Billion In Losses Research Articles

Crops under stress: can we mitigate the impacts of climate change on agriculture and launch the 'Resilience Revolution'?

Climate change is altering our environment, subjecting multiple agroecosystems worldwide to an increased frequency and intensity of abiotic stress conditions such as heat, drought, flooding, salinity, cold and/or their potential combinations. These stresses impact plant growth, yield and survival, causing losses of billions of dollars to agricultural productivity, and in extreme cases they lead to famine, migration and even wars. As the rate of change in our environment has dramatically accelerated in recent years, more research is urgently needed to discover and develop new ways and tools to increase the resilience of crops to different stress conditions. In this theme issue, new studies addressing the molecular, metabolic, and physiological responses of crops and other plants to abiotic stress challenges are discussed, as well as the potential to exploit these mechanisms in biotechnological applications aimed at preserving and/or increasing crop yield under our changing climate conditions.This article is part of the theme issue 'Crops under stress: can we mitigate the impacts of climate change on agriculture and launch the 'Resilience Revolution'?'

Detecção e Classificação de Documentos contendo Macros Maliciosas com base em Processamento de Linguagem Natural

AbstractMacros are functions written in Visual Basic for automation withinMS Office documents. On the one hand, macros bring many facilitiesto home users and organizations. On the other hand, they havealso stimulated the arise of macro viruses (malware that exploitmacros to infect users loading compromised documents, spreadsheets,and presentations). Those viruses may delete data and stealinformation, and have been causing losses of billions of dollars inglobal attacks. Although more prevalent in the 1990s and 2000s,macro viruses resurged in the last decade and continue to threatcurrent MS Windows/Office users. In this article, we present a naturallanguage processing-based pipeline to detect macros in MSOffice documents and classify them in malicious or benign. Usingbyte2vec as document representation, we outperform the state-ofthe-art in Macro detection, reaching over 99% of Precision-RecallArea Under Curve (PRAUC) metric for four out of seven evaluatedclassifiers (and over 98% PRAUC in the remaining three classifiers).

African Problem - African Solution: An Examination of the Application of the Ubuntu Conflict Resolution Systems to Prevailing Conflicts in Africa: A Case Study of the Democratic Republic of Congo and Namibia's Tension

The conflict within the Democratic Republic of Congo is demonstrably violent and primarily localized in the eastern region, formerly known as Zaire. In contrast, Namibia experiences tension between native and non-native African populations arising from inequitable land accumulation by the minority white-German population, which holds the potential for violent escalation. The protracted conflict in the eastern region of the Congo, which resulted in the deaths of millions of Africans and the loss of billions in property, along with the societal tension in Namibia, both trace their origins unequivocally to the Berlin Conference of 1884-1885. To mitigate the violent and deadly conflict in Congo and the potential for violent escalation in Namibia’s tension, we propose the establishment of a centuries-old framework designed to provide permanent peace resolutions, given that these conflicts are occurring on African soil, in a broader context, we see it as an African problem thus requires primarily African solution – The Ubuntu system on conflict resolution – While the United Nations peace system has been employed to resolve numerous global conflicts, including those within the Congo, its efficacy in the Congolese context has been demonstrably ineffective. Thus, we argue that ‘Ubuntu,’ an African system of conflict resolution, has the potential to resolve both direct violence and structural violence that creates tensions not just in the case study countries but in the whole of Africa and beyond, as the system has no specific tribal or religious affiliation, it is just a human-centric philosophy that sees all humans as equals irrespective of races or social status. Lastly, this paper adopts a qualitative research design to explore the application of the Ubuntu conflict resolution system in addressing conflict.

Medicine Traceability Using QR Code

Counterfeit medicines pose a significant threat to public health, resulting in estimated annual losses of billions of dollars worldwide. Ensuring the authenticity and traceability of medicines throughout the supply chain is crucial to prevent counterfeiting. This research proposes a medicine traceability system using Quick Response (QR) codes. Our system utilizes QR codes to store and retrieve information about medicines, enabling real-time tracking and verification. We evaluate the effectiveness of our system in a pilot study involving pharmaceutical manufacturers, wholesalers, and retailers. Results show that our QR code-based system improves medicine traceability, reduces counterfeiting risks, and enhances overall supply chain efficiency. Our findings have important implications for healthcare policymakers, pharmaceutical companies, and regulatory agencies seeking to ensure the safety and authenticity of medicines. Index Terms— Authentication, Counterfeit Detection, Medicine Tracking, Pharmaceutical Supply Chain, QR Code Technology, Traceability Systems.

A Survey on ML Techniques for Multi-Platform Malware Detection: Securing PC, Mobile Devices, IoT, and Cloud Environments.

Malware has emerged as a significant threat to end-users, businesses, and governments, resulting in financial losses of billions of dollars. Cybercriminals have found malware to be a lucrative business because of its evolving capabilities and ability to target diverse platforms such as PCs, mobile devices, IoT, and cloud platforms. While previous studies have explored single platform-based malware detection, no existing research has comprehensively reviewed malware detection across diverse platforms using machine learning (ML) techniques. With the rise of malware on PC or laptop devices, mobile devices and IoT systems are now being targeted, posing a significant threat to cloud environments. Therefore, a platform-based understanding of malware detection and defense mechanisms is essential for countering this evolving threat. To fill this gap and motivate further research, we present an extensive review of malware detection using ML techniques with respect to PCs, mobile devices, IoT, and cloud platforms. This paper begins with an overview of malware, including its definition, prominent types, analysis, and features. It presents a comprehensive review of machine learning-based malware detection from the recent literature, including journal articles, conference proceedings, and online resources published since 2017. This study also offers insights into the current challenges and outlines future directions for developing adaptable cross-platform malware detection techniques. This study is crucial for understanding the evolving threat landscape and for developing robust detection strategies.

Impact of Aflatoxin on food security, health, and economics in Kenyan Peanuts: A Systematic Review

Aflatoxin contamination presents a significant threat to food security and public health in Kenya, particularly in relation to Arachis hypogaea (peanuts), a staple source of protein and income for many households. This systematic review examines the multifaceted issues associated with aflatoxins in peanuts, encompassing their nutritional benefits, health risks, and economic ramifications. Aflatoxins, toxic metabolites produced by fungi such as Aspergillus flavus, jeopardize human health, contributing to conditions like aflatoxicosis and liver cancer, particularly affecting vulnerable populations. In Kenya, the prevalence of aflatoxin contamination in peanuts is exacerbated by high humidity and inadequate post-harvest practices, leading to diminished product quality and significant health hazards. Despite regulatory measures, such as the maximum allowable aflatoxin levels established by the Kenya Bureau of Standards, many contaminated products continue to enter the market, highlighting gaps in enforcement. The economic burden of aflatoxin contamination is profound, with losses attributed to health care costs, decreased productivity, and rejected crop sales, particularly impacting smallholder farmers. It is estimated that the agricultural sector incurs billions in losses, emphasizing the urgent need for effective educational initiatives and improved agricultural practices. Through a comprehensive analysis of existing literature, this review emphasizes the importance of enhancing public awareness and implementing robust food safety measures to mitigate aflatoxin risks. Ultimately, addressing these challenges is critical to improving nutritional outcomes, safeguarding health, and promoting economic stability in Kenya's agricultural landscape.

Histone H2A.Z Deacetylation and Dedifferentiation in Infarcted/Tip60-depleted Cardiomyocytes.

Myocardial infarction (MI) results in the loss of billions of cardiomyocytes (CMs), resulting in cardiac dysfunction. To re-muscularize injured myocardium, new CMs must be generated via renewed proliferation of surviving CMs. Approaches to induce proliferation of CMs after injury have been insufficient. Toward this end we are targeting the acetyltransferase Tip60, encoded by the Kat5 gene, based on the rationale that its pleiotropic functions combine to block CM proliferation at multiple checkpoints. We previously demonstrated that genetic depletion of Tip60 in a mouse model after MI reduces scarring, retains cardiac function, and activates the CM cell-cycle, although it remains unclear whether this culminates in the generation of daughter CMs. In order for pre-existing CMs in the adult heart to undergo proliferation, it has become accepted that they must first dedifferentiate, a process highlighted by loss of maturity, epithelial to mesenchymal transitioning (EMT), and reversion from fatty acid oxidation to glycolytic metabolism, accompanied by softening of the myocardial extracellular matrix (ECM). Based on recently published findings that Tip60 induces and maintains the differentiated state of hematopoietic stem cells and neurons via site-specific acetylation of the histone variant H2A.Z, we assessed levels of acetylated H2A.Z and dedifferentiation markers after depleting Tip60 in CMs post-MI. We report that genetic depletion of Tip60 from CMs after MI results in the near obliteration of acetylated H2A.Z in CM nuclei, accompanied by the altered expression of genes indicative of EMT induction, ECM softening, decreased fatty acid oxidation, and depressed expression of genes that regulate the TCA cycle. In accord with the possibility that site-specific acetylation of H2A.Z maintains adult CMs in a mature state of differentiation, CUT&Tag revealed enrichment of H2A.ZacK4/K7 in genetic motifs and in GO terms respectively associated with CM transcription factor binding and muscle development/differentiation. Along with our previous findings, these results support the notion that Tip60 has multiple targets in CMs that combine to maintain the differentiated state and prevent proliferation.

Applying Deep Learning to Mobile Home and Flood Insurance Risk Evaluation

Flooding from storm surges and precipitation, high winds from storms and tornadoes, and wildfires are now responsible for about 90% of all catastrophe-related insurance losses. The increasing intensity and frequency of these perils means more and more billing, claims, and losses are incurred by property insurance because the buildings are not built to withstand natural disasters. The increasing number of wildfires in the USA and other parts of the world, with their long tail of severity, makes wildfire risk evaluation and property holders aware of this growing peril even more critical. The day of judgment is coming when insurance companies will need to prove that areas they have written hurricanes and water damage insurance are not a loss risk afterward. During intense flooding events, inland and coastal flooding along with wind damage create billions in losses with the vast majority of claims coming from flood insurance. Residential property underwriting has to change moving forward. Businesses need to recognize the true cost of a policy before flood damage occurs. Insurance companies must take action for underwriting properties and businesses that are prone to higher frequency and severity of residential and business interruption losses due to flooding, high winds from hurricanes or tornadoes, and wildfires. In addition, the insurance market must adapt to the next stage of climate risk management tied to the financial ramifications of the growing frequency and severity of the perils across the globe. This is important since property insurance is the primary means of transferring the risk of a peril.

Doppler weather radars as a game changer in desert locust swarm tracking

Desert locusts, notorious for their ruinous impact on agriculture, threaten over 20% of Earth’s landmass, prompting billions in losses and global food scarcity concerns. With billions of these locusts invading agrarian lands, this is no longer a thing of the past. Recent invasions, such as those in India, where losses reached US$ 3 billion in 2019-20 alone, underscore the urgency of action. By tapping into the existing Doppler Weather Radar (DWR) infrastructure, originally deployed for meteorological applications, the present study demonstrates a systematic approach to distinctly identify and track concentrations of desert locust swarms in near real-time using single and dual-polarization radars. Findings reveal the potential to establish early warning systems with lead times of 5–7 h and spatial coverage of approximately 100 km, empowering timely mitigation efforts. In stark contrast to satellite imagery, often constrained by resolution limitations that impede swarm detection, DWRs offer unparalleled spatial and temporal resolution, rendering them indispensable tools in this endeavour. Harnessing radar capabilities within the current infrastructure, unleashes unparalleled ecological monitoring potential and fundamentally transform practices in managing migratory pest management practices. Embracing these technological advancements becomes imperative to safeguard agricultural landscapes, uphold global food security, and effectively mitigate the ecological threats posed by migratory pests.

IMPACTS OF CLIMATE CHANGE AND FLOOD DISASTERS IN PAKISTAN

Ecosystems and human life depends on availability of water. Pakistan holds its 4th position for consuming of freshwater in the world. Pakistan is considered a water-stressed country and is rapidly approaching water scarcity. Pakistan may face climate change challenges in terms of related to water. The quality of drinking water is likewise degrading rapidly. Since independence in 1947, Pakistan has witnessed 29 floods up to 2023, including the first ever flood in 1950 and almost every second year in 1950, 1955, 1956, 1957, 1959, 1973, 1975, 1976, 1977, 1978, 1981, 1983, 1984, 1988, 1992, 1994, 1995, and 2010 up to 2023. There is still no exact data available on the loss to the economy. In 2022, the country is witnessing more than $15 billion in losses. In 2010 calamity, around 1,600 peoples were killed and 38,600 km2 inundated, almost $10 billion (855 billion PKR) was damaged and 578 billion needed for the reconstruction of flood damages. Efficient climate change policy can support the management of water resources as well as boost economic growth, boost agricultural output, and meet food demand. Climate change's effects on expanding cities, rising wages, and growing populations will combine to create a world where water demand will rise exponentially while availability will become more limited and unpredictable.

IMPACTS OF CLIMATE CHANGE AND FLOOD DISASTERS IN PAKISTAN

Ecosystems and human life depends on availability of water. Pakistan holds its 4th position for consuming of freshwater in the world. Pakistan is considered a water-stressed country and is rapidly approaching water scarcity. Pakistan may face climate change challenges in terms of related to water. The quality of drinking water is likewise degrading rapidly. Since independence in 1947, Pakistan has witnessed 29 floods up to 2023, including the first ever flood in 1950 and almost every second year in 1950, 1955, 1956, 1957, 1959, 1973, 1975, 1976, 1977, 1978, 1981, 1983, 1984, 1988, 1992, 1994, 1995, and 2010 up to 2023. There is still no exact data available on the loss to the economy. In 2022, the country is witnessing more than $15 billion in losses. In 2010 calamity, around 1,600 peoples were killed and 38,600 km2 inundated, almost $10 billion (855 billion PKR) was damaged and 578 billion needed for the reconstruction of flood damages. Efficient climate change policy can support the management of water resources as well as boost economic growth, boost agricultural output, and meet food demand. Climate change's effects on expanding cities, rising wages, and growing populations will combine to create a world where water demand will rise exponentially while availability will become more limited and unpredictable.

Genome-wide association mapping identifies novel SNPs for root nodulation and agronomic traits in chickpea.

The chickpea (Cicer arietinum L.) is well-known for having climate resilience and atmospheric nitrogen fixation ability. Global demand for nitrogenous fertilizer is predicted to increase by 1.4% annually, and the loss of billions of dollars in farm profit has drawn attention to the need for alternative sources of nitrogen. The ability of chickpea to obtain sufficient nitrogen via its symbiotic relationship with Mesorhizobium ciceri is of critical importance in determining the growth and production of chickpea. To support findings on nodule formation in chickpea and to map the genomic regions for nodulation, an association panel consisting of 271 genotypes, selected from the global chickpea germplasm including four checks at four locations, was evaluated, and data were recorded for nodulation and 12 yield-related traits. A genome-wide association study (GWAS) was conducted using phenotypic data and genotypic data was extracted from whole-genome resequencing data of chickpea by creating a hap map file consisting of 602,344 single-nucleotide polymorphisms (SNPs) in the working set with best-fit models of association mapping. The GWAS panel was found to be structured with sufficient diversity among the genotypes. Linkage disequilibrium (LD) analysis showed an LD decay value of 37.3 MB, indicating that SNPs within this distance behave as inheritance blocks. A total of 450 and 632 stringent marker-trait associations (MTAs) were identified from the BLINK and FarmCPU models, respectively, for all the traits under study. The 75 novel MTAs identified for nodulation traits were found to be stable. SNP annotations of associated markers were found to be related to various genes including a few auxins encoding as well as nod factor transporter genes. The identified significant MTAs, candidate genes, and associated markers have the potential for use in marker-assisted selection for developing high-nodulation cultivars after validation in the breeding populations.

Evaluating the Reparative Potential of Secretome from Patient-Derived Induced Pluripotent Stem Cells during Ischemia–Reperfusion Injury in Human Cardiomyocytes

During a heart attack, ischemia causes losses of billions of cells; this is especially concerning given the minimal regenerative capability of cardiomyocytes (CMs). Heart remuscularization utilizing stem cells has improved cardiac outcomes despite little cell engraftment, thereby shifting focus to cell-free therapies. Consequently, we chose induced pluripotent stem cells (iPSCs) given their pluripotent nature, efficacy in previous studies, and easy obtainability from minimally invasive techniques. Nonetheless, using iPSC secretome-based therapies for treating injured CMs in a clinical setting is ill-understood. We hypothesized that the iPSC secretome, regardless of donor health, would improve cardiovascular outcomes in the CM model of ischemia–reperfusion (IR) injury. Episomal-generated iPSCs from healthy and dilated cardiomyopathy (DCM) donors, passaged 6–10 times, underwent 24 h incubation in serum-free media. Protein content of the secretome was analyzed by mass spectroscopy and used to treat AC16 immortalized CMs during 5 h reperfusion following 24 h of hypoxia. IPSC-derived secretome content, independent of donor health status, had elevated expression of proteins involved in cell survival pathways. In IR conditions, iPSC-derived secretome increased cell survival as measured by metabolic activity (p < 0.05), cell viability (p < 0.001), and maladaptive cellular remodelling (p = 0.052). Healthy donor-derived secretome contained increased expression of proteins related to calcium contractility compared to DCM donors. Congruently, only healthy donor-derived secretomes improved CM intracellular calcium concentrations (p < 0.01). Heretofore, secretome studies mainly investigated differences relating to cell type rather than donor health. Our work suggests that healthy donors provide more efficacious iPSC-derived secretome compared to DCM donors in the context of IR injury in human CMs. These findings illustrate that the regenerative potential of the iPSC secretome varies due to donor-specific differences.

Rainfall analysis of the May 2021 southeastern Texas and southern Louisiana flood

ABSTRACT This paper analyzes the heavy rainfall on 16–20 May 2021 across southeastern Texas and southern Louisiana. In Louisiana, five fatalities were attributed to the event and > $1 billion in losses. The rainfall was caused by two slow-moving, mesoscale convective vortices that concentrated precipitation south of Port Arthur, TX, Lake Charles, LA, and Baton Rouge, LA, in 6 to 12-hour periods. Using calibrated radar data, the Storm Precipitation Analysis System estimated 6-h rainfall totals of 254–362 mm south of Lake Charles, surpassing 200–500-year average recurrence intervals (ARI) for those locations, with an isolated area receiving 367.5 mm, equating to a > 800-year ARI. In East Baton Rouge Parish, LA, 203–268 mm was estimated in 6-h (200–500-year ARI), with an isolated area receiving 274 mm, equivalent to a 750-year ARI. A comparison of the May 2021 and August 2016 events, which both affected southern Louisiana, is made using a depth-area-duration analysis. While the forcing mechanisms differed, 1–6 h rainfall depths were similar at 1 –25,900 km2. The May 2021 event exceeded rainfall depths produced by the August 2016 event for 2–6 h durations for area sizes of 1–388 km2, highlighting the precipitation intensity produced by the May 2021 event.

Characterization of the Dominant Stages at Which Gas Flaring Is Introduced: Impacts and Policy Options to Ameliorate Them

Information on associated gas flaring in the Niger Delta is analyzed to characterize the various stages in the lifecycle of an oil exploration and production facility through which gas flaring is introduced into an area, leading to ecological, health, and economic impacts, and possible policies and implementation strategies for the reduction of the flared gas are offered. Gas flaring is currently occurring at a rate of 5318 million m3 per year in the Niger Delta region. The impacts of gas flaring on the ecological, human, and economic systems include poor air quality, acid rain, and soil degradation. Other impacts include decreased crop yield, increased incidences of respiratory diseases amongst inhabitants in the area, and losses of billions of USD yearly in economic costs. Three dominant stages in the introduction of gas flaring are characterized in this study, using the concept of the management of the invasion of non-native species into an ecosystem and it is determined that the cheapest method of minimizing gas flaring is to incorporate mitigation measures during the design stage of the oil exploration/production facility, rather than after flaring has commenced, as is the common emphasis. During the early periods of oil production, gas flaring is largely localized, and the gas utilization measures can still be implemented to good effect. However, once the facility is established, gas flaring becomes pervasive, stretching kilometers beyond the flare points. Current policies like the imposition of flare-out years on the oil producers have helped, but they have been insufficient as the intensity of gas flaring in the region continues at double the average global levels. Working with relevant stakeholders, a realistic flare-out deadline should be agreed upon, clear and specific gas flaring legislation should be drawn up that includes measures to mitigate gas flaring for each proposed oil facility, and proper data collection and management services would enable the implementation of the policies to be based on robust evidence. These policies would shift the costs of gas flaring away from the inhabitants of the region back to the operators of the facilities that are the sources of the flares.

Load Shedding and Its Crippling Effect on The South African Economy: An Entrepreneurial Perspective

The country has experienced industry shutdowns, decreased productivity, educational setbacks, increased unemployment rates, and negative healthcare outcomes. Load-shedding in South Africa is primarily caused by inadequate maintenance, internal mismanagement, corruption, and a lack of skills. This issue has had a significant impact on small businesses, as they often lack the necessary resources to handle power surges, equipment damage, and the costs associated with replacing stock. This paper explores how load-shedding has impacted the South African economy from an entrepreneurial perspective. The research is qualitative and exploratory in nature, and it was found that load-shedding has had a significant impact on businesses' finances, resources, and performance. Load-shedding in South Africa has had a severe impact on the daily lives of people, causing disruptions in businesses, households, and the overall economy. Eskom, the primary supplier of energy in South Africa, has been facing significant challenges in meeting the growing demand for electrical energy, leading to job losses, decreased productivity, and a loss of billions of rands. Small businesses have been particularly affected, with an estimated 75% of them failing after being operational for less than three years due to load-shedding. To ensure small businesses have electricity to operate during load-shedding it is recommended that small businesses adopt alternative energy sources like solar power to increase the businesses’ independence and mitigate the effects of load-shedding. The South African government should also encourage and support small businesses to collaborate with successful renewable energy companies.

Detection dogs fighting transnational narcotraffic: performance and challenges under real customs scenario in Brazil.

Narcotic Detection Dogs (NDDs) are essential tools in the fight against drug trafficking, acting with high precision and improving efficiency at border posts. When trained efficiently, these dogs can detect a great variety of compounds, such as cocaine, marijuana and its derivatives, and synthetic drugs, among others. Most of the knowledge on canine detection processes and efficiency has been determined in experimentally controlled conditions, but narcotic seizures detected by dogs in realistic anti-drug operations have not yet been critically determined in a Country with continental dimensions such as Brazil. This study aimed to evaluate the data set concerning the performance, operations, efficiency, and success rate of NDDs used by the Brazilian Customs Authority (Aduana) in the fight against drug trafficking. Narcotic seizure rates increased in luggage and packages detected by NDDs working at border crossings from 2010 to 2020, with an estimated value of over US$ 2 billion in losses to the cocaine drug trafficking business. NDD units also increased most narcotic groups seized in the same period. The number of NDDs and anti-drug operations, and Customs Border Post (CBP) influenced the rates of drugs seized. NDDs provided an increase of 3,157 kg/animal of drugs seized for every new dog introduced into the inspection systems.

Epigenetic Modifications of White Blood Cell DNA Caused by Transient Fetal Infection with Bovine Viral Diarrhea Virus.

Bovine viral diarrhea virus (BVDV) infections cause USD 1.5-2 billion in losses annually. Maternal BVDV after 150 days of gestation causes transient fetal infection (TI) in which the fetal immune response clears the virus. The impact of fetal TI BVDV infections on postnatal growth and white blood cell (WBC) methylome as an index of epigenetic modifications was examined by inoculating pregnant heifers with noncytopathic type 2 BVDV or media (sham-inoculated controls) on Day 175 of gestation to generate TI (n = 11) and control heifer calves (n = 12). Fetal infection in TI calves was confirmed by virus-neutralizing antibody titers at birth and control calves were seronegative. Both control and TI calves were negative for BVDV RNA in WBCs by RT-PCR. The mean weight of the TI calves was less than that of the controls (p < 0.05). DNA methyl seq analysis of WBC DNA demonstrated 2349 differentially methylated cytosines (p ≤ 0.05) including 1277 hypomethylated cytosines, 1072 hypermethylated cytosines, 84 differentially methylated regions based on CpGs in promoters, and 89 DMRs in islands of TI WBC DNA compared to controls. Fetal BVDV infection during late gestation resulted in epigenomic modifications predicted to affect fetal development and immune pathways, suggesting potential consequences for postnatal growth and health of TI cattle.

Detailed seismic structure beneath the earthquake zone of Yogyakarta 2006 (Mw ∼6.4), Indonesia, from local earthquake tomography

Detailed seismic structure beneath the earthquake zone of Yogyakarta 2006 (Mw ∼6.4), Indonesia, from local earthquake tomography

Predicting automobile insurance fraud using classical and machine learning models

Insurance fraud claims have become a major problem in the insurance industry. Several investigations have been carried out to eliminate negative impacts on the insurance industry as this immoral act has caused the loss of billions of dollars. In this paper, a comparative study was carried out to assess the performance of various classification models, namely logistic regression, neural network (NN), support vector machine (SVM), tree augmented naïve Bayes (NB), decision tree (DT), random forest (RF) and AdaBoost with different model settings for predicting automobile insurance fraud claims. Results reveal that the tree augmented NB outperformed other models based on several performance metrics with accuracy (79.35%), sensitivity (44.70%), misclassification rate (20.65%), area under curve (0.81) and Gini (0.62). In addition, the result shows that the AdaBoost algorithm can improve the classification performance of the decision tree. These findings are useful for insurance professionals to identify potential insurance fraud claim cases.