian banks also treat investments in bank subsidiaries relatively generously (capital invested in unlisted subsidiaries is treated as a 400% risk weighted asset rather than a capital deduction).

Conclusion

Overall, I believe that the RBNZ is well within its rights to expect the banks it supervises to maintain a total level of loss absorbing capital of 16% or more. The enhanced role for capital buffers is also a welcome move.

The issue is whether relying almost entirely on CET1 capital is the right way to achieve this objective. This is however an issue that has been debated for many decades with no clear resolution. It will take some time to fully unpack the RBNZ argument and figure out how best to articulate why I disagree. In the interim, any feedback on the issues I have outlined above would be most welcome.

Tony

Distinguishing luck and skill

Quantifying Luck’s Role in the Success Equation

“… we vastly underestimate the role of luck in what we see happening around us”

This post is inspired by a recent read of Michael Mauboussin’s book “The Success Equation: Untangling Skill and Luck in Business, Sports and Investing”. Mauboussin focuses on the fact that much of what we experience is a combination of skill and luck but we tend to be quite bad at distinguishing the two. It may not unlock the secret to success but, if you want to get better at untangling the contributions that skill and luck play in predicting or managing future outcomes, then this book still has much to offer.

“The argument here is not that you can precisely measure the contributions of skill and luck to any success or failure. But if you take concrete steps toward attempting to measure those relative contributions, you will make better decisions than people who think improperly about those issues or who don’t think about them at all.”

Structure wise, Mauboussin:

Starts with the conceptual foundations for thinking about the problem of distinguishing skill and luck,
Explores the analytical tools we can use to figure out the extent to which luck contributes to our achievements, successes and failures,
Finishes with some concrete suggestions about how to put the conceptual foundations and analytical tools to work in dealing with luck in decisions.

Conceptual foundations

It is always good to start by defining your terms; Mauboussin defines luck and skill as follows:

“Luck is a chance occurrence that affects a person or a group.. [and] can be good or bad [it] is out of one’s control and unpredictable”
Skill is defined as the “ability to use one’s knowledge effectively and readily in execution or performance.”

Applying the process that Mauboussin proposes requires that we first roughly distinguish where a specific activity or prediction fits on the continuum bookended by skill and luck. Mauboussin also clarifies that:

Luck and randomness are related but not the same: He distinguishes luck as operating at the level of the individual or small group while randomness operates at the level of the system where more persistent and reliable statistical patterns can be observed.
Expertise does not necessarily accumulate with experience: It is often assumed that doing something for a long time is sufficient to be an expert but Mauboussin argues that in activities that depend on skill, real expertise only comes about via deliberate practice based on improving performance in response to feedback on the ways in which the input generates the predicted outcome.

Mauboussin is not necessarily introducing anything new in his analysis of why we tend to bad at distinguishing skill and luck. The fact that people tend to struggle with statistics is well-known. The value for me in this book lies largely in his discussion of the psychological dimension of the problem which he highlights as exerting the most profound influence. The quote below captures an important insight that I wish I understood forty years ago.

“The mechanisms that our minds use to make sense of the world are not well suited to accounting for the relative roles that skill and luck play in the events we see taking shape around us.”

The role of ideas, beliefs and narratives is a recurring theme in Mauboussin’s analysis of the problem of distinguishing skill and luck. Mauboussin notes that people seem to be pre-programmed to want to fit events into a narrative based on cause and effect. The fact that things sometimes just happen for no reason is not a satisfying narrative. We are particularly susceptible to attributing successful outcomes to skill, preferably our own, but we seem to be willing to extend the same presumption to other individuals who have been successful in an endeavour. It is a good story and we love stories so we suppress other explanations and come to see what happened as inevitable.

Some of the evidence we use to create these narratives will be drawn from what happened in specific examples of the activity, while we may also have access to data averaged over a larger sample of similar events. Irrespective, we seem to be predisposed to weigh the specific evidence more heavily in our intuitive judgement than we do the base rate averaged over many events (most likely based on statistics we don’t really understand). That said, statistical evidence can still be “useful” if it “proves” something we already believe; we seem to have an intuitive bias to seek evidence that supports what we believe. Not only do we fail to look for evidence that disproves our narrative, we tend to actively suppress any contrary evidence we encounter.

Analytical tools for navigating the skill luck continuum

We need tools and processes to help manage the tendency for our intuitive judgements to lead us astray and to avoid being misled by arguments that fall into the same trap or, worse, deliberately exploit these known weaknesses in our decision-making process.

One process proposed by Mauboussin for distinguishing skill from luck is to:

First form a generic judgement on what the expected accuracy of our prediction is likely to be (i.e. make a judgement on where the activity sits on the skill-luck continuum)
Next look at the available empirical or anecdotal evidence, distinguishing between the base rate for this type of activity (if it exists) and any specific evidence to hand
Then employ the following rule:
- if the expected accuracy of the prediction is low (i.e. luck is likely to be a significant factor), you should place most of the weight on the base rate
- if the expected accuracy is high (i.e. there is evidence that skill plays the prime role in determining the outcome of what you are attempting to predict), you can rely more on the specific case.
use the data to test if the activity conforms to your original judgement of how skill and luck combine to generate the outcomes

Figuring out where the activity sits on the skill-luck continuum is the critical first step and Mauboussin offers three methods for undertaking this part of the process: 1) The “Three Question” approach, 2) Simulation and 3) True Score Theory. I will focus here on the first method which involves

First ask if you can easily assign a cause to the effect you are seeking to predict. In some instances the relationship will be relatively stable and linear (and hence relatively easy to predict) whereas the results of other activities are shaped by complex dependencies such as cumulative advantage and social preference. Skill can play a part in both activities but luck is likely to be a more significant factor in the latter group.
Determining the rate of reversion to the mean: Slow reversion is consistent with activities dominated by skill, while rapid reversion comes from luck being the more dominant influence. Note however that complex activities where cumulative advantage and social preference shape the outcome may not have a well-defined mean to revert to. The distribution of outcomes for these activities frequently conform to a power law (i.e. there are lots of small values and relatively few large values).
Is there evidence that expert prediction is useful? When experts have wide disagreement and predict poorly, that is evidence that luck is a prime factor shaping outcomes.

One of the challenges with this process is to figure out how large a sample size you need to determine if there is a reliable relationship between actions and outcome that evidences skill. Another problem is that a reliable base rate may not always be available. That may be because the data has just not been collected but also because a reliable base rate simply may not even exist.

The absence of a reliable base rate to guide decisions is a feature of activities that do not have simple linear relationships between cause and effect. These activities also tend to fall into Nassim Taleb’s “black swan” domain. The fundamental lesson in this domain of decision making is to be aware of the risks associated with naively applying statistical probability based methods to the problem. Paul Wilmott and David Orrell use the idea of a “zone of validity” to make the same point in “The Money Formula”.

The need to understand power laws and the mechanisms that generate them also stands out in Mauboussin’s discussion of untangling skill and luck.

The presence of a power law depends in part on whether events are dependent on, or independent of, one another. In dependent systems, initial conditions matter and come to matter more and more as time goes on. The final outcomes are (sometimes surprisingly) sensitive to both minor variations in the initial conditions and to the path taken over time. Mauboussin notes that a number of mechanisms are responsible for this phenomenon including preferential attachment, critical points and phase transitions are also crucial.

“In some realms, independence and bell-shaped distributions of luck can explain much of what we see. But in activities such as the entertainment industry, success depends on social interaction. Whenever people can judge the quality of an item by several different criteria and are allowed to influence one another’s choices, luck will play a huge role in determining success or failure.”
“For example, if one song happens to be slightly more popular than another at just the right time, it will tend to become even more popular as people influence one another. Because of that effect, known as cumulative advantage, two songs of equal quality, or skill, will sell in substantially different numbers. … skill does play a role in success and failure, but it can be overwhelmed by the influence of luck. In the jar model, the range of numbers in the luck jar is vastly greater than the range of numbers in the skill jar.”
“The process of social influence and cumulative advantage frequently generates a distribution that is best described by a power law.”
“The term power law comes from the fact that an exponent (or power) determines the slope of the line. One of the key features of distributions that follow a power law is that there are very few large values and lots of small values. As a result, the idea of an “average” has no meaning.”

Mauboussin’s discussion of power laws does not offer this specific example but the idea that the average is meaningless is also true of loan losses when you are trying to measure expected loss over a full loan loss cycle. What we tend to observe is lots of relatively small values when economic conditions are benign and a few very large losses when the cycle turns down, probably amplified by endogenous factors embedded in bank balance sheets or business models. This has interesting and important implications for the concept of Expected Loss which is a fundamental component of the advanced Internal Rating Based approach to bank capital adequacy measurement.

Mauboussin concludes with a list of ten suggestions for untangling and navigating the divide between luck and skill:

Understand where you are on the luck skill continuum
Assess sample size, significance and swans
Always consider a null hypothesis – is there some evidence that proves that my base belief is wrong
Think carefully about feedback and rewards; High quality feedback is key to high performance. Where skill is more important, then deliberate practice is essential to improving performance. Where luck plays a strong role, the focus must be on process
Make use of counterfactuals; To maintain an open mind about the future, it is very useful to keep an open mind about the past. History is a narrative of cause and effect but it is useful to reflect on how outcomes might have been different.
Develop aids to guide and improve your skill; On the luck side of the continuum, skill is still relevant but luck makes the outcomes more probabilistic. So the focus must be on good process – especially one that takes account of behavioural biases. In the middle of the spectrum, the procedural is combined with the novel. Checklists can be useful here – especially when decisions must be made under stress. Where skill matters, the key is deliberate practice and being open to feedback
Have a plan for strategic interactions. Where your opponent is more skilful or just stronger, then try to inject more luck into the interaction
Make reversion to the mean work for you; Understand why reversion to the mean happens, to what degree it happens, what exactly the mean is. Note that extreme events are unlikely to be repeated and most importantly, recognise that the rate of reversion to the mean relates to the coefficient of correlation
Develop useful statistics (i.e.stats that are persistent and predictive)
Know your limitations; we can do better at untangling skill and luck but also must recognise how much we don’t know. We must recognise that the realm may change such that old rules don’t apply and there are places where statistics don’t apply

All in all, I found Maubossin’s book very rewarding and can recommend it highly. Hopefully the above post does the book justice. I have also made some more detailed notes on the book here.

Tony