MAM
Different modes of transportation covered in marine insurance
You shipped a batch of high-value machinery overseas. However, on its way, a high wave crashes into the vessel mid-ocean, damaging not only the hull but also soaking your entire consignment. A few days later, you despatch the consignment again, but this time, the truck carrying the cargo from the port meets with an accident, damaging your goods. Now, as your cargo suffers loss after loss, you must be wondering which insurance to purchase. The answer is marine insurance, which extends coverage to various transportation modes.
Different modes of transportation under marine insurance
The three different modes of transportation that marine insurance covers are:
Sea transportation
Sea transportation involves the movement of cargo via ships and vessels across oceans and seas. Businesses prefer sea routes for international shipments, particularly for goods such as electronics or commodities, due to their cost-effectiveness and suitability for transporting large quantities. Under marine insurance for sea transportation, the insurer covers the following:
• The policy covers hull damage from grounding. That means if the vessel accidentally hits the seashore and results in a dent or misalignment of the hull structure, the insurer will pay for repairs.
• If the insured ship collides with another vessel and damages the cargo, navigation system, or hull under the third-party liability coverage provision in the policy, the insurer will compensate for the loss.
• If a fire breaks out on board due to faulty wiring, combustion of goods, or machinery overheating, the insurer will compensate for the resultant loss to the engine room, deck, and adjacent containers. However, a claim will only be approved if the cause of the fire is found to be unintentional and without negligence.
• While delay alone is not covered, if it causes perishable goods to deteriorate and the delay is because of a covered peril, such as a collision or a storm, the insurer compensates for the loss.
• During trans-shipment, when the cargo is moved from one ship to another, and incidents like container slippage, damage due to misaligned lifts, or exposure of cargo to seawater occurs, the insurer will offer compensation.
Air transportation
Air transportation involves using aircraft to move goods from one place to another. Although costly, it is ideal for time-sensitive deliveries where speed is crucial. It is also perfect for transporting perishable goods. The marine insurance for air transportation covers the following situations:
• The policy covers damage that occurs during the loading and unloading of goods from the aircraft, including cases involving broken conveyor belts, misaligned loaders, or mishandling by ground staff. However, it does not cover damage caused by poor packing of the cargo.
• If the aircraft carrying your shipment diverts mid-route due to technical or weather issues and the delay causes perishable cargo to spoil, the insurer will pay for the incurred losses.
• The event of pilferage, also known as partial theft by ground staff or baggage handlers, is covered. To qualify for such claims, it is essential that the cargo be properly inspected and verified and that the results are documented.
• If the airline mistakenly ships your cargo to the wrong destination and it gets lost, stolen, or damaged in the process, marine insurance will compensate for the value of the goods.
• If cargo is stolen from secure airport storage areas or while awaiting customs clearance, the policy compensates the declared value of the shipment. The coverage extends to thefts occurring inside bonded terminals.
Land transportation
Land transportation is ideal for delivering goods within domestic borders and involves vehicles such as trucks, lorries, vans, and even railways. If you have purchased marine single transit insurance for such transportation, the policy will cover the following:
• The policy covers damage to cargo during transit caused by collisions, overturns, and crashes. However, if the damage is intentional or the goods being transported are illegal, no compensation will be provided.
• If cargo is stolen or forcibly taken from the vehicle while in transit, the insurer compensates for the loss. This applies to both highway thefts and hijackings, where goods are forcibly removed.
• The policy covers accidental damage to goods during loading or unloading processes at warehouses, depots, or roadside stops. The coverage extends to damage caused by mishandling, dropping, or crushing incidents during the loading and unloading process.
• If the goods spoil or become worthless due to unavoidable delays, such as those caused by accidents or strikes that block transit routes, the insurer will cover the loss.
• The policy covers damage during inspections, customs checks, or government-authorised examinations en route.
Conclusion
Marine insurance covers sea, air, road, and land transport. The policy extends coverage to incidents like collisions, theft, fire, pilferage, and accidental damage during loading or delays. Whether your cargo travels across oceans, flies in the air or moves by road within the country, marine insurance ensures your goods are financially protected at every step of the journey.
Digital
GUEST COLUMN: How AI is restructuring distributor and retailer motivation models
From incentives to intelligence, AI is redefining how brands engage channel partners
MUMBAI: Artificial intelligence is rapidly transforming how brands engage with their most critical yet often overlooked stakeholders: distributors, retailers, and last-mile influencers. For Abhinav Jain, co-founder and CEO of Almonds Ai, this shift marks a fundamental departure from traditional, transaction-led incentive models toward behaviour-driven, data-intelligent ecosystems. In this piece, Jain examines how AI is enabling brands to decode partner motivations, predict engagement patterns, and deliver personalised, scalable experiences—ultimately redefining channel relationships from transactional exchanges to long-term growth partnerships.
Across many sectors, there is increasing recognition that motivating those who bring products to market (distributors, retailers, last-mile influencers) poses a growing challenge.
Brands continue to invest significant marketing and digital resources to consumers, yet in many countries and the vast majority of emerging economies, these types of consumer-focused investment areas have had little impact on ultimate product delivery. Rather, it is still the case that traditional retail continues to make up most products sold.
So why is it that the systems built around motivating these channels have yet to evolve?
For decades, distributor and retailer engagement revolved around static schemes – quarterly targets, volume-based rewards, and occasional trade promotions. These programs were designed around transactions, not behaviour. The assumption was simple: if incentives increase, performance will follow.
Now, with the advent of artificial intelligence, the definition of performance is being challenged.
With the development of artificial intelligence, businesses can move beyond simply creating loyalty based on transactional-based models and toward models built on behaviours, the behaviours of channel partners that are intrinsic to their motivations in engaging with particular brands. As a result, the means by which businesses develop relationships within their distribution network are starting to evolve; thus, ultimately changing how brands interact with those within their distribution network.
Assessing engagement: Transitioning from transactional- to behavioural intelligence
Traditional loyalty systems refer to transactional activity (sales data). Although this data is valuable and important, it only provides a partial view of engagement across the channel partner.
For example, a retailer may have a high frequency of sales of a product, but their lack of engagement with the manufacturer would not reflect that they have true loyalty toward that brand. Conversely, a retailer who actively participates in training programmes, acts as brand advocates, and is engaged in learning with the supplier would exhibit more profound levels of loyalty but would have been invisible based on historical incentive programmes.
Artificial intelligence allows for the identification of behaviours that help to address this gap. Brands are able to use a variety of engagement data points, participate in learning programs, respond to communications, redeem behaviour and track platform use behaviour in order to identify motivation through behaviour.
McKinsey has stated that companies that leverage advanced analytics for their sales and distribution functions can achieve as much as a 15-20 per cent increase in productivity due to increased awareness of their behavioural trends throughout their networks.
This visibility of behavioural patterns within channel ecosystems can be transformational to brands as they can now view how partners engage on their path to purchasing products, instead of just measuring the sales revenue generated by those purchases.
Predicting motivations, not just measuring performance
Possibly, the largest contribution of Artificial Intelligence (AI) to helping brands engage with partners via channel ecosystems is its ability to predict future engagement versus simply measuring past performance.
Traditionally, brands only realised that a partner was disengaged (not likely to purchase products) once their sales performance had already declined. By then, the brand would have to use significant amounts of incentives or aggressive promotional activities to recovery their partner’s engagement level.
AI models can help organisations to detect early signs that a partner is becoming disengaged, such as declining participation in learning modules, declining interaction via the platform, or slower reward redemption rates. These indicators can help organisations to proactively engage with their partners before their sales performance begins to decline.
The practical application of AI and predictive analytics gives brands the ability to re-engage with their partners prior to their sales performance declines. For example, instead of developing and implementing broad-reaching incentive programs that provide a “one size fits all” incentive to all partners in an ecosystem, brands are able to develop targeted, engaging re-engagement programmes. This is how personalisation can be done on a large scale, such as across global distribution and retail networks.
The vast majority of distributor and retailer channels have thousands, if not millions, of individual channel partners. Historically, providing personalisation to such a large number of businesses has not been feasible.
However, with the advent of AI, personalisation at scale is becoming a reality.
Brands can now create tailored engagement journeys for all their partners, based on their partner profiles, through some combination of machine learning models and behavioural segmentation. For example, high-performing distributors might receive higher levels of leadership-based recognition and greater incentives to continue to grow. Emerging retailers, on the other hand, might be supported with training, onboarding rewards, and measurable performance milestones.
The shift towards personalisation of partner engagement echoes the direction that consumer marketing is already moving towards.
According to Salesforce’s report, over 70 per cent of customers expect personalisation in the way that brands engage with them. As such, there is a growing expectation for B2B ecosystems to have these same types of expectations from their channel partners.
Gamification and continuous engagement
AI is also radically changing how brands will engage with their channel partners through the use of gamification.
Many traditional incentive-based contests and leaderboards would spark temporary engagement among their participants, but they struggled to sustain engagement over time. With the use of AI, gamification mechanics are evolving dynamically based on historical and evolving participation patterns by their channel partners.
Challenges, rewards, and recognition structures can be modified continuously in order to sustain engagement with all of a brand’s partner segments. This will provide a greater opportunity to move away from episodic campaigns towards ongoing, continuous engagement experiences.
When channel partners receive motivation as part of their daily business activities through recognition, learning, and tracking their performance, long-term loyalty will be achieved.
Aligning motivation to broader impact
There is a growing trend within the channel ecosystem to integrate sustainability and socially responsible behaviours into the channel partner programmes of brands.
Increasingly, brands are motivating their partners to use sustainable practices in their operations, participate in sustainable practices like sustainability-related knowledge programmes, or promote products that are in line with their sustainability objectives.
Brands can use AI to monitor and measure these types of behaviours and incorporate them into their incentive frameworks so that brands can align their commercial objectives with broader social and environmental outcomes.
A shift in the way brands view their channel partners
AI is having the most significant impact on the way that brands are now viewing their channel partners, as it relates to the underlying philosophy of those fundamental relationships.
For the past several decades, many brands have viewed their channel partners as intermediaries in the supply chain. More and more brands are now beginning to view their channel partners as key ‘partners-in-growth,’ and their actions can have a direct impact on market performance.
In fact, all the channel ecosystems are using behavioural engagement platforms to design new models that reward not just transactional behaviour, but also create continuous engagement journeys for their partners, where their partners can receive recognition for their participation, learning, and continued engagement, thereby reinforcing long-term loyalty to the brand.
The future: Intelligent channel ecosystems
As we consider what the next phase of channel engagement may look like, many believe that it will be based on intelligent ecosystems, using AI to continuously monitor and adjust the engagement strategies used to engage their channel partners, in real time and based on the behaviours of those partners.
For brands operating in complex distribution networks, the ability to perform well will be determined both by whether products are available to their customers, as well as by the enthusiasm, expertise, and loyalty shown from each channel partner that represents the brand each and every day that they are working on behalf of the brand.
While AI clearly does not eliminate the human aspect of a brand’s relationship with its channel partners, it does allow brands to better understand and nurture that relationship.
In markets where the last mile will determine whether a sale is made, how one leverages the intelligence gained by using AI will ultimately be the difference between gaining a new, sustainable competitive advantage versus losing one.
