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AI Use Cases

The AI and digital use cases across the insurance value chain — the real, named, live assets (LEO, FG ConGo, I-Assist OCR, i-ViSS, IRIS) alongside peer-benchmarked targets — each tied to the metric it moves: claims TAT, straight-through processing, fraud catch-rate and the loss ratio.

Generali Central Insurance Company Limited · FY25 (Mar'25, audited)
Mid-tier private multiline general insurer — Top-10 private (rank ~10)
2,644 employees · 167 branches · 21,000+ agents
🤖 Digital, AI & fraud controlStep 1 of 6 · the AI use-case portfolio: LEO · FG ConGo · I-Assist · i-ViSS · IRISFraud & SIU 360 ▶All journeys
🌐 Enterprise 360 modules· on AI Use CasesBrowse all 51 views ▾
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↗ Where this connects — act / drill across
🛰Control Tower· the towers the AI serves🛡Fraud & SIU 360· act on the fraud-scored cases🔁Claims & Renewals 360· speed the claims queue
● LiveBuilt forChief Marketing, Customer & Digital/AI· the AI roadmap & what's liveClaims / Underwriting / Fraud· the tool on each deskCEO / Board· AI as a combined-ratio lever

Each use case names the metric it moves and whether it is a verified live asset (V) or a modeled, peer-benchmarked target (M). The five live assets are real and nameable; every company-specific STP / TAT / fraud-save figure attached to a target is a benchmark, not a claimed actual. Today 87% of policies already issue digitally.

Data backing: ai_usecase (name · category · status · metric moved · current→target · source_tag V=real asset / M=modeled target) · kpi (digital issuance · loss ratio)
12
AI use cases
across the value chain
5
Live · verified
real, named assets
4
Piloting
in-flight
3
Planned
on the roadmap
5 · 7
Real vs modeled
V verified · M target
Legend: Verified live asset (V) Modeled / peer-benchmarked target (M) Live Piloting Planned
5 use cases · 3 live

Claims

Motor & health claims — faster, cheaper, more auditable settlement.

FG ConGo (Claims on the Go)

Live● Verified
Claims

In-house AI motor-claims app for surveyors — Smart Form, OCR, data services, Action Board, fuzzy search.

Moves · Motor claim TAT / accuracy
~1 day→hours

I-Assist OCR

Live● Verified
Claims

Health-claim bill OCR + auto-extraction, integrated to the claims system.

Moves · Health adjudication TAT
~6 days→3 days

i-ViSS (Video Self-Survey)

Live● Verified
Claims

Video-based, survey-less settlement of minor motor damage (from the i-MoSS motor settlement system).

Moves · Small-claim settlement time
hours→on-the-spot

AI Motor Photo-Assessment

PilotingModeled
Claims

Customer self-inspection photo/video AI damage estimate (InstaSpect / IDEAS-style).

Moves · Motor OD assessment time
hours→minutes

Health Auto-Adjudication

PlannedModeled
Claims

Straight-through cashless auto-adjudication for low-risk health claims (Amplify-Health-style).

Moves · Cashless STP %
not yet live→40% STP
1 use case · 0 live

Fraud

AI/ML scoring & network analytics on the ~8–10% claims leakage.

AI Fraud Scoring Engine

PilotingModeled
Fraud

ML fraud/FWA scoring + link/network analytics on claims (Shift-Technology-style, a proven Generali-group capability).

Moves · Fraud catch-rate
62%→+20–30% uplift
2 use cases · 0 live

Underwriting

Real-time risk selection & straight-through approval — a direct loss-ratio lever.

AI Underwriting (STP / auto-approval)

PilotingModeled
Underwriting

Real-time AI underwriting & auto-approval for retail health & motor (Smart-Health-Underwriting-style).

Moves · Auto-approval %
not yet live→70% auto-approved

Smart Health Underwriting

PlannedModeled
Underwriting

AI medical-risk triage for retail health — a direct lever on the health loss ratio.

Moves · Health loss ratio
99%→<94%
2 use cases · 1 live

Service

Self-serve & GenAI copilots that cut cost-to-serve.

LEO

Live● Verified
Service

GenAI WhatsApp chatbot (with Meta) — renewals, real-time claim status, instant health card, locate garages/hospitals, integrated UPI/card payments.

Moves · Query deflection / self-serve
~45% self-serve→65% self-serve

GenAI Service Copilot

PlannedModeled
Service

Agent/CSR GenAI copilot for servicing & grievance (Insurance-Samjho-style).

Moves · Cost-to-serve
not yet live→−20–30%
2 use cases · 1 live

Distribution

Agent self-issuance & renewal propensity across the book.

IRIS agent platform

Live● Verified
Distribution

Live agent self-issuance portal for Motor/Health/PA/Travel (Fire/Marine in pipeline).

Moves · Policy-issuance TAT / agent STP
87% digital→92% digital

AI Renewal-Propensity

PilotingModeled
Distribution

Propensity model to lift policy retention & cross-sell across the book.

Moves · Policy retention
82%→85%+
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