Why Does Shipping a Truck 100 Miles Cost the Same to Insure as 1,500?

Chris Kalinski spent about 20 years in logistics, cargo, and supply chain — building several companies, exiting a couple of them, and running a trucking carrier along the way. Complex supply chains in particular: pharmaceuticals, refrigerated freight, the kind of movement where things go wrong in expensive ways.

The insurance piece struck him as unsolved for as long as he worked around it. So after his last exit he did something unusual for a founder with a complaint about an industry: he went and worked inside it, taking a three-year consulting role on Munich Re’s marine cargo innovation team to see the other side. How insurance is managed, distributed, rated — the whole back end, inside and out.

Between those two vantage points he reached the conclusion that starts most companies: there is a better way to do this. That became Redkik.

In Episode 137 of InsurTechTalk, Chris and I covered why cargo pricing ignores the actual journey, how you deliver an insurance quote fast enough that nobody notices they bought insurance, and what becomes visible when you aggregate claims across carriers, brokers, and insurers that would otherwise never compare notes.

About Chris Kalinski

Chris Kalinski is the CEO of Redkik, a technology company providing embedded, per-shipment cargo insurance and back-end policy administration systems for large insurance brokers, carriers, and MGAs. Redkik is a pure technology play — it holds no binding authority itself and is deliberately agnostic across markets, brokers, and MGAs. Before founding it, Chris spent two decades in logistics and supply chain, founded and exited multiple companies, operated a trucking carrier, and spent three years on Munich Re’s marine cargo innovation team. He is based in Maryland and races sailboats competitively, including offshore ocean races.

The Static Pricing Problem

The core insight is easy to state and apparently very hard for the industry to fix.

• Cargo insurance is priced off large data sets and long historical experience, which makes underwriting robust but static
• The practical consequence: insuring a truckload from New York to San Francisco costs the same as New York to New Jersey. Same cargo, same price — distance and risk probability barely enter the calculation
• From the underwriter’s side this works fine and has worked for a very long time. From the buyer’s side it is simply not the right product
• COVID exposed how badly this fits, as supply chain volatility made the mismatch between static pricing and actual risk impossible to ignore

Chris hit this personally as a trucking operator. In that business every cost is variable and measured per mile — truck, trailer, fuel, driver, tolls, fuel tax. Everything except insurance. Which leaves an operator guessing whether to apportion insurance across projected annual miles or simply absorb it as a cost of doing business. Neither worked well for him.

He also framed the opportunity clearly: insurance is a substantial share of supply chain cost structure, and turning it from a cost driver into a revenue driver changes a company’s operating expenses immediately.

Instant Gratification as a Product Requirement

The second half of the diagnosis is about speed, and it has nothing to do with insurance mechanics.

• Modern commerce has trained everyone to click a button and get the thing — Amazon Prime, same afternoon if you are lucky
• The insurance alternative: call a broker, receive a paper form, maybe a website or an email form if you are lucky, play phone tag several times, and get an overpriced quote a week later
• Redkik’s answer is embedded quoting in 500 milliseconds, including sanction checks and policy checks
• The example Chris used: you schedule a shipment in Uber Freight, a button offers insurance for $30, you accept, check out in the same flow, and the load ships fully covered end to end
• Pricing is dynamic — Redkik runs risk probability on the individual transaction and prices to that specific shipment’s risk profile

His point about latency is worth isolating: 30 seconds is not good enough, let alone two minutes. The quote has to already be there at the moment someone is deciding how to ship.

Two Businesses, One System

Redkik runs two related lines:

• Embedded distribution — the instant per-shipment quoting described above, sitting inside the platforms where freight is actually booked
• Back-end policy administration — systems for large brokers, insurers, and MGAs who hold the underwriting intelligence and need an efficient way to deliver it

The architecture is multi-tenant, giving each participant their own instance governed by their own rules, which is how Redkik serves constituencies whose interests do not naturally align:

• Brokers care about what they manage and see — whether first notice of loss or referrals route to them
• Insurance markets need aggregate exposure, risk profiles, and underwriting intelligence
• Underwriters keep authority over pricing, deductibles, and execution rule sets; Redkik configures the system but does not set the terms

On rating structures, Chris was refreshingly unfussy: bring spreadsheets, PDFs, however the rating is assembled — Redkik turns it into rule sets the underwriters then control.

What $14 Trillion of Insured Value Makes Visible

Over roughly two and a half years, Redkik’s system has quoted insured values north of $14 trillion. That volume turns into a different kind of product.

• Participants can opt into anonymized data trending across the network
• The example Chris gave: a single warehouse shows isolated shortage claims across a dozen insurers, several brokers, and many trucking carriers — JB Hunt, Uber Freight, and others. To any one of them, a couple of damaged boxes is just the cost of doing business
• Aggregated, the picture changes: 37 claims in one warehouse between 8am and noon is not noise, it is a problem with a root cause
• Redkik runs a system it calls ALARM — active loss ratio management — surfacing monthly which zip code, warehouse, route, commodity, or trade lane is running higher loss frequency, and is in the process of commercializing it beyond the accounts it already runs it for

This is the part I find genuinely interesting: no single participant can see the pattern, because each one only holds their slice. The aggregator sees it immediately.

War Rates and the Missing Link

Asked how conflict in the Middle East — Houthi attacks, threats to the Strait of Hormuz, rerouting around Africa instead of through Suez — flows through to insurance, Chris described a gap I did not expect.

• Longer transit times and port congestion change the risk profile substantially. A thousand ships waiting at Singapore is a different exposure than twenty at Baltimore
• Every insurer has war rates, but they are applied manually or retroactively: the policy says that passing through a war zone triggers a percentage uplift after the fact
• The missing piece is that insurers do not know where the ships are actually going. Vessels are tracked — that data exists — but what is missing is the link between a given vessel and which insured cargo is aboard it
• On a single vessel, a great many insurers may cover a great many containers. Reconstructing who is on risk for which container on which ship is enormous manual effort
• Embedded booking closes that loop: when the container is booked onto the vessel and insurance is applied at the point of sale, the system already knows the container, the vessel, the route, and that sanction checks passed

The forward-looking version, which Redkik holds a global patent for, is risk-probability-based pricing: adjust price to actual conditions — storms, weather, traffic patterns, routing — rather than a broad assumption of risk. Applied to war routing, that means quoting a defined uplift for going through a contested corridor and a lower rate for going around, potentially offsetting the cost of the longer voyage. Insurance pricing then starts steering supply chain behavior rather than merely reacting to it.

An Industry Changing Tech Together

One aside stuck with me. Chris noted that the insurance industry last went through a wholesale technology transition roughly 25 years ago — which is why so many participants are on the same generation of systems today. What is happening now is that same collective migration happening again, all at once, across an industry this size.

The Closing Lesson: Control Your Finance People

Asked for a failure and the lesson from it, Chris did not hedge. At his trucking carrier, the person running the finances ran away with the finances.

The lesson he drew is about where delegation stops:

• Too much trust is never good — keep control over the core functions that can kill the business if they go wrong
• He delegates broadly, with the explicit exception of finance, which reports directly to him: no decisions without a conversation, with weekly reviews of accounts and cash flow
• His COO — his wife — executes across everything else, with fully aligned interests
• Most Redkik employees hold some form of ownership, which he sees as the structural version of the same idea

Key Takeaways

• Cargo insurance priced on historical aggregates ignores the actual journey, leaving buyers paying identically for wildly different risk
• In a business where every other cost is variable per mile, a fixed insurance cost is an accounting problem operators cannot cleanly solve
• Embedded insurance has a latency requirement, not just a UX requirement — the quote must exist at the moment of the shipping decision, which for Redkik means 500 milliseconds
• Aggregated claims data across otherwise disconnected carriers, brokers, and insurers exposes root causes no single participant can see
• War rates are applied retroactively because insurers cannot link vessels to the specific insured cargo aboard them — a data-plumbing gap, not an underwriting one
• Priced dynamically, insurance stops being a passive cost and starts influencing routing decisions in the supply chain
• Delegate widely, but keep finance reporting directly to you