---
title: "Focus on Covered Bonds: Helaba Cover Pool Radar (#1)"
url: https://www.helaba.com/en/focus-covered-bonds-helaba-cover-pool-radar-1
type: dd_research
language: en
updated: 2026-09-28
keywords: Credit, Credit Special
---

# Focus on Covered Bonds: Helaba Cover Pool Radar (#1)

Focus on: Covered Bonds 2 September 2026 © Helaba | Research | 2 September 2026 1 of 6 Helaba Research Helaba Cover Pool Radar (#1) This publication marks the launch of a series of reports in which we filter through the vast number of issuance programs to identify those where certain characteristics of the cover pool have significantly changed compared to the previous coverage report. Know Your Risk European regulations require banks, insurance companies, and fund investors to inde- pendently assess the creditworthiness of their financial investments and not rely solely on external ratings. However, the practical implementation of these requirements is par- ticularly challenging for covered bonds. A sound assessment requires not only analyzing the issuer's creditworthiness but also understanding the quality and composition of the cover pool, as well as the regulatory frameworks consisting of supranational regulations, national laws and decrees, and individual contrac- tual frameworks. Since independent credit analyses of the respective issuer are already necessary due to invest- ments in unsecured debt instruments, the first part of these regulatory requirements is often the lesser problem. Analyzing regulatory frameworks can be challenging, but it remains manageable as country-specific rules apply broadly to many issuers and are seldom modified. Core Challenges in Cover Pool Monitoring Undoubtedly, national initiatives (e.g., National Transparency Templates \[NTT\] or §28 PfandBG) and international initiatives (Art. 129 (7) CRR in conjunction with ECBC HTT) for the homogeneous provision of coverage accounts are already of crucial importance. However, it must be borne in mind that there are currently around 170 active benchmark covered bond issuers. Many of them have more than one issuance program, which, depending on how they are counted, leads to nearly 250 currently active programs. Given the format of the reporting files, this means approximately 150,000 data fields – each quarter. In addition, information provided by rating agencies further in- creases the relevant volume of data. Moody’s Global Covered Bonds Comparison Tool Report, in particular, must be mentioned here. Ultimately, the challenge is twofold: managing the sheer volume of data while keeping a close eye on data quality. The Helaba Cover Pool Radar, or: " Data Wrangling Made Easy" By defining and calibrating alert levels, we are able to identify significant changes in the cover pool in a timely manner, thereby creating the foundation for more in-depth investigations. In many cases, significant changes in the cover pool will be explainable by routine day-to-day covered bond operations, for example through:  New additions to the cover pool: The total cover pool grows, overcollateralization increases, the average loan size increases due to the higher proportion of recent loans, the seasoning (average age) of the loans falls, the average remaining maturity lengthens, the LTV distribution shifts upward, etc.  New issuances of covered bonds: The outstanding volume of covered bonds increases, overcollateraliza- tion decreases. In the case of redemptions, the mechanism works in the opposite direction. In this inaugural publication, we provide examples to illustrate these standard movements. In line with the objec- tive of this series, however, future reports will only briefly reference routine changes as we pivot our focus toward the 'truffles' – those cover pools whose shifts deviate from the typical pattern. Florian Hillenbrand, CFA Senior Covered Bond Analyst T 069/91 32-40 79 Focus on: Covered Bonds – Cover Pool Radar © Helaba | Research | 2 September 2026 2 of 6 Generally, the structure of a cover pool should reflect an issuer's ordinary business activities in the relevant asset classes (mortgages, public-sector loans, ship loans, etc.). It would therefore be expected that once a covered bond program reaches a certain level of maturity, its core characteristics change very little. Key statistics such as aver- age loan size, average loan-to-value (LTV) ratio, average credit size, etc., should at best move slowly and steadily. Consequently, jumps in these statistics should be treated with greater attention. The same applies to the distribu- tion of LTVs, the regional or supra-regional breakdown of the cover pools, property types, performance statistics, etc. Ultimately, a warning light going off in our analysis is the beginning rather than the end of the monitoring pro- cess. If a change is classified as "significant," we will also closely examine other, non-significant changes and question the consistency of the developments. Finally, we consider it indispensable to leave room for "soft factors" as well. Consequently, we do not restrict our- selves solely to the data level, mechanically describing and interpreting the red lights generated by our database. Rather, in cases where pure data interpretation falls short, we provide the respective issuers with the opportunity to explain developments flagged as unusual. Key Metrics and Significance Thresholds Size of the cover pool: The most logical source of changes in cover pool characteristics is certainly a change in the volume of the available cover pool. It should be noted that an increase in the cover pool is a one-dimensional process, whereas a shrink- age can occur for two fundamentally different reasons: normal amortization or the manual release of cover assets. In our monitoring, we treat an increase in cover assets as a neutral event and a trigger for potential changes in cover pool characteristics. Normal amortization of the cover pool would fly under the radar of our threshold (±25%). A manual change - meaning an unusually high reduction in the cover pools - would be classified as a sig- nificant change. We also keep an eye on the ratio between primary coverage and substitute coverage. This is done, on the one hand, to generally monitor the standard 15% maximum criterion for substitute coverage. Primarily, however, it allows us to automatically detect shifts of ±7.5 percentage points. Overcollateralisation: We monitor both mandatory overcollateralization and voluntary overcollateralization. In principle, changes in mandatory overcollateralization could occur due to amendments in legislation; however, a change in the require- ments imposed by rating agencies is the more likely scenario. We consider both cases to be so serious that we de- fine any change as significant. Changes in voluntary overcollateralization are a natural process: they will increase when new assets are added to the pool in preparation for an issuance, and they will decrease once the issuance is completed. In phases without new issuances and without the addition of new cover assets, they will decline due to the natural amortization of the cover assets. We choose a threshold of 25 percentage points. However, we only consider these changes signif- icant or relevant if other characteristics change as well, indicating, for example, that cover assets have been ac- tively released. General Characteristics of the Cover Pool: As previously mentioned, cover assets should reflect the ordinary business activities in the issuer's business areas relevant to the coverage business. Once the cover pools have reached a certain level of maturity, substantial changes should rarely occur, which is why we monitor changes in relation to:  Origin of the cover pools  Breakdown of cover assets by residential vs. commercial vs. substitute coverage  Property types of residential and commercial cover assets  Average age (seasoning) and average remaining maturities of the assets  Average loan size Focus on: Covered Bonds – Cover Pool Radar © Helaba | Research | 2 September 2026 3 of 6 Loan-to-Value (LTV) Ratio: A major topic in the characterization of cover pools is the loan-to-value ratio of the loans. Fully aware of the vary- ing calculation methods, we include both the average value and the distribution of LTVs in the cover pool in our monitoring. Ceteris paribus, loans should amortize, and as a result, the average loan-to-value ratio should de- crease on the one hand, and the lower LTV brackets should tend to gain more weight on the other. This develop- ment should take place without major data jumps. Therefore, we define a change of 10 percentage points as sig- nificant for both the average values and the LTV brackets. When new loans are added to the pool - to an extent that we would consider significant - we verify consistency based on increasing LTV values. Non-Performing Loans (NPL) Ratio: We monitor the change in the share of non-performing loans divided into three brackets. Since non-performing loans generally do not play a major role, we apply a relatively sensitive seismograph here at 0.5 percentage points. We consider two aspects of our observation of non-performing loans worth mentioning:  Non-performing loans in a cover pool are per se a minor problem. Although the cash flows from the re- spective loans by definition fall short of expectations, the realized loss rate from non-performing loans is, on average, significantly lower than the haircut applied by the maximum loan-to-value ratio of 80% due to the collateralization.  Although we technically also monitor bracket 1, which includes delinquencies of less than two to three months, our focus is on the development of the higher brackets. Specific Moody’s Fields: Moody’s contribution to understanding the quality of cover pools can hardly be overestimated. The key metrics developed by Moody’s, such as the Collateral Score, Market Risk, and Collateral Risk, are simply too valuable. In this respect, we would deliberately compromise the quality of our monitoring if we were to forgo the use of these - albeit second-hand – metrics. The Collateral Score measures the extent of credit deterioration of the assets in the cover pool that aligns with the theoretically highest achievable rating in the respective jurisdiction. The higher the credit quality of the cover pool, the lower the collateral score. Moody’s Market Risk quantifies the losses in the cover pool following a covered bond anchor event that are caused by refinancing risks, currency mismatches, and interest rate differentials. The three metrics we mentioned appear as "significant" in our analysis starting from a change of 2.5 percentage points Significant Changes in Cover Pools Enough introduction. We have started the engine and take our first look at issuers where we have identified signif- icant changes. The programs are listed in alphabetical order.  ASN Bank N.V. − Mortgage Covered Bonds (Q2-2026 vs. Q1-2026) Changes: Overcollateralization Assessment: We are listing the change at ASN here to give ourselves and our readers a bit of a routine in this inaugural edition. In later publications, we will likely pay little attention to a drop in overcollateralization – even if it is by nearly 30 percentage points from 41% to 13% – in an otherwise stable scenario. The decline is ultimately a reflection of routine issuance activity. Overcollateralization also remains significantly above the 5% minimum and the 7% level required to maintain the current rating.  Banco Santander Public Sector (Q2-2026 vs. Q1-2026) Changes: Overcollateralization Assessment: By adding a further EUR 450m to the pool, the overcollateralization ratio for Santander's public covered bonds increased from 455% to 485%. Regional exposure shifted toward Catalonia (+6 pp from 12% to 18%) at the expense of the Madrid region (-7 pp from 19% to 12%). Focus on: Covered Bonds – Cover Pool Radar © Helaba | Research | 2 September 2026 4 of 6  Barclays Bank UK PLC − Mortgage Covered Bonds (Q2-2026 vs. Q1-2026) Changes: Cover Pool Term Assessment: Due to a relatively strong amortization of the cover pool from GBP 5.4bn to GBP 4.7bn, the overcollateralization ratio not only dropped from 69% to 47%, but the average remaining maturity of the cover pool also shifted from 13.8 years to 15.8 years. We view this change as neutral.  BBVA, S.A. − Mortgage Covered Bonds (Q2-2026 vs. Q1-2026) Changes: Overcollateralization Assessment: Overcollateralization decreased from 227% to 166% due to issuance activity. On June 5, BBVA issued a dual-tranche transaction with a total volume of EUR 3.5bn. The volume of outstanding covered bonds increased from EUR 15.5bn to EUR 19.8bn. Therefore, the decline is to be regarded as neutral as it is the result of routine issuance activity.  Compagnie de Financement Foncier − Covered Bonds (Q2-2026 vs. Q1-2026) Changes: Country Distribution Assessment: Changes in the country composition – particularly the inclusion of new countries or the re- moval of existing ones – trigger a warning light in our database. Issuers engaged in state-guaranteed export credit business that also include these in their cover pools often produce curious cases here. Specifically, according to the Q2 2026 figures, new export credits to debtors in Togo (approx. EUR 34m) and Indonesia (approx. EUR 134m) are in the cover pool – publicly guaranteed by a Bpifrance (Export Credit Agency). We view this development as neutral.  Equitable Bank (Q2-2026 vs. Q1-2026) Changes: Loans in Arrears; Overcollateralization; Rating Risk Assessment: Due to its core business model based on alternative financing (B-lending), Equitable Bank rec- ords higher shares of non-performing loans. It serves the self-employed, individuals with unconventional proof of income, or borrowers who do not meet the strict prime criteria of traditional major banks. We do not see this as a fundamental problem as long as the properties used as collateral are valued conservatively enough. However, we do view the current situation at Equitable Bank with some suspicion: for four quarters, the total volume of the cover pool has been falling, while the total volume of non-performing loans has been steadily rising. In recent quarters, the increase was mainly in bracket 1 (< 3 months). At the turn of the year (Q1 vs. Q4), the share of non-performing loans in bracket 2 (3-6 months) rose to 57 bp, while the share of non-performing loans in bracket 1 fell by more or less the same amount (55 bp). In Q2, the total volume of non-performing loans rose again by 28%, while the breakdown shifted back into bracket 1. Overall, we view three points with particular concern: • An increase in the absolute volume of non-performing loans year-on-year (+360%). • An increase in the share of non-performing loans year-on-year from 0.7% to 3.3%. • The simultaneous oscillation of loans from bracket 1 into bracket 2 and back again. Incidentally, Moody’s does not view this development as a negative – the Collateral Score and cover pool losses changed to an insignificant extent.  Eurocaja Rural – Cédulas Hipotecarias (Q2-2026 vs. Q1-2026) Changes: Asset Type Distribution Assessment: In the second quarter, Eurocaja Rural reported a decline in the share of commercial real estate financing by nearly 11 percentage points from 12.9% to 2.1%. Given the very small cover pool of only Focus on: Covered Bonds – Cover Pool Radar © Helaba | Research | 2 September 2026 5 of 6 around EUR 1.3bn, however, these seemingly large percentage changes represent movements only in the six-figure euro range. Given the currently static pool, the changes are to be regarded as neutral.  Lloyds Bank Plc (Q2-2026 vs. Q1-2026) Changes: Average Loan Size; Cover Pool Composition; Cover Pool Term Assessment: Already in the first quarter, Lloyds Bank Plc noticeably increased its cover pool from GBP 20bn to GBP 26bn. In the second quarter, another GBP 6bn was added. Naturally, this is accompanied by some structural changes. The associated modifications were unspectacular. For example, the average loan size increased in two steps from GBP 103k to GBP 132k. The composition of the cover pool, consisting of over 98% primary coverage and just under 2% substitute coverage, remained unchanged. Overall, the changes are the result of customary covered bond business and are therefore to be seen as neutral.  Nordea Mortgage Bank Plc − Mortgage Covered Bonds (Q2-2026 vs. Q1-2026) Changes: Overcollateralization Assessment: Due to a relatively strong amortization of the cover pool from EUR 7bn to EUR 5.3bn, the over- collateralization ratio not only fell from 47% to 14%. The decline is plausible, as Nordea had already re- ported a high volume of loans in the 0-20% LTV segment in the previous quarter. We view this change as neutral.  Raiffeisen Bank International AG − Mortgage Covered Bonds (Q2-2026 vs. Q1-2026) Changes: Country Distribution Assessment: In its mainly commercial cover pool, RBI had cover assets from Austria, Germany, Poland, the Czech Republic, Romania, Slovakia, Bulgaria, and the Netherlands in its last reporting. In the latest reporting, Slovenia was added, but it accounts for only about 1% of the cover pool.  UniCredit Bank GmbH − Public-Sector Covered Bonds (Q2-2026 vs. Q1-2026) Changes: Country Distribution Assessment: In its public cover pool, UniCredit Bank had cover assets from Germany, the United Kingdom, France, Austria, Switzerland, and Denmark in its last reporting. In the latest reporting, a minimal position in Italy was added (EUR 4.5m).  UniCredit S.p.A. – Mortgage Covered Bonds Pool #2 (Q2-2026 vs. Q1-2026) Changes: Overcollateralization Assessment: Overcollateralization fell from 105% to 47% due to issuance activity. The volume of outstand- ing covered bonds increased from EUR 13.25bn to EUR 19.25bn. UniCredit issued EUR 4.5bn in retained for- mat and EUR 2.5bn in placed form – EUR 1bn retained matured during the relevant period. Therefore, the decline is to be regarded as neutral as it is the result of routine issuance activity. Focus on: Covered Bonds – Cover Pool Radar © Helaba | Research | 2 September 2026 6 of 6 Publisher and editor Helaba Research Editor: Dr Stefan Mitropoulos Capital Market Research Publisher: Dr Gertrud Rosa Traud Chief Economist/Head of Research Neue Mainzer Str. 52-58 60311 Frankfurt T +49 69 / 91 32 – 20 24 Internet: www.helaba.com Disclaimer This publication has been prepared with the utmost care. However, it contains only non- binding analyses and forecasts of current and future market conditions. The infor- mation is based on sources that we consider reliable, but we cannot guarantee its accu- racy, completeness or timeliness. All infor- mation contained in this publication is for informational purposes only. It should not be construed as an offer or recommendation for investment decisions. Sign in for our newsletter here: https://news.helaba.de/ research/

Cover Pool Radar #1 is the first in a series of publications identifying and analysing significant changes in covered bond cover pools. It is published quarterly and is based on calculations for approx. 250 covered bond issuance programmes. This first issue identifies changes at ASN Bank, Santander, Barclays, BBVA, CFF, Equitable Bank, Eurocaja, Lloyds, Nordea, RAI and Unicredit.