Loan asset indicators and commercial bank fragility in Kenya

Purpose. To test the predictive ability of loan asset indicators on Commercial bank fragility in Kenya. Design/Method/Research approach. The study adopted positivism research philosophy with exploratory research design. The study population was 42 Commercial banks in operation on 31st December 2015. Secondary data was collected from Central Bank of Kenya and analysed using Stata Statistics/Data analysis. Generalised Linear Model was used to establish the relationship between asset indicators and bank fragility. The concept of credit creation was explored as the genesis of bank fragility. This study is part of early warning systems in detecting bank fragility. Findings. The research found a direct relationship between a lagged dependent variable, loan portfolio growth, loan deposit ratio and bank fragility. Practical implications. Recommendations are followed on the basis of this study. At first, regulator develop a potential solution to control loan portfolio growth, cap loan deposit ratio and limit the level of non-performing loans. Banking practitioners should model monthly reporting requirements to ensure that banks are able to disclose the ratio and explain any significant changes. Secondly, since Non-performing loans can act as an incentive for bank managers to seek deposits and lend more thereby exacerbating the problem, banks with NPL to gross loans greater than an upper threshold determined by the regulator should not be allowed to attract more deposits. Thirdly, set the maximum level of loan deposit ratio to avoid expensive, sensitive and high-risk loan capital. Implementation of these recommendations will lead to secured social welfare. Originality/Value. The study examines the role of certain loan asset indicators on bank fragility and extends the discussion in the area of early warning systems and commercial bank instability in Kenya. Research limitations/Future Research. This research contributes to the discussion on bank fragility and early warning systems. The further research should review evidence from other jurisdiction with high numbers of distressed institutions to determine how many months or years before distress the three significant variables could predict fragility. Besides, there is need for research on insider loans as defined and why there was no statistical significance. Paper type. Empirical.

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Current State and Solutions for Future Challenges in Early Warning Systems and Alerting Technologies

Advanced ICTs for Disaster Management and Threat Detection ◽

10.4018/978-1-61520-987-3.ch008 ◽

2011 ◽

pp. 108-130 ◽

Cited By ~ 5

Author(s):

Ulrich Meissen ◽

Agnès Voisard

Keyword(s):

Information And Communication Technologies ◽

Early Warning ◽

Communication Technologies ◽

Early Warning Systems ◽

Future Research ◽

Warning Systems ◽

Current State ◽

Future Challenges ◽

Critical Issues ◽

Information And Communication

The deployment of Early Warning Systems (EWS) and Alerting Technologies (AT) is one of the best measures for improved disaster prevention and mitigation. With the evolution of Information and Communication Technologies (ICT), we face new opportunities as well as new challenges for improving classical warning processes. This chapter concentrates on the main aspects of existing early warning systems and alerting technologies. Beginning with the definition and classifications in this field, we describe general approaches, representative systems, and interoperability aspects of EWS. Furthermore, we introduce a list of criteria for evaluating and comparing existing systems. It is worth noting that the deployment of an operational EWS is a complex challenge and remains a young field of research. This is due to many reasons, ranging from the political to the technical. The most critical issues regarding efficient alerting are described in this chapter, along with areas for future research.

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Towards an improved understanding of participation in natural hazard early warning systems

International Journal of Disaster Resilience in the Built Environment ◽

10.1108/ijdrbe-11-2020-0120 ◽

2021 ◽

Vol ahead-of-print (ahead-of-print) ◽

Author(s):

Georgina Clegg ◽

Richard Haigh ◽

Dilanthi Amaratunga

Keyword(s):

Conceptual Understanding ◽

Early Warning ◽

Natural Hazard ◽

Early Warning Systems ◽

Future Research ◽

Warning Systems ◽

Content Type ◽

Academic Literature ◽

Online Searches ◽

Risk Knowledge

Purpose The purpose of this paper is to improve the conceptual understanding of the process of participation in early warning systems (EWS) through a review of participatory EWS examples in the academic literature. Specifically, this paper asks: who is involved, what responsibilities do participants hold, what activities are they involved in, and what are the associated successes, issues and outcomes? Design/methodology/approach A total of 30 cases of participation in EWS documented in the academic literature were identified through online searches. Existing concepts in participation (power and responsibility, communication) and people-centred early warning (risk knowledge, monitoring and warning, communication and dissemination and response capability) were used to examine each paper. Findings Participation was found to take place through a range of activities across all elements of the EWS. Participation also varied in breadth of inclusion, ranging from the general public to selected volunteers. The majority of cases received support and facilitation from other actors, such as government and NGOs, but the extent of power and responsibility held by participants varied greatly within this. Common successes and issues associated with participatory EWS and the potential outcomes are presented, and the opportunities, challenges and gaps in knowledge are discussed. Originality/value This paper links participation and EWS literature to form a clearer conceptualisation of participation in EWS in support of future research in the field. It provides unique insights into who participates, their roles and relations with other actors and the outcomes of participation.

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PERBANDINGAN EARLY WARNING SYSTEMS (EWS) UNTUK MEMPREDIKSI KEBANGKRUTAN BANK UMUM DI INDONESIA

Buletin Ekonomi Moneter dan Perbankan ◽

10.21098/bemp.v7i3.120 ◽

2005 ◽

Vol 7 (3) ◽

Author(s):

Liza Angelina, SE, Msi, Akt

Keyword(s):

Discriminant Analysis ◽

Commercial Bank ◽

Early Warning ◽

Early Warning Systems ◽

Warning Systems ◽

Multiple Discriminant Analysis ◽

Analysis Model ◽

Recognition Model ◽

System Models ◽

Forewarning System

This research is testing the capability of several forewarning system models to predict bank bankruptcy. We apply these models on Indonesian commercial bank data during the period of 1994/ 1995 - 1999/2000. Considering the data incompleteness and or their inexistence, our data finally contains of 74 failed-banks and 81 non failed-banks.Our result shows the Trait Recognition model (TR) is more pre-eminent than Logit and Multiple Discriminant Analysis model (MDA).Keywords : Trait Recognition (TR), Logit, Multiple Discriminant Analysis (MDA), Bank BankruptcyJEL: C25, C35, G21, G33

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The CARE Telematics Network for the Surveillance of Influenza in Europe

Methods of Information in Medicine ◽

10.1055/s-0038-1634617 ◽

1995 ◽

Vol 34 (05) ◽

pp. 518-522 ◽

Cited By ~ 13

Author(s):

M. Bensadon ◽

A. Strauss ◽

R. Snacken

Keyword(s):

Public Health ◽

Early Warning ◽

Early Warning Systems ◽

Warning Systems ◽

Surveillance Networks ◽

Spanish Flu ◽

The 1950S ◽

National Networks ◽

First Time

Abstract:Since the 1950s, national networks for the surveillance of influenza have been progressively implemented in several countries. New epidemiological arguments have triggered changes in order to increase the sensitivity of existent early warning systems and to strengthen the communications between European networks. The WHO project CARE Telematics, which collects clinical and virological data of nine national networks and sends useful information to public health administrations, is presented. From the results of the 1993-94 season, the benefits of the system are discussed. Though other telematics networks in this field already exist, it is the first time that virological data, absolutely essential for characterizing the type of an outbreak, are timely available by other countries. This argument will be decisive in case of occurrence of a new strain of virus (shift), such as the Spanish flu in 1918. Priorities are now to include other existing European surveillance networks.

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