Policy Management Cloud-Native: Architettura API-First per Piattaforme Assicurative
Il sistema di gestione delle polizze (Policy Administration System, PAS) e il cuore pulsante di qualsiasi compagnia assicurativa. E il sistema che definisce cosa un cliente ha acquistato, per quanto tempo, a quale prezzo e con quali condizioni. Eppure, nella stragrande maggioranza delle compagnie assicurative italiane ed europee, questo sistema critico gira ancora su mainframe degli anni '90, con batch notturni che durano ore e API che non esistono o si riducono a file SFTP schedulati.
La transizione verso architetture cloud-native API-first non e solo una questione tecnologica: e una necessità competitiva. I nuovi operatori InsurTech lanciano prodotti in settimane invece di mesi, servono clienti in real-time e integrano dati da decine di fonti esterne. Il mercato InsurTech globale, valutato 5,3 miliardi di dollari nel 2024, crescera a oltre 132,9 miliardi entro il 2034 (CAGR 22%). Il 74% degli assicuratori tradizionali sta già investendo nella modernizzazione dei core system (Capgemini World InsurTech Report 2024).
In questo articolo costruiamo un sistema di policy management cloud-native da zero: dalla modellazione del dominio all'API design, dal lifecycle management delle polizze alle integrazioni con broker, canali digitali e sistemi regolamentari.
Cosa Imparerai
- Architettura API-first per policy administration cloud-native
- Modellazione del ciclo di vita completo di una polizza
- Design di REST API per quote, bind, endorse, cancel, renew
- Event sourcing e CQRS nel contesto assicurativo
- Integrazione con broker portals, e-commerce e intermediari
- Versioning delle polizze e gestione degli endorsement
- Pattern di testing per sistemi assicurativi complessi
1. Il Ciclo di Vita di una Polizza: Da Quote a Lapse
Prima di scrivere una sola riga di codice, dobbiamo comprendere il ciclo di vita completo di una polizza. Il modello standard del settore prevede questi stati principali:
Policy Lifecycle States
- QUOTED: Il cliente ha ricevuto un preventivo ma non ha ancora acquistato
- APPLICATION: L'applicazione e in fase di underwriting review
- BOUND: La copertura e attiva, in attesa di emissione formale
- IN_FORCE: Polizza attiva e pienamente efficace
- SUSPENDED: Copertura temporaneamente sospesa (es. mancato pagamento)
- RENEWED: Polizza rinnovata per un nuovo periodo
- CANCELLED: Polizza cancellata prima della scadenza naturale
- EXPIRED / LAPSED: Polizza giunta a scadenza naturale o decaduta
Ogni transizione di stato ha regole di business precise: chi può attivarla, quali validazioni sono richieste, quali eventi vengono generati, quali notifiche vengono inviate. Il codice deve esprimere queste regole in modo esplicito e testabile.
2. Domain Model: Entità Fondamentali
Un buon policy management system si basa su un domain model preciso. Ecco le entità fondamentali e le loro relazioni in Python con type annotations:
from dataclasses import dataclass, field
from datetime import date, datetime
from decimal import Decimal
from enum import Enum
from typing import Optional
from uuid import UUID, uuid4
class PolicyStatus(str, Enum):
QUOTED = "QUOTED"
APPLICATION = "APPLICATION"
BOUND = "BOUND"
IN_FORCE = "IN_FORCE"
SUSPENDED = "SUSPENDED"
RENEWED = "RENEWED"
CANCELLED = "CANCELLED"
EXPIRED = "EXPIRED"
class CoverageType(str, Enum):
LIABILITY = "LIABILITY"
COMPREHENSIVE = "COMPREHENSIVE"
COLLISION = "COLLISION"
PERSONAL_INJURY = "PERSONAL_INJURY"
PROPERTY = "PROPERTY"
BUSINESS_INTERRUPTION = "BUSINESS_INTERRUPTION"
@dataclass(frozen=True)
class Money:
"""Value object immutabile per importi monetari."""
amount: Decimal
currency: str = "EUR"
def __add__(self, other: "Money") -> "Money":
if self.currency != other.currency:
raise ValueError(f"Cannot add {self.currency} and {other.currency}")
return Money(self.amount + other.amount, self.currency)
def __mul__(self, factor: Decimal) -> "Money":
return Money(self.amount * factor, self.currency)
@dataclass(frozen=True)
class Coverage:
"""Una singola copertura assicurativa all'interno di una polizza."""
coverage_id: UUID
coverage_type: CoverageType
limit: Money # Massimale di indennizzo
deductible: Money # Franchigia
premium: Money # Premio per questa copertura
effective_date: date
expiry_date: date
is_active: bool = True
@dataclass
class PolicyHolder:
"""Il contraente/assicurato della polizza."""
party_id: UUID
first_name: str
last_name: str
fiscal_code: str # Codice fiscale IT
date_of_birth: date
email: str
phone: Optional[str]
address: dict # Indirizzo strutturato
@dataclass
class Endorsement:
"""Una modifica alla polizza originale (endorsement / appendice)."""
endorsement_id: UUID
policy_id: UUID
endorsement_type: str # ADD_COVERAGE, REMOVE_COVERAGE, CHANGE_LIMIT, etc.
effective_date: date
description: str
premium_adjustment: Money # Positivo = aumento, negativo = rimborso
previous_state: dict # Snapshot dello stato prima dell'endorsement
new_state: dict # Snapshot dello stato dopo l'endorsement
created_at: datetime = field(default_factory=datetime.utcnow)
@dataclass
class Policy:
"""Entità radice dell'aggregato polizza."""
policy_id: UUID
policy_number: str # Es. "AUTO-IT-2024-0001234"
product_code: str # Es. "AUTO_RC", "HOME_ALL_RISK"
status: PolicyStatus
holder: PolicyHolder
coverages: list[Coverage]
endorsements: list[Endorsement]
effective_date: date
expiry_date: date
annual_premium: Money
created_at: datetime
updated_at: datetime
# Metadata di distribuzione
channel: str # "DIRECT", "BROKER", "AGGREGATOR"
agent_code: Optional[str]
broker_code: Optional[str]
def total_premium(self) -> Money:
base = sum(
(c.premium for c in self.coverages if c.is_active),
start=Money(Decimal("0"))
)
adjustments = sum(
(e.premium_adjustment for e in self.endorsements),
start=Money(Decimal("0"))
)
return base + adjustments
def is_active(self) -> bool:
return self.status == PolicyStatus.IN_FORCE
def can_file_claim(self) -> bool:
today = date.today()
return (
self.is_active()
and self.effective_date <= today <= self.expiry_date
)
3. API Design: REST API per Policy Operations
Un'architettura API-first significa che le API sono la prima cosa che si progetta, prima ancora dell'implementazione. Il contratto API deve essere chiaro, versionato e compatibile con le aspettative del settore (ACORD standards, OpenAPI 3.1).
Di seguito la struttura delle principali API endpoint per un policy management service:
| Method | Endpoint | Operazione | Body / Response |
|---|---|---|---|
| POST | /v1/quotes | Genera un preventivo | QuoteRequest -> QuoteResponse |
| POST | /v1/quotes/{quoteId}/bind | Converte preventivo in polizza | BindRequest -> PolicyResponse |
| GET | /v1/policies/{policyId} | Recupera polizza | -> PolicyResponse |
| POST | /v1/policies/{policyId}/endorse | Emette endorsement | EndorseRequest -> EndorsementResponse |
| POST | /v1/policies/{policyId}/cancel | Cancella polizza | CancellationRequest -> PolicyResponse |
| POST | /v1/policies/{policyId}/renew | Rinnova polizza | RenewalRequest -> PolicyResponse |
| GET | /v1/policies/{policyId}/documents | Documenti polizza | -> DocumentListResponse |
Implementazione FastAPI con validazione Pydantic:
from fastapi import FastAPI, HTTPException, Depends, BackgroundTasks
from pydantic import BaseModel, Field, validator
from typing import Optional
from decimal import Decimal
from datetime import date
from uuid import UUID
import uuid
app = FastAPI(
title="Policy Management API",
version="1.0.0",
description="Cloud-native insurance policy management"
)
# --- Request/Response Models ---
class VehicleInfo(BaseModel):
plate: str = Field(..., pattern=r"^[A-Z]{2}[0-9]{3}[A-Z]{2}$|^[A-Z]{2}[0-9]{5}$")
make: str
model: str
year: int = Field(..., ge=1900, le=2026)
value: Decimal = Field(..., gt=0)
engine_cc: int
class QuoteRequest(BaseModel):
product_code: str = Field(..., pattern="^[A-Z_]+$")
holder_fiscal_code: str
vehicle: Optional[VehicleInfo]
effective_date: date
desired_coverages: list[str]
channel: str = Field(default="DIRECT")
@validator("effective_date")
def effective_date_not_past(cls, v: date) -> date:
if v < date.today():
raise ValueError("Effective date cannot be in the past")
return v
class CoverageQuote(BaseModel):
coverage_type: str
limit: Decimal
deductible: Decimal
annual_premium: Decimal
currency: str = "EUR"
class QuoteResponse(BaseModel):
quote_id: UUID
product_code: str
coverages: list[CoverageQuote]
total_annual_premium: Decimal
currency: str = "EUR"
valid_until: date
terms_version: str
class BindRequest(BaseModel):
payment_reference: str
holder_data: dict # Validated separately by KYC service
selected_coverages: list[str]
broker_code: Optional[str]
class PolicyResponse(BaseModel):
policy_id: UUID
policy_number: str
status: str
product_code: str
effective_date: date
expiry_date: date
annual_premium: Decimal
currency: str = "EUR"
created_at: str
# --- Service Layer ---
class PolicyService:
def __init__(self, repo, pricer, underwriter, event_bus):
self.repo = repo
self.pricer = pricer
self.underwriter = underwriter
self.event_bus = event_bus
async def create_quote(self, request: QuoteRequest) -> QuoteResponse:
# 1. Validate product exists
product = await self.repo.get_product(request.product_code)
if not product:
raise ValueError(f"Unknown product: {request.product_code}")
# 2. Score the risk
risk_score = await self.underwriter.score(request)
# 3. Calculate premium
coverages = await self.pricer.calculate(product, risk_score, request)
# 4. Persist quote with TTL
quote = await self.repo.save_quote(
product_code=request.product_code,
coverages=coverages,
valid_hours=72
)
return QuoteResponse(
quote_id=quote.id,
product_code=request.product_code,
coverages=coverages,
total_annual_premium=sum(c.annual_premium for c in coverages),
valid_until=quote.valid_until,
terms_version=product.terms_version
)
async def bind_policy(
self,
quote_id: UUID,
request: BindRequest,
background_tasks: BackgroundTasks
) -> PolicyResponse:
# 1. Retrieve and validate quote
quote = await self.repo.get_quote(quote_id)
if not quote or quote.is_expired():
raise ValueError("Quote expired or not found")
# 2. Final underwriting check
uw_result = await self.underwriter.final_check(quote, request.holder_data)
if uw_result.is_declined:
raise ValueError(f"Policy declined: {uw_result.reason}")
# 3. Create policy
policy = await self.repo.create_policy(quote, request, uw_result)
# 4. Async operations (non-blocking)
background_tasks.add_task(self._post_bind_workflow, policy)
return PolicyResponse(
policy_id=policy.id,
policy_number=policy.number,
status=policy.status,
product_code=policy.product_code,
effective_date=policy.effective_date,
expiry_date=policy.expiry_date,
annual_premium=policy.annual_premium.amount,
currency=policy.annual_premium.currency,
created_at=policy.created_at.isoformat()
)
async def _post_bind_workflow(self, policy):
"""Operazioni asincrone post-bind."""
await self.event_bus.publish("policy.bound", {"policy_id": str(policy.id)})
# Trigger: document generation, CRM update, payment setup
# --- API Routes ---
@app.post("/v1/quotes", response_model=QuoteResponse, status_code=201)
async def create_quote(
request: QuoteRequest,
service: PolicyService = Depends(get_policy_service)
):
try:
return await service.create_quote(request)
except ValueError as e:
raise HTTPException(status_code=422, detail=str(e))
@app.post("/v1/quotes/{quote_id}/bind", response_model=PolicyResponse, status_code=201)
async def bind_policy(
quote_id: UUID,
request: BindRequest,
background_tasks: BackgroundTasks,
service: PolicyService = Depends(get_policy_service)
):
try:
return await service.bind_policy(quote_id, request, background_tasks)
except ValueError as e:
raise HTTPException(status_code=422, detail=str(e))
4. Event Sourcing per l'Audit Trail Assicurativo
Il settore assicurativo ha requisiti stringenti di audit e tracciabilita: ogni modifica a una polizza deve essere tracciata in modo immutabile per ragioni normative (IVASS, EIOPA) e legali. L'event sourcing e il pattern architetturale più adatto a questo requisito.
Invece di aggiornare lo stato direttamente, ogni operazione sulla polizza genera un evento immutabile. Lo stato corrente e la proiezione di tutti gli eventi passati:
from dataclasses import dataclass
from datetime import datetime
from typing import Union
from uuid import UUID
# --- Policy Domain Events ---
@dataclass(frozen=True)
class PolicyQuoted:
event_type: str = "PolicyQuoted"
policy_id: UUID = None
quote_id: UUID = None
product_code: str = None
holder_id: UUID = None
annual_premium: dict = None # {amount, currency}
occurred_at: datetime = None
@dataclass(frozen=True)
class PolicyBound:
event_type: str = "PolicyBound"
policy_id: UUID = None
policy_number: str = None
effective_date: str = None
expiry_date: str = None
channel: str = None
agent_code: str = None
occurred_at: datetime = None
@dataclass(frozen=True)
class PolicyEndorsed:
event_type: str = "PolicyEndorsed"
policy_id: UUID = None
endorsement_id: UUID = None
endorsement_type: str = None
premium_adjustment: dict = None
occurred_at: datetime = None
@dataclass(frozen=True)
class PolicyCancelled:
event_type: str = "PolicyCancelled"
policy_id: UUID = None
cancellation_reason: str = None
cancellation_date: str = None
refund_amount: dict = None
requested_by: str = None # "HOLDER", "INSURER", "REGULATOR"
occurred_at: datetime = None
PolicyEvent = Union[PolicyQuoted, PolicyBound, PolicyEndorsed, PolicyCancelled]
# --- Event Store ---
class PolicyEventStore:
"""Append-only store per eventi di polizza."""
def __init__(self, db_pool):
self.db = db_pool
async def append(self, policy_id: UUID, event: PolicyEvent) -> int:
"""Appende un evento e restituisce il nuovo sequence number."""
async with self.db.acquire() as conn:
row = await conn.fetchrow(
"""
INSERT INTO policy_events
(policy_id, event_type, event_data, occurred_at)
VALUES ($1, $2, $3, $4)
RETURNING sequence_number
""",
str(policy_id),
event.event_type,
event.__dict__,
event.occurred_at or datetime.utcnow()
)
return row["sequence_number"]
async def get_history(self, policy_id: UUID) -> list[dict]:
"""Recupera tutti gli eventi di una polizza in ordine cronologico."""
async with self.db.acquire() as conn:
rows = await conn.fetch(
"""
SELECT event_type, event_data, occurred_at, sequence_number
FROM policy_events
WHERE policy_id = $1
ORDER BY sequence_number ASC
""",
str(policy_id)
)
return [dict(r) for r in rows]
async def rebuild_state(self, policy_id: UUID) -> dict:
"""Ricostruisce lo stato corrente della polizza dagli eventi."""
events = await self.get_history(policy_id)
state = {}
for evt in events:
state = self._apply_event(state, evt)
return state
def _apply_event(self, state: dict, event: dict) -> dict:
event_type = event["event_type"]
data = event["event_data"]
if event_type == "PolicyQuoted":
return {
**state,
"status": "QUOTED",
"policy_id": data["policy_id"],
"product_code": data["product_code"],
"annual_premium": data["annual_premium"]
}
elif event_type == "PolicyBound":
return {
**state,
"status": "IN_FORCE",
"policy_number": data["policy_number"],
"effective_date": data["effective_date"],
"expiry_date": data["expiry_date"],
"channel": data["channel"]
}
elif event_type == "PolicyEndorsed":
# Aggiorna il premio
current_premium = state.get("annual_premium", {"amount": "0"})
adjustment = data.get("premium_adjustment", {"amount": "0"})
return {
**state,
"annual_premium": {
"amount": str(
float(current_premium["amount"])
+ float(adjustment["amount"])
),
"currency": current_premium.get("currency", "EUR")
}
}
elif event_type == "PolicyCancelled":
return {
**state,
"status": "CANCELLED",
"cancellation_reason": data["cancellation_reason"],
"cancellation_date": data["cancellation_date"]
}
return state
5. Endorsement Management: Modifiche Mid-Term
Gli endorsement (modifiche mid-term) sono operazioni frequenti e delicate: l'aggiunta di un conducente, la variazione del veicolo, il cambio di indirizzo. Ogni endorsement può avere impatti sul premio (pro-rata) e deve generare documentazione aggiornata.
from decimal import Decimal
from datetime import date
class EndorsementCalculator:
"""Calcola l'aggiustamento di premio per un endorsement mid-term."""
def calculate_prorata_adjustment(
self,
current_annual_premium: Decimal,
new_annual_premium: Decimal,
endorsement_date: date,
policy_expiry: date
) -> Decimal:
"""
Calcola l'aggiustamento pro-rata del premio.
Restituisce importo positivo (addebitare) o negativo (rimborsare).
"""
remaining_days = (policy_expiry - endorsement_date).days
total_days = 365 # Semplificazione; usare calendario reale per polizze annuali
premium_difference = new_annual_premium - current_annual_premium
prorata_factor = Decimal(remaining_days) / Decimal(total_days)
return premium_difference * prorata_factor
class EndorsementService:
def __init__(self, repo, event_store, calculator, doc_service):
self.repo = repo
self.event_store = event_store
self.calculator = calculator
self.doc_service = doc_service
async def add_driver(
self,
policy_id: str,
driver_data: dict,
effective_date: date
) -> dict:
"""Aggiunge un conducente aggiuntivo alla polizza auto."""
# 1. Recupera polizza corrente
policy = await self.repo.get_policy(policy_id)
if not policy.is_active():
raise ValueError("Cannot endorse inactive policy")
# 2. Calcola nuovo premio con driver aggiuntivo
new_premium = await self._reprice_with_driver(policy, driver_data)
# 3. Calcola aggiustamento pro-rata
adjustment = self.calculator.calculate_prorata_adjustment(
current_annual_premium=policy.annual_premium.amount,
new_annual_premium=new_premium,
endorsement_date=effective_date,
policy_expiry=policy.expiry_date
)
# 4. Persisti endorsement
endorsement_id = await self.repo.create_endorsement(
policy_id=policy_id,
type="ADD_DRIVER",
effective_date=effective_date,
driver_data=driver_data,
premium_adjustment=adjustment
)
# 5. Pubblica evento
await self.event_store.append(policy_id, PolicyEndorsed(
policy_id=policy_id,
endorsement_id=endorsement_id,
endorsement_type="ADD_DRIVER",
premium_adjustment={"amount": str(adjustment), "currency": "EUR"}
))
# 6. Genera documento endorsement (async)
await self.doc_service.generate_endorsement_certificate(
policy_id, endorsement_id
)
return {
"endorsement_id": str(endorsement_id),
"premium_adjustment": float(adjustment),
"currency": "EUR",
"effective_date": effective_date.isoformat()
}
async def _reprice_with_driver(self, policy, driver_data: dict) -> Decimal:
"""Riprice la polizza includendo il nuovo conducente."""
# Logic depends on product rating algorithm
base_premium = policy.annual_premium.amount
driver_age = driver_data.get("age", 30)
# Young driver surcharge (semplificato)
if driver_age < 25:
surcharge = base_premium * Decimal("0.25")
elif driver_age < 30:
surcharge = base_premium * Decimal("0.10")
else:
surcharge = Decimal("0")
return base_premium + surcharge
6. Architettura Microservizi: Decomposizione del Policy Domain
Un sistema di policy management enterprise si decompone tipicamente nei seguenti microservizi, ognuno con il proprio bounded context e responsabilità ben definite:
| Servizio | Responsabilità | Database | Comunicazione |
|---|---|---|---|
| quote-service | Preventivazione, rating | Redis (cache) + PostgreSQL | REST + Events |
| policy-service | Lifecycle polizza, endorsement | PostgreSQL (event store) | REST + Events |
| billing-service | Pagamenti, installments, refund | PostgreSQL | Events |
| document-service | Generazione PDF, archiviazione | S3 / Azure Blob | Events (async) |
| notification-service | Email, SMS, push | Redis (queue) | Events (async) |
| underwriting-service | Risk scoring, accept/decline | PostgreSQL + ML Store | REST (sync) |
7. Integrazione Broker Portal
I broker assicurativi accedono al sistema tramite un portale dedicato. L'integrazione API deve gestire autenticazione, accesso ai dati dei clienti del broker, commissioni e reporting aggregato. Di seguito un esempio di middleware OAuth2 per broker:
from fastapi import FastAPI, Depends, HTTPException, status
from fastapi.security import HTTPBearer, HTTPAuthorizationCredentials
from jose import jwt, JWTError
import httpx
BROKER_PORTAL_SCOPES = [
"policy:read",
"policy:quote",
"policy:bind",
"policy:endorse",
"commission:read"
]
class BrokerAuth:
"""Middleware per autenticazione e autorizzazione broker."""
def __init__(self, jwks_url: str, audience: str):
self.jwks_url = jwks_url
self.audience = audience
self._jwks_cache = None
async def get_jwks(self) -> dict:
if not self._jwks_cache:
async with httpx.AsyncClient() as client:
resp = await client.get(self.jwks_url)
self._jwks_cache = resp.json()
return self._jwks_cache
async def verify_broker_token(
self,
credentials: HTTPAuthorizationCredentials = Depends(HTTPBearer())
) -> dict:
"""Verifica JWT token del broker e restituisce claims."""
try:
jwks = await self.get_jwks()
payload = jwt.decode(
credentials.credentials,
jwks,
algorithms=["RS256"],
audience=self.audience
)
broker_code = payload.get("broker_code")
if not broker_code:
raise HTTPException(
status_code=status.HTTP_403_FORBIDDEN,
detail="Missing broker_code claim"
)
return payload
except JWTError as e:
raise HTTPException(
status_code=status.HTTP_401_UNAUTHORIZED,
detail=f"Invalid token: {str(e)}"
)
# Dependency injection
broker_auth = BrokerAuth(
jwks_url="https://auth.insurer.com/.well-known/jwks.json",
audience="broker-portal-api"
)
@app.get("/v1/broker/{broker_code}/portfolio")
async def get_broker_portfolio(
broker_code: str,
broker_claims: dict = Depends(broker_auth.verify_broker_token),
policy_service: PolicyService = Depends(get_policy_service)
):
"""Restituisce il portfolio polizze di un broker."""
# Verifica che il broker acceda solo ai propri dati
if broker_claims["broker_code"] != broker_code:
raise HTTPException(
status_code=status.HTTP_403_FORBIDDEN,
detail="Access denied: broker_code mismatch"
)
policies = await policy_service.get_policies_by_broker(broker_code)
return {
"broker_code": broker_code,
"total_policies": len(policies),
"in_force_count": sum(1 for p in policies if p["status"] == "IN_FORCE"),
"total_gwp": sum(p["annual_premium"] for p in policies),
"policies": policies[:50] # Paginare in produzione
}
8. Rinnovi Automatici: Batch Processing e Outreach
I rinnovi sono operazioni critiche: la perdita di un cliente al rinnovo e costosa (costo acquisizione cliente 5-7x rispetto al mantenimento). Un sistema moderno automatizza il processo di rinnovo con outreach personalizzato e pricing dinamico.
import asyncio
from datetime import date, timedelta
from dataclasses import dataclass
@dataclass
class RenewalCandidate:
policy_id: str
holder_email: str
expiry_date: date
current_premium: float
renewal_premium: float
days_to_expiry: int
class RenewalOrchestrator:
"""Gestisce il processo automatico di rinnovo polizze."""
RENEWAL_WINDOWS = [60, 45, 30, 15, 7] # Giorni prima della scadenza
def __init__(self, policy_repo, pricer, notification_svc, event_bus):
self.repo = policy_repo
self.pricer = pricer
self.notification = notification_svc
self.event_bus = event_bus
async def run_daily_renewal_batch(self) -> dict:
"""Job giornaliero: identifica polizze da rinnovare e avvia outreach."""
today = date.today()
stats = {"processed": 0, "quoted": 0, "errors": 0}
for days_ahead in self.RENEWAL_WINDOWS:
target_date = today + timedelta(days=days_ahead)
candidates = await self.repo.get_expiring_policies(target_date)
tasks = [
self._process_renewal_candidate(c, days_ahead)
for c in candidates
]
results = await asyncio.gather(*tasks, return_exceptions=True)
for result in results:
stats["processed"] += 1
if isinstance(result, Exception):
stats["errors"] += 1
else:
stats["quoted"] += 1
return stats
async def _process_renewal_candidate(
self,
policy_id: str,
days_to_expiry: int
) -> dict:
policy = await self.repo.get_policy(policy_id)
# Calcola nuovo premio di rinnovo
renewal_premium = await self.pricer.calculate_renewal(policy)
premium_change_pct = (
(renewal_premium - float(policy["annual_premium"])) /
float(policy["annual_premium"]) * 100
)
# Salva preventivo rinnovo
renewal_quote = await self.repo.save_renewal_quote(
policy_id=policy_id,
renewal_premium=renewal_premium,
valid_days=days_to_expiry + 30
)
# Scegli template notifica in base ai giorni rimanenti
if days_to_expiry == 60:
template = "renewal_early_notice"
elif days_to_expiry == 30:
template = "renewal_30_day"
elif days_to_expiry == 7:
template = "renewal_final_reminder"
else:
template = "renewal_standard"
# Invia notifica
await self.notification.send_renewal_outreach(
holder_email=policy["holder"]["email"],
template=template,
context={
"policy_number": policy["policy_number"],
"expiry_date": policy["expiry_date"],
"renewal_premium": renewal_premium,
"premium_change_pct": premium_change_pct,
"renewal_link": f"https://portal.insurer.com/renew/{renewal_quote['id']}"
}
)
# Pubblica evento
await self.event_bus.publish("policy.renewal_quoted", {
"policy_id": policy_id,
"renewal_quote_id": renewal_quote["id"],
"days_to_expiry": days_to_expiry
})
return renewal_quote
9. Testing: Approcci per Sistemi Assicurativi Complessi
I sistemi assicurativi hanno logica di business complessa e alta dipendenza da regole che cambiano nel tempo. Il testing deve coprire unit test per le regole di business, integration test per i flussi end-to-end, e contract test per le API esposte ai broker.
import pytest
from decimal import Decimal
from datetime import date, timedelta
from unittest.mock import AsyncMock, MagicMock
class TestEndorsementCalculator:
"""Unit test per il calcolo pro-rata degli endorsement."""
def setup_method(self):
self.calc = EndorsementCalculator()
def test_prorata_increase_with_full_year_remaining(self):
adjustment = self.calc.calculate_prorata_adjustment(
current_annual_premium=Decimal("600"),
new_annual_premium=Decimal("750"),
endorsement_date=date(2025, 1, 1),
policy_expiry=date(2026, 1, 1)
)
# 150 difference * (365/365) = 150
assert abs(adjustment - Decimal("150")) < Decimal("1")
def test_prorata_decrease_at_midterm(self):
adjustment = self.calc.calculate_prorata_adjustment(
current_annual_premium=Decimal("600"),
new_annual_premium=Decimal("500"),
endorsement_date=date(2025, 7, 1), # 6 mesi dopo inizio
policy_expiry=date(2026, 1, 1)
)
# Aggiustamento negativo (rimborso)
assert adjustment < Decimal("0")
def test_endorsement_on_last_day_is_zero(self):
today = date.today()
adjustment = self.calc.calculate_prorata_adjustment(
current_annual_premium=Decimal("600"),
new_annual_premium=Decimal("800"),
endorsement_date=today,
policy_expiry=today # Scadenza oggi
)
assert adjustment == Decimal("0")
@pytest.mark.asyncio
class TestPolicyService:
"""Integration test del service layer."""
async def test_create_quote_success(self):
# Arrange
mock_repo = AsyncMock()
mock_repo.get_product.return_value = MagicMock(terms_version="v2.1")
mock_pricer = AsyncMock()
mock_pricer.calculate.return_value = [
CoverageQuote(
coverage_type="LIABILITY",
limit=Decimal("1000000"),
deductible=Decimal("0"),
annual_premium=Decimal("400")
)
]
mock_underwriter = AsyncMock()
mock_underwriter.score.return_value = MagicMock(score=0.3)
mock_repo.save_quote.return_value = MagicMock(
id="q-123",
valid_until=date.today() + timedelta(days=72)
)
service = PolicyService(
repo=mock_repo,
pricer=mock_pricer,
underwriter=mock_underwriter,
event_bus=AsyncMock()
)
request = QuoteRequest(
product_code="AUTO_RC",
holder_fiscal_code="CLDFRC80A01H501U",
effective_date=date.today() + timedelta(days=1),
desired_coverages=["LIABILITY"]
)
# Act
result = await service.create_quote(request)
# Assert
assert result.total_annual_premium == Decimal("400")
assert result.terms_version == "v2.1"
mock_underwriter.score.assert_awaited_once()
10. Best Practices e Anti-Pattern
Anti-Pattern: God Object Policy
Non creare un'unica tabella "policies" con 200 colonne. Usa un domain model ricco con value objects (Money, Coverage, Address) e aggregate boundaries chiari. Una colonna "coverage_data JSONB" non e un domain model.
Anti-Pattern: Stato Mutabile Senza Audit Trail
Non fare UPDATE diretti su una polizza senza tracciare la storia. Il settore assicurativo richiede audit completi per IVASS. Usa event sourcing o almeno una tabella di history.
Best Practice: Idempotency per Operazioni Critiche
Le operazioni di bind e cancellazione devono essere idempotenti. Usa un
idempotency_key header nelle richieste critiche. Persisti il risultato
e restituiscilo se la stessa chiave viene inviata di nuovo.
Best Practice: Contract Testing con Pact
Per le integrazioni con broker e aggregatori, usa contract testing (Pact). Ogni consumer definisce il contratto che si aspetta; il provider verifica che lo rispetti. Questo previene breaking changes nelle API critiche.
Conclusioni
Un sistema di policy management cloud-native API-first richiede investimento nella modellazione del dominio prima ancora dell'infrastruttura. Il domain model ricco (aggregate, value objects, events), l'API design ACORD-compatible e l'event sourcing per l'audit trail sono i fondamentali su cui costruire.
Il 74% degli assicuratori sta modernizzando i core system: la competizione con gli InsurTech nativi digitali rende questa trasformazione non più opzionale. I pattern descritti in questo articolo - event sourcing, microservizi, API-first, endorsement management - sono la base tecnica per costruire piattaforme assicurative scalabili e manutenibili.
Prossimi Articoli della Serie InsurTech
- Pipeline Telematica: Processing Dati UBI su Scala
- AI Underwriting: Feature Engineering e Risk Scoring
- Automazione Sinistri: Computer Vision e NLP
- Fraud Detection: Graph Analytics e Behavioral Signal

Commenti
Caricamento commenti...
Accedi per commentare