An Empirical Analysis of Marine Cargo Insurance – A Study on Customer’s Perspective

Marine insurance is little unique compared to the other insurances as it covers a wide range of risks linked to sea voyages, like damage of ships and goods, due to perils such as storms, fires, and theft (Huebner, n.d.). Marine cargo insurance requires a thorough knowledge of maritime law, vessel types, cargo specifics, and international regulations for safe transportation in global supply chains (Jain, 2021). Marine cargo insurance is vital for global trade, covering risks like false declarations, delays, damage, poor packaging, and operational oversights, all of which can lead to financial losses (Tseng et al., 2015). Common challenges include land traffic accidents, improper cargo arrangement, disputes over Bill of Lading, theft, commercial fraud, and shipping guarantee issues. These risks highlight the importance of comprehensive insurance coverage in mitigating potential financial losses and ensuring smooth operations in maritime trade.

LITERATURE REVIEW

The paper starts with a literature review focused on existing articles and academic theses in marine insurance, aiming to identify gaps in scholarly literature for further exploration. Diana and Ml (2022) analyse marine insurance's importance in ship construction, operation, and cargo management, emphasizing insurance and reinsurance's role in mitigating risks. Devadasan et al. (2020) discuss marine insurance's implications in India's financial sector, especially regarding multinational insurers and regulatory frameworks. Ravichandran (2001) explores trends in mutual P&I Clubs amidst industry shifts and competitive pressures. Huebner (n.d.) examines the US marine insurance landscape, highlighting trends like self-insurance. Bennett (2000) focuses on P&I Clubs' regulatory dynamics, emphasizing risk regulation and trust-building. Tseng et al. (2015) propose cargo damage risk management strategies in Taiwan's freight forwarding. Levy (2012) navigates historical and legal aspects of marine insurance, addressing legal complexities and disputes. Wong (1975) discusses legal challenges in containerized shipping, advocating for international standards. Brown (2012) explores policyholders' attitudes toward insurance companies, while Kavitha (2012) delves into customer perceptions in insurance, contributing to our understanding of marine insurance's regulatory, operational, and customer-centric aspects globally and regionally.

METHODOLOGY

The study is aimed to explore the perceptions of marine cargo insurance among diverse stakeholders like exporters, freight forwarders, and industry professionals. A sample of 40 respondents was chosen due to practical constraints, with data collection focusing on Cochin-based individuals. The data collection involved a structured questionnaire covering various aspects of marine cargo insurance such as respondent backgrounds, industry affiliations, experience levels, awareness of insurance terms, coverage needs, satisfaction with insurer communication, and views on online processes, technology's role, and a risk-ranking exercise. A total of 50 responses were received, of which 40 valid responses were analysed using descriptive analysis in SPSS. Charts, frequency tables, and mean values of Likert scale ratings were used due to the small sample size, providing insights into stakeholders' perceptions and highlighting areas for potential improvement in marine cargo insurance practices. The detailed Data analysis as follows

1. Organizations

The most common types of organizations based on the provided data are "Freight Forwarding" and "Exporter/Importer," each comprising 30.8% of the valid responses. “Clearing and Forwarding" and "Steamer Agent" are less common, with frequencies of 1 and 6, respectively. The "Other" category represents 20.5% of the valid responses, indicating a significant portion of organizations that do not fit into the specified categories. This analysis provides insights into the distribution of different types of organizations within the dataset and their relative frequencies.

2. Experience

The majority of individuals in the dataset have more than 8 years of experience, comprising 84.6% of the valid responses. The "4-8 years" category represents a smaller proportion, indicating that there are fewer individuals with mid-level experience compared to those with either less than 3 years or more than 8 years of experience.

This analysis provides insights into the distribution of experience levels within the dataset. It shows that the majority of individuals have extensive experience (more than 8 years), which can be valuable for understanding the expertise and composition of the group being studied.

3. Awareness

Source: Analysing the Primary Data

Overall, the descriptive statistics suggest that while there is variation in awareness levels among respondents (as indicated by the standard deviation), the average awareness level is relatively high (mean of 4.08). This is a positive indication that respondents generally have a good understanding of the terms and conditions of marine insurance, with some variation in the extent of their awareness.

4. Essentiality of Marine Cargo insurance

Source: Analysing the Primary Data

Overall, the descriptive statistics suggest a high level of agreement among respondents that marine cargo is an essential element, as indicated by the high mean rating and relatively low standard deviation.

This strong agreement implies that respondents view marine cargo as a crucial component within the context being surveyed.

5. Importance of Marine Cargo insurance to Specific risks

Source: Analysing the Primary Data

The mean rating of 4.85 indicates strong agreement among respondents regarding the necessity of specific coverage in marine insurance policies for tasks like theft, damage, loading/unloading incidents, or natural disasters. This suggests widespread support for tailored coverage. The low standard deviation of 0.366 signifies minimal variability in opinions, reinforcing the consensus on the importance of such coverage. A low standard deviation indicates that ratings are closely clustered around the mean, reflecting a clear consensus among respondents regarding the importance of addressing specific risks in marine insurance.

6. Communication and Support from Insurer

The descriptive statistics reveal that respondents' satisfaction with the communication and support from their insurer varies, with a moderate average satisfaction level. While the mean indicates overall satisfaction, the higher standard deviation suggests that some respondents have stronger positive or negative feelings about the communication and support provided. Insurers may use this information to identify areas for improvement in their communication and support strategies to enhance overall customer satisfaction.

7. Perceptions on Online Processing of Marine Cargo Insurance

The descriptive statistics indicate a range of opinions among respondents regarding whether online is a better process for obtaining marine insurance. While the mean leans towards agreement, the higher standard deviation suggests that opinions are more varied, with some respondents strongly supporting online methods while others strongly disagree.

Perceptions on online across Organization Level