CARGOSHAKTI · LOSS INTELLIGENCE · CROSS-CLIENT CORPUS STUDY

Most cargo isn't lost to the sea. It's broken by handling.

Across 326,000 anonymised claims, the largest driver of loss is not fire, theft or storm — it is damage during loading, unloading and road transit. Loss is not an act of God. It is an operations problem, and operations problems are preventable.

78%
of all loss value comes from just two causes — handling damage and jerks & jolts in transit. Perils of the sea barely register.
The evidence base

A corpus large enough for patterns to become facts.

326,113
claim records analysed
₹2,729 Cr
total paid loss examined
49 sheets
across 11 client / sector books
4.9 yrs
of claim history, 2021–2026

Party names — carriers, shippers, consignees — are coded. Everything else you see here is real: the actual causes, commodities, corridors and seasons that drive loss.

What actually breaks cargo

Two causes carry three-quarters of the loss.

Ranked by value paid, the picture is unambiguous: handling — loading, unloading, jerks and jolts — dwarfs every catastrophic peril. This is the single most important fact for prevention, because handling is controllable in a way that weather is not.

1
Damage during loading / unloading
60.3%123,944 claims
2
Jerks / jolts in transit
17.7%116,374 claims
3
Accidental damage
5.5%2,928 claims
4
Fresh / rain-water damage
2.0%6,932 claims
5
Sea-water damage
1.9%56 claims
6
Denting
1.4%17,712 claims
7
Breakage
1.0%9,837 claims
8
Improper handling in transit
0.8%7,705 claims
Handling and shock account for 78% of loss. Sea-water damage — the archetypal “marine peril” — accounts for 1.9%, from just 56 claims. The money is in the warehouse and on the road, not on the water.
What's in the box

Fragile, high-value electronics dominate the loss book.

The commodities driving loss are consumer electronics and white goods — displays, refrigerators, air-conditioners, washing machines. High unit value and shock-sensitivity is exactly the profile that turns a jolt into a claim.

Top commodities by loss value

Share of total paid loss
Displays — LED / LCD / monitors 68% combined
₹1,863 Cr
Refrigerators
₹169 Cr · 6.2%
Air-conditioners
₹103 Cr · 3.8%
Washing machines
₹99 Cr · 3.6%
Microwave / other white goods
₹21 Cr

Where the money hides: the tail

The median claim is small; the largest few carry almost everything.
Median claim
₹18,749
Mean claim (pulled up by the tail)
₹99,275
95th percentile
₹1,00,978
Loss above the 95th percentile
78%
Loss from the largest 1% of claims
68%

A risk model tuned to the average claim would miss the money entirely. The tail is the book.

Where loss concentrates

A handful of corridors carry outsized value.

Most movement is domestic road freight, and loss clusters on specific lanes. A single high-severity corridor can carry more value than thousands of routine intracity claims combined — the signature of concentrated, addressable risk.

1
Bengaluru → Mangalore181 claims · ₹5.2 Cr average ticket — extreme severity
₹934 Crtotal paid
2
Bengaluru → Vijayawada1,674 claims
₹394 Crtotal paid
3
Shanghai → Pune42 claims · import lane
₹46 Crtotal paid
4
Pune → Pune7,068 claims · intracity / last-mile
₹44 Crtotal paid
5
Busan → Greater Noida166 claims · import lane
₹36 Crtotal paid

The Bengaluru→Mangalore lane is a study in itself: only 181 claims, but a ₹5.2 crore average ticket — a small number of very large losses, exactly where survey and control effort earns its keep.

The cross-client moat

Risk is an intersection — carrier × commodity × corridor.

A carrier is rarely simply good or bad. Coded here as A / B / C, the three highest-loss carriers show sharply different profiles by commodity and lane — the kind of pattern only a pooled, cross-client corpus can reveal, and the raw material for a carrier-specific risk rating.

Carrier (coded)On displaysOn refrigeratorsOn washing machinesWorst corridor
Carrier A₹1,211 Cr
60,382 claims
₹28 Cr₹51 CrBengaluru→Mangalore
₹934 Cr
Carrier B₹308 Cr
750 claims — high severity
——Bengaluru→Vijayawada
₹307 Cr
Carrier C₹86 Cr
28,883 claims — high frequency
——Noida→Noida
₹19 Cr

Carrier B and Carrier C tell opposite stories on the same commodity: B has few claims but enormous severity; C has tens of thousands of small ones. The same rating would be wrong for both — which is why the intersection, not the carrier alone, is the unit of risk.

Season shapes the loss — handling damage peaks in winter

Loading / unloading damage by season, paid value
Winter peak
₹1,009 Cr · 26,782 claims
Spring
₹451 Cr · 26,034 claims
Jerks & jolts — autumn peak
₹133 Cr · 34,774 claims
Jerks & jolts — monsoon
₹126 Cr · 31,638 claims
What the evidence supports

Four findings that reshape how cargo risk is priced and prevented.

Prevent handling, not perils

78% of loss is handling and shock — loading supervision, lashing, packaging and shock-monitoring beat catastrophe cover. The controllable causes are the expensive ones.

Electronics need their own regime

Displays and white goods dominate the book. Fragility-graded packaging warranties and pre-dispatch condition capture target the value where it actually sits.

Rate the intersection

Carrier-alone ratings are blunt. The signal lives in carrier × commodity × corridor cells — and a pooled cross-client corpus already holds them at volume.

The tail and the lane

68% of loss is the largest 1% of claims, concentrated on a few high-severity corridors. Survey and control effort aimed there returns more than any broad SOP.