Search results for: predictive risk

Authors: Amanda R. R. Oliveira, Caio F. F. C. Cunha, Juan C. L. Junior, Amorim H. P. Junior

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Children deaths are traumatic events that most often can be prevented. The technology of prevention and intervention in cases of infant deaths is available at low cost and with solid evidence and favorable results, however, with low access cover. Weight is one of the main factors related to death in the neonatal period, so the newborns of low birth weight are a population at high risk of death in the neonatal period, especially early neonatal period. This paper describes the development of a model based in neural network analysis to predict the mortality risk rating in the early neonatal period for newborns of low birth weight to identify the individuals of this population with increased risk of death. The neural network applied was trained with a set of newborns data obtained from Brazilian health system. The resulting network presented great success rate in identifying newborns with high chances of death, which demonstrates the potential for using this tool in an integrated manner to the health system, in order to direct specific actions for improving prognosis of newborns.

Keywords: low birth weight, neonatal death risk, neural network, newborn

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Authors: Jennifer Reese, Josh Biber, Howard Weeks, Rachel Hess

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Aim: The Edinburgh Postnatal Depression Screen (EPDS) is a mental health screening for pregnant women that has been widely used over the last 30 years. This screen is typically given in clinic on paper to patients throughout pregnancy and postpartum. The screen helps identify patients who may be at risk for pregnancy related depression or postpartum depression. In early 2016, University of Utah Health implemented an electronic version of the EPDS as well as the PROMIS Depression v1.0 instrument for all pregnant and postpartum patients. We asked patients both instruments to understand coverage of patients identified as at risk for each instrument. Methods: The EPDS is currently administered as part of our PRO template for pregnant and postpartum women. We also administer the PROMIS Depression as part of a standard PRO assessment to all patients. Patients are asked to complete an assessment no more often than every eight weeks. PRO assessments are either completed at home or in clinic with a tablet computer. Patients with a PROMIS score of ≥ 65 or a EPDS score of ≥ 10 were identified as at risk for depression Results: From April 2016 to April 2017, 1,330 unique patients were screened at University of Utah Health in OBGYN clinics with both the EPDS and PROMIS depression instrument on the same day. There were 28 (2.1%) patients were identified as at risk for depression using the PROMIS depression screen, while 262 (19.7%) patients were identified as at risk for postpartum depression using the EPDS screen. Overall, 27 (2%) patients were identified as at risk on both instruments. Conclusion: The EPDS identified a higher percent (19.7%) of patients at risk for depression when compared to the PROMIS depression (2.1%). Ninety-six percent of patients who screened positive on the PROMIS depression screen also screened positive on the EPDS screen. Mental health is an important component to a patient’s overall wellbeing. We want to ensure all patients, particularly pregnant or post-partum women, receive screening and treatment when necessary. A combination of screenings may be necessary to provide the overall best care for patients and to identify the highest percentage of patients at risk.

Keywords: patient reported outcomes, mental health, maternal, depression

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Authors: M. V. Shivaani, P. K. Jain, Surendra S. Yadav

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Worldwide regulators, practitioners and researchers view risk-disclosure as one of the most important steps that will promote corporate accountability and transparency. Recognizing this growing significance of risk disclosures, the paper first develops a risk disclosure index. Covering 69 risk items/themes, this index is developed by employing thematic content analysis and encompasses three attributes of disclosure: namely, nature (qualitative or quantitative), time horizon (backward-looking or forward-looking) and tone (no impact, positive impact or negative impact). As the focus of study is on substantive rather than symbolic disclosure, content analysis has been carried out manually. The study is based on non-financial companies of Nifty500 index and covers a ten year period from April 1, 2005 to March 31, 2015, thus yielding 3,872 annual reports for analysis. The analysis reveals that (on an average) only about 14% of risk items (i.e. about 10 out 69 risk items studied) are being disclosed by Indian companies. Risk items that are frequently disclosed are mostly macroeconomic in nature and their disclosures tend to be qualitative, forward-looking and conveying both positive and negative aspects of the concerned risk. The second objective of the paper is to gauge the factors that affect the level of disclosures in annual reports. Given the panel nature of data, and possible endogeneity amongst variables, Diff-GMM regression has been applied. The results indicate that age and size of firms have a significant positive impact on disclosure quality, whereas growth rate does not have a significant impact. Further, post-recession period (2009-2015) has witnessed significant improvement in quality of disclosures. In terms of corporate governance variables, board size, board independence, CEO duality, presence of CRO and constitution of risk management committee appear to be significant factors in determining the quality of risk disclosures. It is noteworthy that the study contributes to literature by putting forth a variant to existing disclosure indices that not only captures the quantity but also the quality of disclosures (in terms of semantic attributes). Also, the study is a first of its kind attempt in a prominent emerging market i.e. India. Therefore, this study is expected to facilitate regulators in mandating and regulating risk disclosures and companies in their endeavor to reduce information asymmetry.

Keywords: risk disclosure, voluntary disclosures, corporate governance, Diff-GMM

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Authors: Muhammad Arzim Naim, Saiful Azhar Rosly, Mohamad Sahari Nordin

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The objective of this study is to investigate the factors affecting the rise of Shariah non-compliance risk that can bring Islamic banks to succumb to monetary loss. Prior literatures have never analyzed such risk in details despite lots of it arguing on the validity of some Shariah compliance products. The Shariah non-compliance risk in this context is looking to the potentially failure of the facility to stand from the court test say that if the banks bring it to the court for compensation from the defaulted clients. The risk may also arise if the customers refuse to make the financing payments on the grounds of the validity of the contracts, for example, when relinquishing critical requirement of Islamic contract such as ownership, the risk that may lead the banks to suffer loss when the customer invalidate the contract through the court. The impact of Shariah non-compliance risk to Islamic banks is similar to that of legal risks faced by the conventional banks. Both resulted into monetary losses to the banks respectively. In conventional banking environment, losses can be in the forms of summons paid to the customers if they won the case. In banking environment, this normally can be in very huge amount. However, it is right to mention that for Islamic banks, the subsequent impact to them can be rigorously big because it will affect their reputation. If the customers do not perceive them to be Shariah compliant, they will take their money and bank it in other places. This paper provides new insights of risks faced by credit intensive Islamic banks by providing a new extension of knowledge with regards to the Shariah non-compliance risk by identifying its individual components that directly affecting the risk together with empirical evidences. Not limited to the Islamic banking fraternities, the regulators and policy makers should be able to use findings in this paper to evaluate the components of the Shariah non-compliance risk and make the necessary actions. The paper is written based on Malaysia’s Islamic banking practices which may not directly related to other jurisdictions. Even though the focuses of this study is directly towards to the Bay Bithaman Ajil or popularly known as BBA (i.e. sale with deferred payments) financing modality, the result from this study may be applicable to other Islamic financing vehicles.

Keywords: Islamic banking, Islamic finance, Shariah Non-compliance risk, Bay Bithaman Ajil (BBA), principal axis factoring

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Authors: Daniel Mokatsanyane, Johnny Jansen Van Rensburg

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This paper is a concise introduction of the risk management on the water derivatives market. Water, a new commodity in the market, is one of the most important commodity on earth. As important to life and planet as crops, metals, and energy, none of them matters without water. This paper presents a brief overview of water as a tradable commodity via a new first of its kind futures contract on the Nasdaq Veles California Water Index (NQH2O) derivative instrument, TheGeneralised Autoregressive Conditional Heteroscedasticity (GARCH) statistical model will be the used to measure the water price volatility of the instrument and its performance since it’s been traded. describe the main products and illustrate their usage in risk management and also discuss key challenges with modeling and valuation of water as a traded commodity and finally discuss how water derivatives may be taken as an alternative asset investment class.

Keywords: water derivatives, commodity market, nasdaq veles california water Index (NQH2O, water price, risk management

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Authors: Tayo P. Ogundunmade, Adedayo A. Adepoju

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Terrorist attacks in liberal democracies bring about a few pessimistic results, for example, sabotaged public support in the governments they target, disturbing the peace of a protected environment underwritten by the state, and a limitation of individuals from adding to the advancement of the country, among others. Hence, seeking for techniques to understand the different factors involved in terrorism and how to deal with those factors in order to completely stop or reduce terrorist activities is the topmost priority of the government in every country. This research aim is to develop an efficient deep learning-based predictive model for the prediction of future terrorist activities in Nigeria, addressing low-quality prediction accuracy problems associated with the existing solution methods. The proposed predictive AI-based model as a counterterrorism tool will be useful by governments and law enforcement agencies to protect the lives of individuals in society and to improve the quality of life in general. A Heterogeneous Bayesian Neural Network (HETBNN) model was derived with Gaussian error normal distribution. Three primary transfer functions (HOTTFs), as well as two derived transfer functions (HETTFs) arising from the convolution of the HOTTFs, are namely; Symmetric Saturated Linear transfer function (SATLINS ), Hyperbolic Tangent transfer function (TANH), Hyperbolic Tangent sigmoid transfer function (TANSIG), Symmetric Saturated Linear and Hyperbolic Tangent transfer function (SATLINS-TANH) and Symmetric Saturated Linear and Hyperbolic Tangent Sigmoid transfer function (SATLINS-TANSIG). Data on the Terrorist activities in Nigeria gathered through questionnaires for the purpose of this study were used. Mean Square Error (MSE), Mean Absolute Error (MAE) and Test Error are the forecast prediction criteria. The results showed that the HETFs performed better in terms of prediction and factors associated with terrorist activities in Nigeria were determined. The proposed predictive deep learning-based model will be useful to governments and law enforcement agencies as an effective counterterrorism mechanism to understand the parameters of terrorism and to design strategies to deal with terrorism before an incident actually happens and potentially causes the loss of precious lives. The proposed predictive AI-based model will reduce the chances of terrorist activities and is particularly helpful for security agencies to predict future terrorist activities.

Keywords: activation functions, Bayesian neural network, mean square error, test error, terrorism

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Authors: Muhammad Ridho Fakhrin, Leni Sagita Riantini, Yusuf Latief

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Based on the 2015-2019 RPJMN data, the realization of toll road infrastructure development in Indonesia experienced a delay of 49% or 904 km of the total plan. One of the major causes of delays in development is caused by institutional factors. The case study taken in this research is the construction of the Trans Sumatra Toll Road (JTTS). The purpose of this research is to identify the institutional forms, functions, roles, duties, and responsibilities of each stakeholder and the risks that occur in the Trans Sumatra Toll Road Infrastructure Development. Risk analysis is implemented on functions, roles, duties, responsibilities of each existing stakeholder and is carried out at the Funding Stage, Technical Planning Stage, and Construction Implementation Stage in JTTS. This research is conducted by collecting data through a questionnaire survey, then processed using statistical methods, such as homogeneity, data adequacy, validity, and reliability test, continued with risk assessment based on a risk matrix. The results of this study are the evaluation and development of institutional functions in risk-based JTTS development can improve time performance and minimize delays in the construction process.

Keywords: institutional, risk management, time performance, toll road

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Authors: A. Luli, A. Santona

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It is rare for individuals that are involved in a relationship to think about the possibility of having procreation problems in the near present or in the future. However, infertility is a condition that affects millions of people all around the world. Often, infertile individuals have to deal with experiences of psychological, relational and social problems. In these cases, they have to review their choices and take into consideration, if it is necessary, new ones. Different studies have examined the different decisions that infertile individuals have to go through dealing with infertility and its treatment, but none of them is focused on the decision-making style used by infertile individuals to solve their problem and on the factors that influences it. The aim of this paper is to define the style of decision-making used by infertile persons to give a solution to the ‘problem’ and the potential predictive role of the attachment and of the dyadic adjustment. The total sample is composed by 251 participants, divided in two groups: the experimental group composed by 114 participants, 62 males and 52 females, age between 25 and 59 years, and the control group composed by 137 participants, 65 males and 72 females, age between 22 and 49 years. The battery of instruments used is composed by: the General Decision Making Style (GDMS), the Experiences in Close Relationships Questionnaire Revised (ECR-R), Dyadic Adjustment Scale (DAS), and the Symptom Checklist-90-R (SCL-90-R). The results from the analysis of the samples showed a prevalence of the rational decision-making style for both males and females. No significant statistical difference was found between the experimental and control group. Also the analyses showed a significant statistical relationship between the decision making styles and the adult attachment styles for both males and females. In this case, only for males, there was a significant statistical difference between the experimental and the control group. Another significant statistical relationship was founded between the decision making styles and the adjustment scales for both males and females. Also in this case, the difference between the two groups was founded to be significant only of males. These results contribute to enrich the literature on the subject of decision-making styles in infertile individuals, showing also the predictive role of the attachment styles and the adjustment, confirming in this was the few results in the literature.

Keywords: adjustment, attachment, decision-making style, infertility

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Authors: Junhong Li, Danni Cheng, Yaxin Luo, Xiaowei Yi, Ke Qiu, Wendu Pang, Minzi Mao, Yufang Rao, Yao Song, Jianjun Ren, Yu Zhao

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Background: The number of multiple cancer patients was increasing, and the impact of prior cancer history on salivary gland cancer patients remains unclear. Methods: Clinical, demographic and pathological information on salivary gland cancer patients were retrospectively collected from the Surveillance, Epidemiology, and End Results (SEER) database from 2004 to 2017, and the characteristics and prognosis between patients with a prior cancer and those without prior caner were compared. Univariate and multivariate cox proportional regression models were used for the analysis of prognosis. A risk score model was established to exam the impact of treatment on patients with a prior cancer in different risk groups. Results: A total of 9098 salivary gland cancer patients were identified, and 1635 of them had a prior cancer history. Salivary gland cancer patients with prior cancer had worse survival compared with those without a prior cancer (p<0.001). Patients with a different type of first cancer had a distinct prognosis (p<0.001), and longer latent time was associated with better survival (p=0.006) in the univariate model, although both became nonsignificant in the multivariate model. Salivary gland cancer patients with a prior cancer were divided into low-risk (n= 321), intermediate-risk (n=223), and high-risk (n=62) groups and the results showed that patients at high risk could benefit from surgery, radiation therapy, and chemotherapy, and those at intermediate risk could benefit from surgery. Conclusion: Prior cancer history had an adverse impact on the survival of salivary gland cancer patients, and individualized treatment should be seriously considered for them.

Keywords: prior cancer history, prognosis, salivary gland cancer, SEER

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Authors: Marinko Maslaric, Maja Jokic

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When searching for fast and long term responses, sustainable logistics and supply chain applications have developed irrefutable theories and hypotheses towards market requirements. Nevertheless, there are certain misunderstandings on how the implementation of sustainability principles (social, economical, and environmental) and concepts should work in practice, more specifically, within a humanitarian supply chain management context. This paper will focus on the review and analysis of risk management concepts in humanitarian supply chain in order to identify their compliance with sustainable principles. In this direction, the study will look for strategies that suggest: minimization of environmental impacts throughout the reduction of resources consumption, depreciation of logistics costs, including supply chain ones, minimization of transportation and service costs, elaboration of quality performance of supply chain and logistics, and reduction of supply chain delivery time. On the side of meeting all defense, trades and humanitarian logistics needs, the research will be aligned to UN Sustainable Development Goals, standards, and performances. It will start with relevant strategies for identification of risk indicators and it will end with suggestion of valuable strategic approaches for their minimization or total prevention. Finally, a content analysis will propose a suitable methodological structure for the creation of most sustainable strategy in risk management of humanitarian supply chain. Content analysis will accompany thorough, consistent and methodical approach of literature review for potential disaster risk management plan. Thereupon, the propositions of this research will look for contemporary literature gaps, with respect to operate the literature analysis and to suggest the appropriate sustained risk low master plan. The indicated is here to secure the high quality of logistics practices in hazardous events.

Keywords: humanitarian logistics, sustainability, supply chain risk, risk management plan

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Authors: Tomyslav Sledevič, Artūras Serackis, Gintautas Tamulevičius, Dalius Navakauskas

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This paper presents a comparative evaluation of features extraction algorithm for a real-time isolated word recognition system based on FPGA. The Mel-frequency cepstral, linear frequency cepstral, linear predictive and their cepstral coefficients were implemented in hardware/software design. The proposed system was investigated in the speaker-dependent mode for 100 different Lithuanian words. The robustness of features extraction algorithms was tested recognizing the speech records at different signals to noise rates. The experiments on clean records show highest accuracy for Mel-frequency cepstral and linear frequency cepstral coefficients. For records with 15 dB signal to noise rate the linear predictive cepstral coefficients give best result. The hard and soft part of the system is clocked on 50 MHz and 100 MHz accordingly. For the classification purpose, the pipelined dynamic time warping core was implemented. The proposed word recognition system satisfies the real-time requirements and is suitable for applications in embedded systems.

Keywords: isolated word recognition, features extraction, MFCC, LFCC, LPCC, LPC, FPGA, DTW

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Authors: Yi-Fan Lin, Peter P. Howley, Frank A. Tuyl

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Quality measurement and reporting systems are used in healthcare internationally. In Australia, the Australian Council on Healthcare Standards records and reports hundreds of clinical indicators (CIs) nationally across the healthcare system. These CIs are measures of performance in the clinical setting, and are used as a screening tool to help assess whether a standard of care is being met. Existing analysis and reporting of these CIs incorporate Bayesian methods to address sampling variation; however, such assessments are retrospective in nature, reporting upon the previous six or twelve months of data. The use of Bayesian methods within statistical process control for monitoring systems is an important pursuit to support more timely decision-making. Our research has developed and assessed a new graphical monitoring tool, similar to a control chart, based on the beta-binomial posterior predictive (BBPP) distribution to facilitate the real-time assessment of health care organizational performance via CIs. The BBPP charts have been compared with the traditional Bernoulli CUSUM (BC) chart by simulation. The more traditional “central” and “highest posterior density” (HPD) interval approaches were each considered to define the limits, and the multiple charts were compared via in-control and out-of-control average run lengths (ARLs), assuming that the parameter representing the underlying CI rate (proportion of cases with an event of interest) required estimation. Preliminary results have identified that the BBPP chart with HPD-based control limits provides better out-of-control run length performance than the central interval-based and BC charts. Further, the BC chart’s performance may be improved by using Bayesian parameter estimation of the underlying CI rate.

Keywords: average run length (ARL), bernoulli cusum (BC) chart, beta binomial posterior predictive (BBPP) distribution, clinical indicator (CI), healthcare organization (HCO), highest posterior density (HPD) interval

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Authors: A. Asambe

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A study was conducted to determine the level of compliance with sanitary measures in piggeries, and awareness and risk factors of African swine fever in Benue State, Nigeria. Questionnaires were distributed to 74 respondents consisting of piggery owners and attendants in different piggeries across 12 LGAs to collect data for this study. Sanitary measures in piggeries were observed to be generally very poor, though respondents admitted being aware of ASF. Piggeries located within a 1 km radius of a slaughter slab (OR=9.2, 95% CI - 3.0-28.8), piggeries near refuse dump sites (OR=3.0, 95% CI - 1.0-9.5) and piggeries where farm workers wear their work clothes outside of the piggery premises (OR=0.2, 95% CI - 0.1-0.7) showed higher chances of ASFV infection and were significantly associated (p < 0.0001), (p < 0.05) and (p < 0.01), and were identified as potential risk factors. The study concluded that pigs in Benue State are still at risk of an ASF outbreak. Proper sanitary and hygienic practices is advocated and emphasized in piggeries, while routine surveillance for ASFV antibodies in pigs in Benue State is strongly recommended to provide a reliable reference data base to plan for the prevention of any devastating ASF outbreak.

Keywords: African swine fever, awareness, piggery, risk factors, sanitary measures

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Authors: Yuri Katz, Kun Liu, Arunram Atmacharan

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Due to illiquidity, mispricing on Credit Markets is inevitable. This creates huge challenges to banks and investors as they seek to find new ways of risk valuation and portfolio management in a post-credit crisis world. Here, we analyze the difference in behavior of the spread-to-maturity in investment and high-yield categories of US corporate bonds between 2014 and 2023. Deviation from the theoretical dependency of this measure in the universe under study allows to identify multiple cases of mispriced credit risk. Remarkably, we observe mispriced bonds in both categories of credit ratings. This identification is supported by the application of the state-of-the-art machine learning model in more than 90% of cases. Noticeably, the ML-driven model-based forecasting of a category of bond’s credit ratings demonstrate an excellent out-of-sample accuracy (AUC = 98%). We believe that these results can augment conventional valuations of credit portfolios.

Keywords: credit risk, credit ratings, bond pricing, spread-to-maturity, machine learning

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Authors: Makhosazana Dubazana

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Many South Africans commuters use minibus taxis daily and are connected to the informal transport network through metro centres informally known as Taxi Ranks. Taxi ranks form part of an economic nexus for many informal traders, connecting them to commuters, their prime clientele. They work along designated areas along the periphery of the taxi rank and in between taxi lanes. Informal traders are therefore at risk of adverse health effects associated with the inhalation of exhaust fumes from minibus taxis. Of the exhaust emissions, benzene, toluene, ethylbenzene and xylenes (BTEX) have high toxicity. Purpose: The purpose of this study was to conduct a Human Health Risk Assessment for informal traders, looking at their exposure to BTEX compounds. Methods: The study was conducted in a subsection of a taxi rank which is representative of the entire taxi rank. This subsection has a daily average of 400 minibus taxi moving through it and an average of 60 informal traders working in it. In the health risk assessment, a questionnaire was conducted to understand the occupational behaviour of the informal traders. This was used to deduce the exposure scenarios and sampling locations. Three sampling campaigns were run for an average of 10 hours each covering the average working hours of traders. A gas chronographer was used for collecting continues ambient air samples at 15 min intervals. Results: Over the three sampling days, the average concentrations were, 8.46ppb, 0.63 ppb, 1.27ppb and 1.0ppb for benzene, toluene, ethylbenzene, and xylene respectively. The average cancer risk is 9.46E-03. In several cases, they were incidences of unacceptable risk for the cumulative exposure of all four BTEX compounds. Conclusion: This study adds to the body of knowledge on the Human Health Risk effects of urban BTEX pollution, furthermore focusing on the impact of urban BTEX on high risk personal such as informal traders, in Southern Africa.

Keywords: human health risk assessment, informal traders, occupational risk, urban BTEX

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Authors: Andreas Livera, Spyros Theocharides, Michalis Florides, Charalambos Anastassiou

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A main challenge in the quest for ensuring quality of operation, especially for photovoltaic (PV) systems, is to safeguard the reliability and optimal performance by detecting and diagnosing potential failures and performance losses at early stages or before the occurrence through real-time monitoring, supervision, fault detection, and predictive maintenance. The purpose of this work is to present the functionalities and results related to the development and validation of a software platform for PV assets diagnosis and maintenance. The platform brings together proprietary hardware sensors and software algorithms to enable the early detection and prediction of the most common and critical faults in PV systems. It was validated using field measurements from operating PV systems. The results showed the effectiveness of the platform for detecting faults and losses (e.g., inverter failures, string disconnections, and potential induced degradation) at early stages, forecasting PV power production while also providing recommendations for maintenance actions. Increased PV energy yield production and revenue can be thus achieved while also minimizing operation and maintenance (O&M) costs.

Keywords: failure detection and prediction, operation and maintenance, performance monitoring, photovoltaic, platform, recommendations, predictive maintenance

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Authors: Abiodun Musbau Lawal, Benjamin Oladapo Olley

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Long Distance Truck Drivers (LDTDs) have been found to be a high-risk group in the spread of HIV/AIDS globally; perhaps, due to their high Sexual Risk Behaviours (SRBs). Interventions for reducing SRBs in trucking population have not been fully exploited. A quasi-experimental control group pretest-posttest design was used to assess the efficacy of psycho-education and behavioural skills training in reducing SRBs among LDTDs. Sixteen drivers rivers were randomly assigned into either experimental or control groups using balloting technique. A questionnaire was used as an instrument for data collection. Repeated measures t-test and independent t-test were used to test hypotheses. The intervention had a significant effect on the SRBs among LDTDs at post-test(t{7}=6.01, p<.01) and at followup (t{7}=6.42, p<.01). No significant difference in sexual risk behaviour of LDTDs at post-test and at follow-up stage. Similarly, intervention had significant effects on sexual risk behaviour at post-test (t {14}=- 4.69, p<.05) and at follow-up (t {14}= -9.56, p < .05) respectively. At post-test and follow-up stages, drivers in experimental group reported reduced SRBs than those in the control group. Drivers in an experimental group reported lower sexual risk behaviour a week after intervention as well as at three months follow-up than those in the control group. It is concluded that HIV/AIDS preventive intervention that provides the necessary informational and behavioural skills content can significantly impact long distance truck drivers sexual risk behaviours.

Keywords: HIV/AIDS interventions, long distance truck drivers, Nigeria, sexual risk behaviours

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Authors: Yusarina Mat-Isa, Zuraidah Mohd-Sanusi, Mohd-Nizal Haniff, Paul A. Barnes

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In view that money laundering has become eminent for banking institutions, it is an obligation for the banking institutions to adopt a risk-based approach as the integral component of the accepted policies on anti-money laundering. In doing so, those involved with the banking operations are the most critical group of personnel as these are the people who deal with the day-to-day operations of the banking institutions and are obligated to form a judgement on the level of impending risk. This requirement is extended to all relevant banking institutions staff, such as tellers and customer account representatives for them to identify suspicious customers and escalate it to the relevant authorities. Banking institutions staffs, however, face enormous challenges in identifying and distinguishing money launderers from other legitimate customers seeking genuine banking transactions. Banking institutions staffs are mostly educated and trained with the business objective in mind to serve the customers and are not trained to be “detectives with a detective’s power of observation”. Despite increasing awareness as well as trainings conducted for the banking institutions staff, their competency in assessing money laundering risk is still insufficient. Several gaps have prompted this study including the lack of behavioural perspectives in the assessment of money laundering risk in the banking institutions. Utilizing experimental approach, respondents are randomly assigned within a controlled setting with manipulated situations upon which judgement of the respondents is solicited based on various observations related to the situations. The study suggests that it is imperative that informed judgement is exercised in arriving at the decision to proceed with the banking services required by the customers. Judgement forms a basis of opinion for the banking institution staff to decide if the customers posed money laundering risk. Failure to exercise good judgement could results in losses and absorption of unnecessary risk into the banking institutions. Although the banking institutions are exposed with choices of automated solutions in assessing money laundering risk, the human factor in assessing the risk is indispensable. Individual staff in the banking institutions is the first line of defence who are responsible for screening the impending risk of any customer soliciting for banking services. At the end of the spectrum, the individual role involvement on the subject of money laundering risk assessment is not a substitute for automated solutions as human judgement is inimitable.

Keywords: banking institutions, experimental approach, money laundering, risk assessment

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Authors: Seba Mohanty, Jitendra Mahakud

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Capital ratio is one of the major indicators of the stability of the commercial banks. Pertinent to its pervasive importance, over the years the regulators, policy makers focus on the maintenance of the particular level of capital ratio to minimize the solvency and liquidation risk. In this context, it is very much important to identify the relationship between capital and risk and find out the factors which determine the capital ratios of commercial banks. The study examines the relationship between capital and risk of the commercial banks operating in India. Other bank specific variables like bank size, deposit, profitability, non-performing assets, bank liquidity, net interest margin, loan loss reserves, deposits variability and regulatory pressure are also considered for the analysis. The period of study is 1997-2015 i.e. the period of post liberalization. To identify the impact of financial crisis and implementation of Basel II on capital ratio, we have divided the whole period into two sub-periods i.e. 1997-2008 and 2008-2015. This study considers all the three types of commercial banks, i.e. public sector, the private sector and foreign banks, which have continuous data for the whole period. The main sources of data are Prowess data base maintained by centre for monitoring Indian economy (CMIE) and Reserve Bank of India publications. We use simultaneous equation model and more specifically Two Stage Least Square method to find out the relationship between capital and risk. From the econometric analysis, we find that capital and risk affect each other simultaneously, and this is consistent across the time period and across the type of banks. Moreover, regulation has a positive significant impact on the ratio of capital to risk-weighted assets, but no significant impact on the banks risk taking behaviour. Our empirical findings also suggest that size has a negative impact on capital and risk, indicating that larger banks increase their capital less than the other banks supported by the too-big-to-fail hypothesis. This study contributes to the existing body of literature by predicting a strong relationship between capital and risk in an emerging economy, where banking sector plays a majority role for financial development. Further this study may be considered as a primary study to find out the macro economic factors which affecting risk and capital in India.

Keywords: capital, commercial bank, risk, simultaneous equation model

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Authors: Prashant Verma

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Commercial banks are facing immense pressure, including financial disintermediation, interest rate volatility and digital ways of finance. Retaining an existing customer is 5 to 25 less expensive than acquiring a new one. This paper explores customer churn prediction, based on various statistical & machine learning models and uses under-sampling, to improve the predictive power of these models. The results show that out of the various machine learning models, Random Forest which predicts the churn with 78% accuracy, has been found to be the most powerful model for the scenario. Customer vintage, customer’s age, average balance, occupation code, population code, average withdrawal amount, and an average number of transactions were found to be the variables with high predictive power for the churn prediction model. The model can be deployed by the commercial banks in order to avoid the customer churn so that they may retain the funds, which are kept by savings bank (SB) customers. The article suggests a customized campaign to be initiated by commercial banks to avoid SB customer churn. Hence, by giving better customer satisfaction and experience, the commercial banks can limit the customer churn and maintain their deposits.

Keywords: savings bank, customer churn, customer retention, random forests, machine learning, under-sampling

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Authors: Mohsen Shirani, Shadi Asadzandi, Micaela Demichela

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This paper presents the results of a study to assess crucial aspects and the strength of the scientific basis of a typically interdisciplinary, applied field: food supply chain risk assessment research. Our approach is based on an advanced scientometrics analysis with novel elements to assess the influence and dissemination of research results and to measure interdisciplinary. This paper aims to describe the quantity and quality of the publication trends in food supply chain risk assessment. The population under study was composed of 266 articles from database web of science. The results were analyzed based on date of publication, type of document, language of the documents, source of publications, subject areas, authors and their affiliations, and the countries involved in developing the articles.

Keywords: food supply chain, risk assessment, scientometrics, web of science

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Authors: Zohreh Khojasteh-Ghamari, Takashi Irohara

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One of the efficient ways in supply chain risk management is avoiding the interruption in Supply Chain (SC) before it occurs. Although the majority of the organizations focus on their first-tier suppliers to avoid risk in the SC, studies show that in only 60 percent of the disruption cases the reason is first tier suppliers. In the 40 percent of the SC disruptions, the reason is downstream SC, which is the second tier and lower. Due to the increasing complexity and interrelation of modern supply chains, the SC elements have become difficult to trace. Moreover, studies show that there is a vital need to better understand the integration of risk and visibility, especially in the context of multiple objectives. In this study, we propose a multi-objective programming model to avoid disruption in SC. The objective of this study is evaluating the effect of downstream SCV on managing supply chain risk. We propose a multi-objective mathematical programming model with the objective functions of minimizing the total cost and maximizing the downstream supply chain visibility (SCV). The decision variable is supplier selection. We assume there are several manufacturers and several candidate suppliers. For each manufacturer, our model proposes the best suppliers with the lowest cost and maximum visibility in downstream supply chain. We examine the applicability of the model by numerical examples. We also define several scenarios for datasets and observe the tendency. The results show that minimum visibility in downstream SC is needed to have a safe SC network.

Keywords: downstream supply chain, optimization, supply chain risk, supply chain visibility

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Authors: Rachel deCatanzaro, Madeline Austen, Ken Tuininga, Kathy St. Laurent, Christina Rohe

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In Canada, the federal Species at Risk Act (SARA) provides protection for wildlife species at risk and a national legislative framework for the conservation or recovery of species that are listed as endangered, threatened, or special concern under Schedule 1 of SARA. Key aspects of the federal species at risk program include the development of recovery documents (recovery strategies, action plans, and management plans) outlining threats, objectives, and broad strategies or measures for conservation or recovery of the species; the identification and protection of critical habitat for threatened and endangered species; and working with groups and organizations to implement on-the-ground recovery actions. Environment Canada’s progress on the development of recovery documents and on the identification and protection of critical habitat in Ontario will be presented, along with successes and challenges associated with on-the ground implementation of recovery actions. In Ontario, Environment Canada is currently involved in several recovery and monitoring programs for at-risk bird species such as the Loggerhead Shrike, Piping Plover, Golden-winged Warbler and Cerulean Warbler and has provided funding for a wide variety of recovery actions targeting priority species at risk and geographic areas each year through stewardship programs including the Habitat Stewardship Program, Aboriginal Fund for Species at Risk, and the Interdepartmental Recovery Fund. Key research needs relevant to the recovery of species at risk have been identified, and include: surveys and monitoring of population sizes and threats, population viability analyses, and addressing knowledge gaps identified for individual species (e.g., species biology and habitat needs). The engagement of all levels of government, the local and international conservation communities, and the scientific research community plays an important role in the conservation and recovery of species at risk in Ontario– through surveying and monitoring, filling knowledge gaps, conducting public outreach, and restoring, protecting, or managing habitat – and will be critical to the continued success of the federal species at risk program.

Keywords: conservation biology, habitat protection, species at risk, wildlife recovery

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Authors: Lina Najafian, Hamidreza Vakilifard

Abstract:

The present study focused on the relationship between the quality of accruals and non-systematic risk. The independent study variables included the ability of accruals, the information content of accruals, and amount of discretionary accruals considered as accruals quality measures. The dependent variable was non-systematic risk based on the Fama and French Three Factor model (FFTFM) and the capital asset pricing model (CAPM). The control variables were firm size, financial leverage, stock return, cash flow fluctuations, and book-to-market ratio. The data collection method was based on library research and document mining including financial statements. Multiple regression analysis was used to analyze the data. The study results showed that there is a significant direct relationship between financial leverage and discretionary accruals and non-systematic risk based on FFTFM and CAPM. There is also a significant direct relationship between the ability of accruals, information content of accruals, firm size, and stock return and non-systematic based on both models. It was also found that there is no relationship between book-to-market ratio and cash flow fluctuations and non-systematic risk.

Keywords: accruals quality, non-systematic risk, CAPM, FFTFM

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Authors: O. O. Olawusi-Peters, K. I. Adejugbagbe

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The concentration of heavy metal (Cd, Pb, Fe, Zn, Cu) in Clarias gariepinus collected from fish markets; Fanibi (Station I) and Fiwasaye (Station II) in Akure metropolis, Ondo state, Nigeria were investigated to ascertain the safety for the consumers. 60 samples were collected from the two markets in three batches (I, II, III) for a period of six months and analyzed for heavy metals in the gills and muscles of the fish. Also, the Health Risk Index (HRI) was used to determine the health risk of these metals to the consumer. The results showed that the investigated metal concentration was higher in station I than station II, except Pb having higher concentration in station II than station I. In both stations, the highest concentration of Fe was recorded in the gills (12.60 ± 1.51; 6.94 ± 1.38) and muscles (3.72 ± 0.09; 3.86 ± 0.33) of samples in batch I. Also, the HRI revealed that consumption of Clarias gariepinus from these study areas did not pose any health risk (HRI < 1). In addition, concentrations of the heavy metals were all below the permissible limits recommended by FAO/WHO.

Keywords: health risk index, heavy metals, clarias gariepinus, akure metropolis, fish monger

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Authors: Saurabh Kumar

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In the fiercely competitive landscape of e-commerce, understanding and mitigating customer churn has become paramount for sustainable business growth. This paper presents a thorough investigation into the application of machine learning techniques for churn prediction in e-commerce, aiming to provide actionable insights for businesses seeking to enhance customer retention strategies. We conduct a comparative study of various machine learning algorithms, including traditional statistical methods and ensemble techniques, leveraging a rich dataset sourced from Kaggle. Through rigorous evaluation, we assess the predictive performance, interpretability, and scalability of each method, elucidating their respective strengths and limitations in capturing the intricate dynamics of customer churn. We identified the XGBoost classifier to be the best performing. Our findings not only offer practical guidelines for selecting suitable modeling approaches but also contribute to the broader understanding of customer behavior in the e-commerce domain. Ultimately, this research equips businesses with the knowledge and tools necessary to proactively identify and address churn, thereby fostering long-term customer relationships and sustaining competitive advantage.

Keywords: customer churn, e-commerce, machine learning techniques, predictive performance, sustainable business growth

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Authors: Eun-Chan Kim, Jeong-Hwan Oh, Seung-Guk Lee

Abstract:

Billions of tones of ballast water including various aquatic organisms are being carried around the world by ships. When the ballast water is discharged into new environments, some aquatic organisms discharged with ballast water may become invasive and severely disrupt the native ecology. Thus, International Maritime Organization (IMO) adopted the Ballast Water Management Convention in 2004. Regulation A-4 of the convention states that a government in waters under their jurisdiction may grant exemptions to any requirements to ballast water management, but only when they are granted to a ship or ships on a voyage or voyages between specified ports or locations, or to a ship which operates exclusively between specified ports or locations. In order to grant exemptions, risk assessment should be conducted based on the guidelines for risk assessment developed by the IMO. For the risk assessment, it is essential to collect the relevant information and establish a database system. This paper studies the database system for ballast water risk assessment. This database consists of the shipping database, ballast water database, port environment database and species database. The shipping database has been established based on the data collected from the port management information system of Korea Government. For the ballast water database, ballast water discharge has only been estimated by the loading/unloading of the cargoes as the convention has not come into effect yet. The port environment database and species database are being established based on the reference documents, and existing and newly collected monitoring data. This database system has been approved to be a useful system, capable of appropriately analyzing the risk assessment in the all ports of Korea.

Keywords: ballast water, IMO, risk assessment, shipping, environment, species

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Authors: Lowanika Victor Tibane, David Mamba

Abstract:

Human body, animals, and plants depend on certain essential metals in permissible quantities for their survival. Excessive metal concentration may cause severe malfunctioning of the organisms and even fatal in extreme cases. Because of gold mining in the Witwatersrand basin in South Africa, enormous untreated mine dumps comprise elevated concentration of essential trace elements. Elevated quantities of trace metal have direct negative impact on the quality of soil for different land use types, reduce soil efficiency for plant growth, and affect the health human and animals. A total of 21 subsoil samples were examined using inductively coupled plasma optical emission spectrometry and X-ray fluorescence methods and the results elevated men concentration of Fe (36,433.39) > S (5,071.83) > Cu (1,717,28) > Mn (612.81) > Cr (74.52) > Zn (68.67) > Ni (40.44) > Co (9.63) > P (3.49) > Mo > (2.74), reported in mg/kg. Using various contamination indices, it was discovered that the sites surveyed are on average moderately contaminated with Co, Cr, Cu, Mn, Ni, S, and Zn. The ecological risk assessment revealed a low ecological risk for Cr, Ni and Zn, whereas Cu poses a very high ecological risk.

Keywords: essential trace elements, soil contamination, contamination indices, toxicity, descriptive statistics, ecological risk evaluation

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Authors: Rupesh K. Chaudhary, Narinder P. Jain, Rajesh Mahajan, Rajat Manchanda

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Introduction: Delirium is a complex, multifactorial neuropsychiatric syndrome comprising a broad range of cognitive and neurobehavioral symptoms. In critically ill patients, it may develop secondary to multiple predisposing factors. Although it can be transient and irreversible but if left untreated may lead to long term cognitive dysfunction. Early identification and assessment of risk factors usually help in appropriate management of delirium which in turn leads to decreased hospital stay, cost of therapy and mortality. Aim and Objective: Aim of the present study was to estimate the incidence of delirium using a validated scale in medical ICU patients and to determine the associated risk factors and outcomes. Material and Method: A prospective study in an 18-bed medical-intensive care unit (ICU) was undertaken. A total of 357 consecutive patients admitted to ICU for more than 24 hours were assessed. These patients were screened with the help of Confusion Assessment Method for Intensive Care Unit -CAM-ICU, Richmond Agitation and Sedation Scale, Screening Checklist for delirium and APACHE II. Appropiate statistical analysis was done to evaluate the risk factors influencing mortality in delirium. Results: Delirium occurred in 54.6% of 194 patients. Risk of delirium was independently associated with a history of hypertension, diabetes but not with severity of illness APACHE II score. Delirium was linked to longer ICU stay 13.08 ± 9.6 ver 7.07 ± 4.98 days, higher ICU mortality (35.8% % vs. 17.0%). Conclusion: Our study concluded that delirium poses a great risk factor in the outcome of the patient and carries high mortality, so a timely intervention helps in addressing these issues.

Keywords: delirium, risk factors, outcome, intervention

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Authors: Haïfa Ben Mna, Ayed Added

Abstract:

To evaluate the trace metals contamination status in the Gulf of Tunis, forty one sediment samples were analyzed using different approaches. According to certain contamination and ecological risk indices (Contamination Factor, Geoaccumulation index and Ecological risk index), Hg has the highest contamination level while pollution by Ni, Pb, Cd and Cr was absent. The highest concentrations of trace metals were found in sediments collected from the offshore and coastal areas located opposite the main exchange points with the gulf particularly, the Mejerda and Meliane Rivers, the Khalij Channel, Ghar El Melh and El Malah lagoons, Tunis Lake and Sebkhat Ariana. However, further ecological indices (Potential ecological risk index, Toxic unit and Mean effect-range median quotient) and comparison with sediment quality guidelines suggest that in addition to Mercury, Cr, Pb and Ni concentrations are detrimental to biota in both the offshore and areas near to the exchange points with the gulf. Moreover, in these areas the results from sequential extraction and individual contamination factor calculation pointed to the mobility and bioavailability of Cr, Pb and Ni.

Keywords: sediment, trace metals, contamination assessment, ecological risk, Tunis gulf

Procedia PDF Downloads 79