Non-core Funding Research Articles

Banks funding, leverage, and investment

Banks’ funding sources have changed significantly during the last two decades. The share of non-core funding (NCF) was high before the 2008 crisis but declined substantially after the crisis. We propose a general equilibrium model where NCF provides insurance against idiosyncratic risks faced by banks. Insurance makes leverage and investment more attractive, but it also increases the vulnerability of the banking sector to crises. We show that learning about the likelihood of a crisis could have been important for generating the observed dynamics of NCF and leverage, which in turn affected the dynamics of the macro-economy.

Insider Abuse and Fraud Prediction for U.S. Banks: A Comparison of Machine Learning Approaches

We develop and compare alternative empirical models for the detection of insider abuse and fraud occurring at U.S. commercial banks with the goals of identifying leading indicators of fraud and fraud prediction. Specifically, we use information on enforcement actions taken by bank supervisors to remove bank officers and other employees and to prohibit bank employees from banking during the period 2007–2019 to identify instances of serious insider abuse and fraud. To the best of our knowledge, these data — enforcement actions — have not been used in previous studies of insider abuse and fraud (hereafter, fraud) at banks. The explanatory variables in our models are measures of banks’ capital adequacy, asset quality, management, earnings, liquidity and sensitivity to market risk and other financial measures that previous studies have identified as indicators of fraud. We model fraud using machine learning approaches, each with different strengths and weaknesses — artificial neural network, deep learning autoencoder network, gradient boosting, logit regression and random forest. The models are fitted annually using observed incidences of fraud and four quarters of bank financial data. We use these models to make predictions of the probability of fraud at banks in the following calendar year. Our results indicate that artificial neural network, gradient boosting and random forest are, in general, more accurate in out-of-sample/time fraud forecasts than are deep learning autoencoder network and logit regression models. Finally, in terms of the drivers of fraud the estimates of logit regressions are somewhat mixed but do suggest that earning assets and capitalization are negatively related to fraud while loan loss rates and noncore funding dependence are positively related to fraud.

Non-core liabilities and interest rate pass-through: bank-level evidence from Indonesia

ABSTRACTThe policy importance of non-core liabilities (bank liabilities other than equity and retail deposits) has risen to prominence in recent years with a number of studies highlighting it as a useful indicator of financial procyclicality and vulnerability. In this paper, we look at non-core liabilities in relation to its role in the transmission of monetary policy, particularly by examining how the interest rate channel of monetary policy is affected by non-deposit liabilities. We analyse this issue in the context of an emerging economy experience of Indonesia, which in recent years, has seen an increased reliance of its banking sector on non-core funding. Our investigation employs available bank-level data on non-core liabilities and lending rates in Indonesia over the period October 2011 to July 2016. We find that including non-core liabilities in the estimation has an effect, relative to the baseline, of stronger overall and immediate pass-through, albeit with a more sluggish adjustment towards the correction of disequilibrium in the next period. The overall effect is that non-core liabilities make the duration longer for the monetary policy rate to transmit to bank lending rates in Indonesia.

Impact of Islamic Securitization (Sukuk) on Islamic Banks Liquidity Risk in Light of Basel III Requirements

This study aims to investigate the relation between Islamic securitization representing in Sukuk, and the Islamic banks ‘liquidities in light of Basel 3 requirements. So that the study investigates three variables which include Islamic securitization as independent variable; net cash from financing activities and net noncore funding dependence ratio as dependent variables. The study follows quantitative method by employing cross sectional data context analysis. The data is collected from six banks over six countries through the period 2011-2013. Pearson regression is used to measure causal relation between Sukuk and Net Stable Fund Ratio (NSFR), hence the model is developed to describe the relation. The study uses net noncore funding dependence ratio as (NSFR) which was required by Basel III. The regression result finds that there is positive relation between Sukuk and NSFR for Islamic banks. Also the study uses loans / deposits ratio to discover the relation between Sukuk and Islamic banks ‘liquidity risk, so the regression test shows that there is positive relation between Sukuk and loans / deposit ratio.

Non-Core Liabilities and Monetary Policy Transmission in Indonesia During the Post-2007 Global Financial Crisis

The policy importance of non-core liabilities has risen to prominence in recent years with the studies of Shin and Shin (2010), Hahm, et al., (2010) and Hahm, et al., (2013) highlighting it as a useful indicator of financial procyclicality and vulnerability. In this paper, we look at non-core liabilities in relation to its role in the transmission of monetary policy, particularly by examining how the interest rate channel of monetary policy is affected by non-deposit liabilities. We analyse this issue in the context of an emerging economy experience of Indonesia, which in recent years, has seen an increased reliance of its banking sector on non-core funding. Our investigation employs available bank-level data on non-core liabilities and lending rates in Indonesia over the period October 2011 to July 2016. We find that including non-core liabilities in the estimation has an effect, relative to the baseline, of stronger overall and immediate pass-through, albeit with a more sluggish adjustment towards correction of disequilibrium in the next period. The overall effect is that non-core liabilities make the duration lengthier for the monetary policy rate to transmit to bank lending rates in Indonesia.

Home-Host Banking Issues and Non-Core Funding—Evidence from Central and Eastern Europe

This paper investigates the role of home monetary policy stance and banking regulation on short-term noncore funding in Central, Eastern and Southeastern Europe using a sample of local subsidiaries. We find that the accumulation and dynamic of noncore funding differ significantly between subsidiaries in EU vs. non-EU host countries. While the direct impact of home monetary policy is to a certain extent limited it is amplified through several channels. The most potent among them are the characteristics of the parent bank: capitalization, liquidity, loan growth aggressiveness, provisioning policies and its relative size vis-a-vis a subsidiary. Regulation has only marginal effects and seems to be more potent for the subsidiaries operating in the EU countries. At the same time, host bank regulation seems neutral to the dynamics of the noncore funding and risk build-up on the liability side of the subsidiaries operating under those regimes.

Foreign Currency Noncore Bank Liabilities and Macroprudential Levy in Korea

:Using bank-level data in Korea, we examine empirical properties of foreign currency noncore bank liabilities and assess policy effectiveness of the macroprudential levy introduced in postcrisis Korea. Our panel regression and VAR analyses indicate that the foreign currency noncore bank liability ratio yields significant information on the vulnerability of banks, and the macroprudential levy has exerted nontrivial effects on the noncore funding of banks, leading to the mitigation of foreign currency liquidity risks of Korea’s banks. Our findings strengthen the rationale for using appropriate macroprudential policies as a guard against financial vulnerability in open emerging economies.

(Korea's Multilateral Aid: Recent Developments and Future Challenges)

(Korea's Multilateral Aid: Recent Developments and Future Challenges)

Multi-bi aid and effects of the 2008–10 economic crisis on voluntary development assistance for health contributions: a time series analysis

BackgroundRoughly 40% of multilateral funding is given through so-called multi-bi aid according to an Organisation for Economic Co-operation and Development's Development Assistance Committee report. Multi-bi aid is the practice of donors voluntarily choosing to direct non-core funding—earmarked for specific sectors, themes, countries, or regions—through multilateral agencies. The funding passes through multilateral channels but in fact is more bilaterally controlled. Examples of multi-bi aid include voluntary contributions within WHO, trust funds within World Bank, the Global Fund to Fight HIV/AIDS, TB, and Malaria, and the GAVI Alliance. Most analyses have shown that development assistance for health has not decreased as a result of the global economic crisis of 2008–10, but these analyses have not established whether important reallocations have occurred between different funding channels. We investigated whether voluntary channels have been more or less consistent than assessed contributions based on the assumption that the withdrawal of assessed contributions is more difficult because of the membership and voting rights that are linked to them. We also test whether multi-bi aid flows have increased or decreased as a proportion of overall global health funding. MethodsWe used data for development assistance for health from 2002–09 collected from the Institute for Health Metrics and Evaluation. We categorised disbursements of development assistance for health by all Organisation for Economic Co-operation and Development countries and the Bill and Melinda Gates Foundation as being either traditional bilateral, traditional multilateral (WHO and World Bank), or multi-bi (Global Fund, GAVI, and UNAIDS). We tested by time series methods whether funding trends for each channel deviated after the onset of the global financial crisis (donations made in 2008, or 2009). FindingsSince 2002, global health donors have increasingly prioritised multi-bi aid at the expense of more traditional forms of multilateral aid (measured as a proportion of all development assistance for health). Multi-bi aid increased as a proportion of all aid by 1·5–2·0 percentage points while bilateral aid as a share of total development assistance for health remained stable over this period, ranging from 62% to 68%. The trend towards multi-bi aid reversed after the onset of the global financial crisis, with donors decreasing their contributions to GAVI, the Global Fund, and UNAIDS by 6 percentage points since 2008. The ten largest global health donors decreased multi-bi aid by nearly 6% as a proportion of all development assistance for health during 2008–09. InterpretationSeveral calls have been made to increase the proportion of funding to newer funding mechanisms such as the Global Fund and GAVI Alliance. Such calls emphasise the importance of short-term global health goals, such as keeping people on treatment, or getting children vaccinated. Our study supports the argument that this type of financing arrangement—although attractive to donors in the short term—creates financial uncertainty and thus hinders the ability of new multilateral health institutions to maintain funding. FundingNone.