Nov 162018

Luis de Guindos, Vice-President of the ECB spoke at  the Annual General Meeting of the Foreign Bankers’ Association, which was held in Amsterdam the 15 November 2018. The focus was the state of the euro area banking sector and its current challenges.

 The financial health of euro area banks has improved markedly since the beginning of the crisis. The aggregate core capital (Common Equity Tier 1) ratio of euro area banks stood at around 14% at the end of the second quarter of 2018, the double of what is was in 2007. Regulatory liquidity ratios are at solid levels, with an aggregate liquidity coverage ratio of 141%. European banks are also making progress in fulfilling the minimum requirements for own funds and eligible liabilities (MREL).

One indicator of this is that the volume of Additional Tier 1 bonds and Tier 2 instruments issued by euro area banks and held by investors in the euro area increased by two-thirds between 2013 and 2017. Finally, banks are also making progress in repairing their balance sheets – the aggregate non-performing loan (NPL) ratio has nearly halved from its 2013 peak of around 8%, to its current level of 4.4%.

The recently published results of the 2018 stress tests reflect exactly this. On average, core capital of euro area banks after stress stood at 9.9%, up from 8.8% in the same exercise two years ago. Underlying the results is the strong build-up of capital buffers in recent years resulting in a better condition at the starting point of the exercise (end 2017).

While euro area banks are clearly better capitalised and more resilient, this exercise should not hide the fact that areas of vulnerability remain. In particular, banks are still struggling to achieve sustainable profitability. Admittedly, headline profitability figures show that the sector seems to be improving rapidly – the average return on equity for euro area banks increased from 3.4% in 2016 to 6.9% in the second quarter of 2018. However, more careful analysis reveals that this improvement is mainly due to a reduction in the cost of credit risk. This results, in part, from a cyclical upswing that has stemmed the flow of new NPLs and led to provisioning costs falling to post-crisis lows. At the same time, operating profits have remained modest overall and the average cost-to-income ratio flat at 66% over the same period, reflecting some cyclical and structural challenges.

On the cyclical front, banks are finding it hard to increase their revenue in the low interest rate environment. Although credit growth has increased somewhat with the improving economic conditions, it is not yet sufficient to compensate for the low interest rate margins. The continued economic recovery should, however, reduce the negative impact of cyclical factors over time, as banks’ balance sheets adjust.

But most importantly, a number of structural challenges continue to dampen bank profitability. These factors vary across countries and banks and include incomplete business model adjustments, cost inefficiencies and excess capacity. The stock of NPLs also remains high at some banks.

On the positive side, the growing economy and the ever more resilient banking sector are supporting financial stability. This is partly why the financial system has recently proved resilient to volatility, and why contagion across countries and markets has remained limited. But these developments need to be put into the context of the continuing search for yield in the markets, rising trade protectionism, and political and policy uncertainty, which increase risks to financial stability.

Taking these factors together, the euro area financial sector is faced with risks, which can be classified in three categories. First, the factors that are related to the past, in other words, the legacy of the crisis, include a still-significant private and public debt overhang. Second, the current expansion of the US is now significantly longer than historical norms and the second longest in US modern history. Third, in Europe, debt sustainability concerns have risen both in the public and private sector. As regards public finances, Italy is the most prominent case at the moment in light of the overall debt level and the political tensions around the Italian government’s budget plans. Contagion to other European sovereigns has however been limited.

In sum, there is no reason to be complacent about financial stability risks in the banking sector, which could materialise in a number of ways. At the current opportune moment with 22 consecutive quarters of economic growth behind us, minds should be concentrated on tackling structural impediments to sustained profitability in the euro area banking sector.

Banks need to adjust their business models to further diversify their income and reduce cost inefficiencies. They should also prepare for the challenges of digitalization and competition from technology companies. And it is of the utmost importance that the large stocks of NPLs that still remain in some banks are reduced.

ECB: Euro area banking sector – current challenges (complete speech, HTML)

Nov 162018

The Financial Stability board (FSB) welcomes the publication today of the International Association of Insurance Supervisors (IAIS) consultation document on a proposed holistic framework for the assessment and mitigation of systemic risk in the insurance sector. It sets out the Activities-Based Approach for sector-wide risk monitoring and management, as a key component of the framework, and tools for dealing with the build-up of risk within individual insurers. The FSB notes that a new holistic framework, appropriately implemented, would provide an enhanced basis for mitigating systemic risk in the insurance sector.

The IAIS will further refine the proposed holistic framework, taking account of the public consultation feedback, including feedback on the scope of application of the supervisory measures to ensure proportional application. The specific measures to be incorporated in the IAIS supervisory material (Insurance Core Principles and Common Framework for the Supervision of Internationally Active Insurance Groups, ComFrame) will then be exposed for further public consultation. The IAIS will finalise the holistic framework in 2019, for implementation in 2020.

In light of the progress with the proposed holistic framework, the FSB, in consultation with the IAIS and national authorities, has decided not to engage in an identification of global systemically important insurers (G-SIIs) in 2018. The FSB will assess the IAIS’s recommendation to suspend G-SII identification from 2020 once the holistic framework is finalised in November 2019. In November 2022, the FSB will, based on the initial years of implementation of the holistic framework, review the need to either discontinue or re-establish an annual identification of G-SIIs by the FSB in consultation with the IAIS and national authorities.

In the period until the holistic framework is implemented, the relevant group-wide supervisors have committed to continue applying existing enhanced supervisory policy measures as described in the IAIS consultative document on the holistic framework published today, as applicable.

The FSB will receive from the IAIS an annual update of the IAIS assessment of systemic risk in the global insurance sector and of the supervisory response. The IAIS will continue its annual global monitoring exercise, including the annual data collection from individual insurers building on the current G-SII data collection template and instructions and implement additional data collection from supervisors as necessary to support an assessment of sector-wide trends with regard to specific activities and exposures.


IAIS: proposed holistic framework for the assessment and mitigation of systemic risk in the insurance sector and implications for the identification of G-SIIs and for G-SII policy measures

Nov 162018

The Board of the International Organization of Securities Commissions (IOSCO) is requesting feedback on a proposed framework to help measure leverage used by investment funds which in some circumstances could pose financial stability risks.

The proposed framework, outlined in IOSCO Report: Leverage, comprises a two-step process aimed at achieving a meaningful and consistent assessment of global leverage. The first step indicates how regulators could exclude from consideration funds that are unlikely to create stability risks to the financial system while filtering and selecting a subset of other funds for further analysis.

The second step calls for regulators to conduct a risk-based analysis of the subset of investment funds identified in the first step. The consultation paper principally focuses on the first step, although it also invites feedback on both the second step and the design of the two-step approach.

IOSCO does not prescribe a particular set of metrics or other analytical tools. Instead, each jurisdiction is expected to determine which is the most appropriate risk assessment for it to adopt, given that some risk-based measures are not appropriate for all funds.

The two-step framework seeks an appropriate balance between achieving precise leverage measures and devising simple, robust metrics that can be applied in a consistent manner to a wide range of funds in different jurisdictions. It also addresses synthetic leverage, by including exposure created by derivatives; considers different approaches to analyzing netting and hedging and the directionality of positions; and includes approaches that limit model risk.

The consultation paper responds to a request made in the Financial Stability Board ́s 2017 report Policy Recommendations to Address Structural Vulnerabilities from Asset Management Activities, which provides policy recommendations to address risks to global financial stability arising from potential structural vulnerabilities that may result from asset management activities.

Recommendation 10 in the FSB report asks IOSCO to “identify and or develop consistent measures of leverage in funds to facilitate more meaningful monitoring of leverage for financial stability purposes and help enable direct comparisons across funds and at a global level. IOSCO should also consider identifying and/or developing more risk-based measure(s) to complement the initial measures with a view to enhance authorities’ understanding and monitoring of risks that leverage in funds may create. In both cases, IOSCO should consider appropriate netting and hedging assumptions and where relevant build on existing measures.”

IOSCO: feedback on proposed framework for assessing leverage in investment funds (PDF)

Nov 162018

A key element of the Basel Committee’s post-crisis Basel III reforms is the introduction of a leverage ratio requirement. The leverage ratio complements the risk-based capital requirements by providing a safeguard against unsustainable levels of leverage and by mitigating gaming and model risk across both internal models and standardised risk measurement approaches. By design, the leverage ratio does not differentiate risk across different asset classes.

This consultative document seeks the views of stakeholders on whether a targeted and limited revision of the leverage ratio’s treatment of client cleared derivatives may be warranted, based on the findings of the Committee’s review of the impact of the leverage ratio on banks’ provision of client clearing services and in consideration of key policy objectives of G20 Leaders both to prevent excessive leverage and improve the quality and quantity of capital in the banking system and to promote central clearing of standardised derivatives contracts.

Pending feedback provided in response to this consultation, the range of treatments that the Committee may consider include:

  • no change to the current treatment;
  • an amendment to the treatment of client cleared derivatives to allow cash and non-cash initial margin received from a client to offset the potential future exposure of client cleared derivatives; and
  • alignment of  the treatment of client cleared derivatives with the standardised approach for measuring counterparty credit risk exposures. This would have the effect of allowing both cash and non-cash forms of initial margin and variation margin received from a client to offset the replacement cost and potential future exposure amounts of client cleared derivatives.

The Committee also welcomes feedback on the merits of introducing a requirement for initial margin to be segregated in order for any amended treatment to apply. It also seeks views on forward-looking behavioural dynamics of the client clearing industry that might result from any amended treatment.

Basel Committee: Leverage ratio treatment of client cleared derivatives (PDF)

Nov 152018

Upcoming challenges and new trends for financial institutions

Credit risk management in the banking industry has changed in recent years, mainly as a consequence of the stricter regulations following the financial crisis; further changes, whose magnitude and effects are mostly not predictable, will have an impact in the next decade on its role, scope and organization.

The definition, development and implementation of the interventions needed to keep pace with these changes will require important investments by banks in terms of adoption of new technologies, redefinition of processes and organization, and will imply the need to overcome several challenges. These investments are expected to be compensated by economic returns in the medium-long run, through the possibility to re-allocate staff to more valuable activities, to provide managers with automatic and more comprehensive flows of information fundamental for their strategic decisions and to obtain capital savings thanks to more predictable internal models.

The main trends currently affecting the risk management function, deemed to have an even more important impact in the near future, are related to regulatory topics, digitalization and practices optimization, business development and new risks prevention.

Evolution in the regulatory framework

Financial institutions have recently been facing more stringent regulation therefore significantly expanding their risk management functions. Among the latest regulatory developments affecting credit risk, in December 2017 the legal provisions revising and integrating the Basel III framework, frequently referred to as ‘Basel IV’, have been launched by the Basel Committee. The new dispositions mainly aim to further reduce the variability in the measurement of the RWAs among banks with different dimensions, operating according to diverse regulatory frameworks and business models.

Besides ‘Basel IV’ reforms, in November 2017 the EBA published specific guidelines focused on modelling techniques for the estimation of IRB parameters for defaulted and non-defaulted exposures.

Additionally, it is worth mentioning the process currently being structured by the ECB in order to address the implementation by banks of the new definition of default. The new regulatory framework aims to harmonize the criteria of identification of the default status at European level, therefore minimizing the variability of the RWAs.

Finally, the digitalization process of banking processes currently underway will increase the new regulation issued for the purposes of governing and control this new fields.

Digitalization and practices optimization

Banks business and operational models have evolved in the last decade due to the process of digitalization; it implies the transformation of existing processes by leveraging on the application of digital technologies and data in order to create new value and opportunities. Digitalization represents for the banking industry and risk management the most effective way to reduce costs in a context of persistent margin decline, which is a direct consequence of:

  • competition of aggressive FinTechs and banks early-adopting new technologies, with low-cost business models and automated processes, enabling them to provide customers with different kind of offerings;
  • low interest rates condition affecting the whole industry;
  • increasing regulation, which caused the growth of risk management functions in terms of staff and costs in the last years.

Among tools useful for the risk management function to successfully compete in this evolving framework, advanced analytics and big data systems have already started to prove their effectiveness:

  • advanced analytics: new technological and statistical tools (e.g. machine learning) capable to identify complex patterns in richer datasets, enabling the estimation of more accurate and predictive internal models and the reduction of credit losses;
  • big data systems: data processing software enabling the analysis of greater amounts of structured and unstructured data in a faster way, made possible by the increased computation power of modern technologies.

 Business development

Technological innovation led customers to increasingly demand digital banking services, to be accessible at anytime from any devices, in order to support their everyday decisions. Social media and e-commerce have acquainted clients by means of personalization and brisk fulfilment of their requests. Consequently, it is fundamental for financial institutions to prioritize their digitalization efforts in order to be abreast of the rapid developments in this area. The challenge for banks over the coming years is to be present in key moments of customers’ life, anticipating and satisfying their financial needs while foreseeing variations in their purchasing preferences.

With this aim, advanced statistical algorithms and artificial intelligence systems applied to risk management models and processes will play a fundamental role in meeting customers’ expectations and facilitating business development, anticipating clients’ needs and providing customized solutions. Consequently, the risk function will be called upon to collaborate jointly with each business in order to respond to customers’ demands while limiting risks mainly related to the complexity of supporting processes.

 New risks prevention

Beside regulatory risk types such as credit, liquidity, market and operational risk, specific non-financial risks are emerging as result of structural changes concerning financial institutions, including models’ greater complexity, the introduction of digitalization and automation in many processes, as well as the growth of interconnectedness among market players. In this light, new regulations are progressively addressing additional risk types, which are not properly new, but due to their growing importance and their impact on the financial system, deserve accurate management.

Among others, models’ increasing complexity stemming from the adoption of advanced analytics techniques entails the so-called model risk, occurring when a model performs inadequately. It usually derives from underlying data quality or data management issues resulting in misleading outcomes and operational losses; or due to the incorrect model estimation and execution intended as technologies and processes provided to end users to effectively conduct daily operations. To this extent, the optimization of model risk management is becoming a core part of risk activities.

 Regulatory expectations on the role of FinTechs

In light of the cross-sectoral transformation of the financial industry, the main Supervisory Authorities are carrying out exercises in order to gather information about the range of financial services provided and innovations applied by FinTechs. The main purpose of the Supervisors is to define the related regulatory treatment and the main areas of intervention, focusing on the following aspects: (1) accessibility of financial services to customers, (2) bringing down operational costs and increasing the efficiency of the financial services sector, (3) enhancing competition in the Single Market by lowering barriers to entry, and (4) balancing greater data sharing and transparency with data security and protection needs.

The main results gathered so far made it possible to identify follow-up initiatives and a roadmap at European level for the following years. In particular, regulators’ expectations are focused on the promotion of technological developments in order to allow opportunities in the FinTech perimeter, while it is of primary importance to ensure consumer protection, as well as integrity of financial markets through sector-specific regulation to be issued.

 Impact on credit risk management

In light of the latest evolutions in the regulatory framework, banks are facing, at the same time, an increase in compliance costs – financial institutions will be required to plan an impactful revision of their credit risk-measurement models, as well as of the related internal processes and IT systems – and a reduction in returns due to the raise in capital and liquidity requirements.

On the other side, digitalization represents the opportunity for the banking industry to reduce costs through the use of advanced data analytics and big data systems, enabling the provision of more accurate and performing internal models, leveraging on the automation in order to speed up their development timings and simultaneously reduce the need for manual inputs. To this end, the adoption of new technologies will certainly require the involvement of professional resources characterized by widened analytical-oriented skills.

Additionally, advanced statistical algorithms applied to credit risk management models and processes will play a fundamental role in meeting customers’ expectations and providing customized solutions, likely facilitating business development and making banks more competitive on the market, where FinTechs have become a player of interest for clients. Digitalization will facilitate banks in the processes implying the use of internal models, such as – for instance – credit granting, management reporting and pricing policies. To this purpose, banks will be required to reshape their credit risk management functions, which will be called upon working alongside with several structures, such as business, operations and finance departments; this collaboration will in turn spread and enhance credit risk culture among other strategic areas.

The effectiveness and timely response of banks to the above mentioned trends, and their ability to adapt business models and processes to the evolving environment, will determine their future competitive success. In this context, credit risk management will have the chance to play an important role as one of the leading functions in banks’ strategic change.


Antonio Arfè – Partner Deloitte Consulting

Francesco Zeigner – Partner Deloitte Consulting

Vincenzo Maria Cosenza – Senior Manager Deloitte Consulting

Nov 112018

Lo scorso 2 novembre l’EBA ha diffuso i risultati della nuova tornata di stress test condotta durante il 2018 a partire dai dati di bilancio relativi alla fine del 2017. Il test ha riguardato 48 banche operanti in 15 paesi europei ed ha fornito indicazioni sui coefficienti (attesi) di patrimonializzazione nello scenario base e in quello avverso per un orizzonte temporale che arriva al 2020. Per l’Italia sono state considerate 4 banche: Unicredit, Intesa-Sanpaolo, Ubi e Banco BPM.

Come per gli stress test condotti nel 2016 l’intento dell’EBA non è quello di decretare in modo esplicito gli istituti che falliscono il test quanto quello di utilizzare le informazioni per il Supervisory Review and Evaluation Process (SREP) al fine di definire i requisiti aggiuntivi di capitale richiesti alle singole banche per tener conto del loro grado di rischiosità.

L’assenza di una lista di “vincitori e vinti” ha permesso a molte banche di dichiararsi tra quelle che hanno superato meglio il test, un po’ sulla falsa riga di Donald Trump che ha sbandierato una vittoria al Senato nelle elezioni di midterm omettendo l’amissione della sconfitta alla Camera dei rappresentanti.

I dati presentati nel report dell’EBA si prestano infatti a diverse interpretazioni a seconda dell’indicatore di patrimonializzazione considerato e della grandezza osservata. Prendendo a riferimento il Common Equity Tier1 (CET1) ratio fully loaded (ovvero il ratio che incorpora gli effetti a regime della piena implementazione della Capital Requirements Regulation, della Capital Requirements Directive IV e del principio contabile IFRS 9) e il leverage ratio, sempre fully loaded, si ha una diversa fotografia. Il primo indicatore (CET1 raio) è influenzato dal modello di business della banca, dal livello di rischio degli assets e dall’utilizzo dei modelli interni per la valutazione del rischio. Il secondo indicatore (leverage ratio), avendo al denominatore una grandezza non ponderata per il rischio, ha il pregio di non risentire degli effetti della potenziale manipolazione delle attività ponderate per il rischio (Barucci e Milani, 2018).


Grafico 1. Effetto dello scenario di stress al 2020

Fonte: elaborazioni BEM Research su dati EBA.


Nel grafico 1 è riportato l’effetto al 2020 sui due coefficienti di patrimonializzazione dello scenario di stress in termini di basis points. Le 48 banche considerate sono state aggregate in base al paese di origine. Dal grafico emerge che sulla base del CET1 ratio il Regno Unito e la Germania sono i due sistemi che subirebbero i maggiori contraccolpi nello scenario avverso. In media le banche inglesi vedrebbero ridursi il loro CET1 ratio di oltre 600 punti base (bp), quelle tedesche di circa 560. Pesante sarebbe anche l’effetto sulle banche irlandesi, finlandesi e danesi (circa 500 bp). Le banche italiane, invece, avrebbero un impatto di circa 350 bp, che si colloca leggermente al di sotto della media complessiva (370 bp).

Sulla base di queste evidenze alcuni giornali italiani hanno titolato sottolineando il fatto che le banche italiane siano tra le “vincitrici” dell’ultima tornata di stress test. Questa interpretazione racconta solo una parte della storia. Basta guardare al dato circa l’impatto dello scenario avverso sul leverage ratio per trovare una fotografia in parte diversa. Sulla base di questo indicatore sono le banche irlandesi quelle più colpite (200 bp), seguite dalle finlandesi (150 bp), dalle austriache (140 bp) e dalle inglesi (130 bp). In questo caso le banche italiane, con un impatto negativo medio di 115 bp, si posizionano al di sopra della media europea (90 bp), ad un livello non molto distante da quanto osservato per gli istituti tedeschi. Ci possiamo rasserenare per il fatto che il primo pilastro della regolamentazione si basa pur sempre sul CET ratio ma il dato non può essere trascurato.

Ancor meno rassicurante è il dato che emerge osservando il livello medio di CET1 ratio e di leverage ratio ottenuti negli scenari di stress (grafico 2). In questo caso le banche italiane sono in media tra quelle che evidenziano, per entrambi gli indicatori, coefficienti tra i più bassi in Europa.


Grafico 2. Coefficienti di patrimonializzazione al 2020 nello scenario stressato

Fonte: elaborazioni BEM Research su dati EBA.


Guardando al dettaglio per singola banca si rileva che sono in particolare Banco BPM e UBI ad evidenziare livelli contenuti sia sul CET1 ratio sia sul leverage ratio (grafici 3 e 4).

Leggendo assieme il grafico 1 e il grafico 2 possiamo dedurre che le banche italiane sono sì meno esposte delle altre europee ai rischi macroeconomici ma sono ancora sottocapitalizzate: quindi una variazione non elevata in termini di capital ratio le porta ad un basso coefficiente di patrimonializzazione. A ben guardare è la Gran Bretagna ad essere messa male sotto ambedue i profili.

Da notare in particolare come il leverage ratio, nello scenario stressato, scenderebbe al di sotto della soglia del 3%, prevista da Basilea 3, in diverse realtà bancarie europee, tra cui anche Deutsche Bank e Banco BPM. Solo 21 tra le 48 banche considerate avrebbero invece nel 2020 un leverage ratio post stress test al di sopra del 5%, la soglia imposta dalla Federal Reserve e dal Federal Deposit Insurance Corporation (FDIC) alle banche operanti negli Stati Uniti.


Grafico 3. Fully loaded CET1 ratio al 2020 nello scenario stressato e scarti rispetto alla baseline

Fonte: elaborazioni BEM Research su dati EBA.

Grafico 4. Fully loaded leverage ratio al 2020 nello scenario stressato e scarti rispetto alla baseline

Fonte: elaborazioni BEM Research su dati EBA.

In definitiva, i risultati degli stress test per il 2018 non sembrano essere così rassicuranti come qualche commentatore ha evidenziato. Oltretutto occorre rilevare che, come spesso è accaduto in passato le ipotesi adottate dall’EBA per disegnare gli scenari degli stress sono state superate dalla realtà in due direzioni. Al riguardo occorre notare che per l’Italia lo scenario avverso ha ipotizzato un calo consistente del Pil (7 punti percentuali cumulati fino al 2020) ma con uno spread BTP-Bund pari a 250 bp (Milani, 2018), quando invece nel periodo recente ha toccato quota 340 bp oscillando su valori intorno ai 300 bp.

Le notizie ‘‘positive’’ vengono soprattutto dal fatto che la performance ‘‘negativa’’ in termini di variazione del capital ratio delle banche inglesi, tedesche e dei paesi nordici è dovuta al fatto che finalmente gli stress tests sono in grado di ‘‘stressare’’ gli asset di livello II e III, che sono presenti soprattutto nelle banche dei paesi del nord Europa. Si tratta di titoli complessi, difficili da valutare che sono state all’origine della crisi finanziaria ed erano stati ignorati dall’EBA nelle analisi precedenti, si veda al riguardo Barucci, Baviera e Milani (2018). D’altro canto, la pulizia dei bilanci delle banche italiane dei NPL ha sicuramente avuto un effetto positivo nel renderle meno rischiose.


  • Barucci E., R. Baviera, C. Milani, The Comprehensive Assessment: What lessons can be learned?,  The European Journal of Finance, 2018.
  • Barucci E., C. Milani, Do European banks manipulate risk weights?, International Review of Financial Analysis, Volume 59, pp. 47-57, North-Holland, 2018.
  • Milani C., Le principali caratteristiche degli stress test 2018, del 12 febbraio 2018.
Nov 102018

Mr Hyun Song Shin, Economic Adviser and Head of Research of the Bank for International Settlement (BIS), examines the liquidity properties of decentralised payment systems in an economic model of payments, in which the cost of credit to finance payments enters explicitly.

Payment systems built around distributed ledger technology (DLT) operate by maintaining identical copies of the history of payments among the participant nodes in the payment system. Cryptocurrencies are perhaps the best-known example of the application of DLT, but the applicability of the technology is much broader. Payment systems based on DLT are compatible with oversight by the central bank, and several central banks have conducted successful trials of interbank payments. In these trials, payment system participants transfer digital tokens that are redeemable at the central bank and use DLT to transfer them to other system participants. Decentralised consensus is achieved through agreement of a supermajority of the participants (typically 75-80%) who collectively validate payments.

Nevertheless, the technology by itself does not overcome the credit needs of the payment system to maintain settlement liquidity. In conventional real-time gross settlement (RTGS) payment systems, the value of daily payments can be over 100 times the deposit balance maintained by the system participant at the central bank. As such, incoming payments are recycled into outgoing payments, and credit provided by the central bank supplements private credit from outside the payment system for the smooth functioning of the system as a whole.

In a two-bank example, we illustrate the conceptual distinction between consensus as distributed knowledge and consensus strong enough to sustain a cooperative outcome. In this example, when the cost of credit exceeds a modest threshold, no amount of exchange of messages can elicit the coordination of payments between the two banks. The example focuses attention on the coordination motives of system participants. The cost of credit turns out to be a key determinant of the equilibrium outcome of the game.

We then proceed to examine a general N-bank game and cast the payment problem as a public good contribution game between N banks in a large-value payment system. The public good has two aspects. The first aspect of the public good is the availability of a clean, reconciled ledger that commands agreement from system participants. This part is where the technological innovation can contribute most.

The second aspect of the public good is the provision of credit to clients which allows high volume of outgoing payments that sustains the coordination outcome with high flows. We solve for the unique, dominance-solvable equilibrium using global game techniques and provide an exact characterisation of the states of the world at which the coordination outcome is feasible.

The solution shows that successful coordination is possible in a decentralised setting, but only within a narrow range of fundamentals. The solution is highly sensitive to the cost of credit, and the decentralised equilibrium outcome often fails to reproduce the high-volume payment outcomes that are more normal with central bank balance sheet backing.

Payment systems built around distributed ledger technology (DLT) operate by maintaining identical copies of the history of payments among the participant nodes in the payment system. Cryptocurrencies are perhaps the best-known example of the application of DLT, but the applicability of the technology is much broader. Payment systems based on DLT are compatible with oversight by the central bank, and several central banks have conducted successful trials of interbank payments. In these trials, payment system participants transfer digital tokens that are redeemable at the central bank and use DLT to transfer them to other system participants. Decentralised consensus is achieved through agreement of a supermajority of the participants (typically 75-80%) who collectively validate payments.

Nevertheless, the technology by itself does not overcome the credit needs of the payment system to maintain settlement liquidity. In conventional real-time gross settlement (RTGS) payment systems, the value of daily payments can be over 100 times the deposit balance maintained by the system participant at the central bank. As such, incoming payments are recycled into outgoing payments, and credit provided by the central bank supplements private credit from outside the payment system for the smooth functioning of the system as a whole.

Distributed ledger technology and large value payments: a global game approach (PDF)

Nov 102018

The European Securities and Markets Authority (ESMA) issued a Public Statement in order to raise market participants’ awareness on the readiness of credit rating agencies (CRAs) and trade repositories (TRs) for the possibility of no agreement being reached in the context of the United Kingdom (UK) withdrawing from the European Union (EU).

As there is no assurance that a transition period will be agreed, entities using services provided by CRAs and TRs need to consider the scenario where a no-deal Brexit would take place on 30 March 2019.

Derivatives subject to the reporting obligation under EMIR1 must be reported to a registered EU-established TR or a recognised third-country TR2. Similarly, CRAs need to have a legal entity registered in the EU and supervised by ESMA, in order for their ratings to be used for regulatory purposes in the EU. In a no-deal Brexit scenario, TRs and CRAs established in the UK will lose their EU registration as of the UK’s withdrawal date.

UK-based CRAs and TRs currently registered with ESMA have implemented contingency plans in preparation of a no-deal Brexit scenario. ESMA has noted significant steps forward by both industry sectors in terms of preparedness, however, some actions still need to be completed.

ESMA is engaging on a continuous basis with the relevant supervised entities to ensure that the agreed Brexit contingency plans are fully executed by March 2019 in case of no- deal Brexit, including the finalisation of pending applications for registration. ESMA is currently assessing a number of CRAs and TRs applications, submitted as part of the firms’ Brexit contingency plans.

ESMA emphasises that a positive decision on a registration application ultimately depends on the completeness and the quality of the application file and on the applicant’s compliance with the relevant regulations.

EU counterparties and CCPs must report details of derivative contracts to a registered EU- established TR or a recognised third-country TR. All counterparties must ensure that this requirement continues to be fulfilled. ESMA invites market participants to contact their TR to verify whether continuity of service will be ensured after Brexit.

In general, ESMA emphasises the importance for market participants to monitor closely the public disclosures made by CRAs and TRs in the context of Brexit.


ESMA: Contingency plans of Credit Rating Agencies and Trade Repositories in the context of the United Kingdom withdrawing from the European Union (PDF)


Nov 102018

The Financial Stability Board (FSB) Regional Consultative Group (RCG) for the Middle East and North Africa (MENA) met in Istanbul today at a meeting hosted by the Central Bank of the Republic of Turkey.

Members of the FSB RCG MENA received an update on the FSB’s work programme and deliverables for the G20 Leaders’ Summit later this month in Buenos Aires, including evaluations of the effects of the reforms on infrastructure finance and on incentives to centrally clear over-the-counter derivatives, and a progress report on the FSB action plan to assess and address the decline in correspondent banking relationships. The FSB’s work in 2019 and beyond will focus on (i) finalising and operationalising post-crisis reforms; (ii) monitoring the implementation and evaluating the effects of post-crisis reforms; and (iii) addressing new and emerging vulnerabilities in the financial system.

Turning to vulnerabilities and regional financial stability issues, meeting participants noted that, while global growth remains strong, the recovery is less balanced and financial conditions could tighten, particularly in emerging markets. For the MENA region specifically, members expect economic growth in oil exporting countries to rebound, while importing countries may remain challenged. The region’s banking sector remains generally sound with improved liquidity positions, but non-performing loan levels are high in some countries. Credit growth is modest and could be further impacted by rising interest rates.

Members next considered financing to small and medium-sized enterprises (SMEs) and their role in the region’s economic development. Although SMEs traditionally present more credit risk than large corporates, the level of risk in SMEs has declined in recent years, while credit and business conditions have improved. These positive developments, however, have not always translated into greater access to financing. Members discussed both financial and non-financial impediments to SME lending in the region. The FSB is conducting an evaluation of the effects of the G20 financial regulatory reforms on SME financing, and will publish a consultative paper by mid-2019 and a final report by end-2019.

The group discussed how technology can be leveraged to achieve supervisory and regulatory objectives (SupTech). They considered the potential uses of SupTech and how to facilitate innovation while at the same time maintaining effective oversight. They also exchanged views on how it could change supervision in the future and some of the challenges that technology might raise for financial sector supervisors, such as the skill sets that they will need, oversight of decentralised systems and distributed ledgers, and data protection. Members also discussed the use of technology such as big data and machine learning to help financial institutions comply with regulatory requirements (RegTech).

Finally, members discussed implementation of the Basel Committee’s net stable funding ratio (NSFR) and its effects on banks in the region. They reviewed the objectives and key elements of the NSFR, as well as implementation challenges such as those faced by banks when attempting to adjust their information systems to meet and report on the new requirements. Several jurisdictions in the region have either issued final rules for the implementation of the NSFR or are in the process of doing so.


FSB: RCG on MENA NOV 18 – Full text (PDF)

Nov 102018

L’iniziativa di “Il termometro dei mercati finanziari” vuole presentare un indicatore settimanale sul grado di turbolenza/tensione dei mercati finanziari, con particolare attenzione all’Italia.

Significato degli indicatori

  • Rendimento borsa italiana: rendimento settimanale dell’indice della borsa italiana FTSEMIB;
  • Volatilità implicita borsa italiana: volatilità implicita calcolata considerando le opzioni at-the-money sul FTSEMIB a 3 mesi;
  • Future borsa italiana: valore del future sul FTSEMIB;
  • CDS principali banche 10Ysub: CDS medio delle obbligazioni subordinate a 10 anni delle principali banche italiane (Unicredit, Intesa San Paolo, MPS, Banco BPM);
  • Tasso di interesse ITA 2Y: tasso di interesse costruito sulla curva dei BTP con scadenza a due anni;
  • Spread ITA 10Y/2Y : differenza del tasso di interesse dei BTP a 10 anni e a 2 anni;
  • Rendimento borsa europea: rendimento settimanale dell’indice delle borse europee Eurostoxx;
  • Volatilità implicita borsa europea: volatilità implicita calcolata sulle opzioni at-the-money sull’indice Eurostoxx a scadenza 3 mesi;
  • Rendimento borsa ITA/Europa: differenza tra il rendimento settimanale della borsa italiana e quello delle borse europee, calcolato sugli indici FTSEMIB e Eurostoxx;
  • Spread ITA/GER: differenza tra i tassi di interesse italiani e tedeschi a 10 anni;
  • Spread EU/GER: differenza media tra i tassi di interesse dei principali paesi europei (Francia, Belgio, Spagna, Italia, Olanda) e quelli tedeschi a 10 anni;
  • Euro/dollaro: tasso di cambio euro/dollaro;
  • Spread US/GER 10Y: spread tra i tassi di interesse degli Stati Uniti e quelli tedeschi con scadenza 10 anni;
  • Prezzo Oro: quotazione dell’oro (in USD)
  • Spread 10Y/2Y Euro Swap Curve: differenza del tasso della curva EURO ZONE IRS 3M a 10Y e 2Y;
  • Euribor 6M: tasso euribor a 6 mesi.

I colori sono assegnati in un’ottica VaR: se il valore riportato è superiore (inferiore) al quantile al 15%, il colore utilizzato è l’arancione. Se il valore riportato è superiore (inferiore) al quantile al 5% il colore utilizzato è il rosso. La banda (verso l’alto o verso il basso) viene selezionata, a seconda dell’indicatore, nella direzione dell’instabilità del mercato. I quantili vengono ricostruiti prendendo la serie storica di un anno di osservazioni: ad esempio, un valore in una casella rossa significa che appartiene al 5% dei valori meno positivi riscontrati nell’ultimo anno. Per le prime tre voci della sezione “Politica Monetaria”, le bande per definire il colore sono simmetriche (valori in positivo e in negativo). I dati riportati provengono dal database Thomson Reuters. Infine, la tendenza mostra la dinamica in atto e viene rappresentata dalle frecce: ↑,↓, ↔  indicano rispettivamente miglioramento, peggioramento, stabilità.

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