Motor is the volume engine (≈34% of GWP). The honest split: Third-Party is IRDAI-tariffed (rates frozen since FY20) and runs an underwriting profit; Own-Damage is free-priced, competitive and loss-making. Vehicle-class mix, loss ratio by sub-line, the claims / garage-network machine, and the fraud & SIU exposure sitting inside the OD loss ratio.
Motor writes ₹1,886 Cr of GWP at a 69% blended loss ratio. The story the P&L tells is a pricing one: tariffed TP profits while free-priced OD loses — so the motor turnaround is an OD-underwriting and claims-cost job. PC/2W/CV sub-splits are modeled (the company does not disclose them).
The single most important read on motor: who sets the price. TP rates are set by IRDAI (and frozen since FY20); OD is priced in a competitive market — which is exactly why one makes money and the other doesn't.
Own-damage is written in a competitive, market-priced segment — it ran an underwriting loss (≈ −₹75 Cr) in FY25. The levers are OD repricing, the Plastic Repair Program (repair-not-replace) and i-ViSS video self-survey to compress claim cost.
Third-party rates are IRDAI-tariffed and frozen since FY20 — TP ran an underwriting profit (≈ +₹84 Cr). Carries the regulatory Motor-TP obligation and Solatium Fund; long-tail MACT bodily-injury is the fraud-exposed tail (SIU focus). A future TP tariff revision is the biggest single upside.
Read it: motor is roughly balanced overall (69% blended), but that hides a ₹856 Cr OD book losing money subsidised by a ₹1,030 Cr tariffed TP book making it. Fixing motor = fixing OD, because TP pricing is not in the company's hands.
Two-Wheeler is high-volume / low-premium; Private Car is premium-heavy; Commercial Vehicle is premium-dense and the most loss-prone. Sub-split is modeled (peer-benchmarked).
Bars = GWP by vehicle class (Σ ₹1,886 Cr). Avg premium = GWP ÷ in-force policies. CV carries the highest loss ratio; 2W the largest policy count.
Six sub-lines (PC / 2W / CV × OD / TP). Green = disciplined; wine = loss-leaning. The OD lines and CV sit at the top.
How fast motor claims move, and how much comes in digitally rather than over a counter.
The tools that bend the OD loss ratio — repair-not-replace and survey-less settlement.
Plastic Repair Program. Repair-not-replace on plastic parts (bumpers, panels) cuts OD claim severity — a direct lever on the 75% OD loss ratio.
i-ViSS / video self-survey. Survey-less remote inspection of minor damage settles small OD claims in hours and removes the garage-collusion window (a fraud-adjacent saving).
FG ConGo + Digital Claims Archival. AI motor-claims app (OCR, smart forms) with ~80% less physical documentation — faster, cheaper, more auditable.
Motor is the largest fraud-exposed general-insurance line — staged-accident rings, inflated repairs, fake third-party (MACT) injury, phantom vehicles and backdated e-policies. Catching it pre-payment is a direct OD-loss-ratio lever. Sample drawn from the same SIU caseload as Fraud & SIU 360; portfolio savings are modeled.
FG ConGo + AI/ML scoring. The AI motor-claims app (OCR, smart forms) scores every claim; anything above the 0.75 threshold auto-routes to the SIU.
i-ViSS video self-survey. Survey-less inspection of minor OD damage removes the garage-collusion window.
IIB cross-insurer match. Catches phantom vehicles, fake / backdated e-policies and known-fraudster policyholders across insurers.
Network / link analytics. Surfaces organised staged-accident rings and repeat garage / agent clusters.
Red-flag rules + SIU field investigation. Rule triggers and on-ground investigation for high-value MACT bodily-injury and total-loss / salvage fraud.
Why it matters here: motor fraud sits inside the 75% OD loss ratio. Every rupee of leakage caught pre-payment is a direct OD-loss-ratio saving — the modeled fraud-savings goal (₹78 → ₹120 Cr) is one of the biggest single motor-turnaround levers.
Full SIU pipeline, detection mix & FMF-2025 readiness → Fraud & SIU 360