In-house Financial Services global Company newsroom

Allianz

Customer Service Automation · Risk Management

Allianz wanted to reduce customer effort and cycle time in claims handling, improve risk assessment and pricing, and move from reactive claims payment toward more predictive and preventive support for policyholders.

The entire process is completed in a few minutes.
We’re currently investigating around 60 use cases globally for Generative AI.

Reported impact

Business outcome

Allianz says these AI tools shorten claims handling to minutes, improve customer satisfaction, support more accurate underwriting and claims routing, help customers avoid weather-related damage, and reduce claims expenses while increasing efficiency and productivity.

  • Cost Reduction
  • Customer Experience
  • Productivity Improvement
  • Risk Reduction

Solution

Allianz describes an in-production AI claims and risk-management setup embedded across its insurance operations rather than a single standalone platform. In customer interaction, the company uses intelligent chatbots to answer queries, while underwriting uses AI tools to assess and price risks more accurately. The most concrete named implementation is the CE application, developed by Allianz-owned Control Expert, where customers submit photos of damaged cars or parts and an AI solution evaluates the images to produce a loss amount, confirm coverage, and trigger a direct payment offer within minutes. Allianz also uses AI in claims operations to route cases directly to partner repair shops. A second named tool, the Severe Weather SMS tool, combines available customer data with tracked weather patterns to identify at-risk customers and send preventive storm warnings by text message. The source does not name storage platforms or external model providers, but it clearly shows AI ingesting customer images and customer/weather data, processing them for decisioning, and serving outputs through app-based settlement, repair routing, and SMS notifications.

Data flow

Customers submit vehicle-damage photos through the CE application, where AI analyzes the images and returns a loss amount, coverage confirmation, and direct-payment offer; related claims can then be routed to partner repair shops. Separately, Allianz combines available customer data with tracked weather patterns to identify exposed customers and send storm-warning SMS messages before losses occur.

Solution architecture

2 components · 1 layer
  1. Serving
    • CE application Lets customers submit vehicle-damage photos and uses AI to generate a loss amount, confirm coverage, and offer direct payment.
    • Severe Weather SMS tool Uses customer and weather data to identify risk exposure and send preventive storm warnings by text message.

Architecture clues

  • Allianz says AI is used across the full insurance value chain.
  • Claims workflows can route customers directly to partner repair shops.
  • The CE application was developed by Allianz-owned company Control Expert.
  • The severe-weather use case relies on available customer data in accordance with data privacy regulations plus tracked weather patterns.

Evidence from the source

"All they need to do is take a picture of the damage or damaged parts and through an AI solution, they’re automatically presented with a loss amount, receive coverage confirmation, and are offered a direct payment."
"By leveraging available data from customers (in accordance with data privacy regulations) and tracking weather patterns, the tool sends a storm warning via text message."
"Developed by the Allianz-owned company Control Expert, the app allows customers to take pictures of their damaged car and get a settlement offer immediately."
"The entire process is completed in a few minutes and leads to immediate results for the customer."
"This helps customers avoid damage and brings us corresponding savings in claims expenses."
"We use intelligent chatbots in our client interaction, e.g., to answer customer queries, and embed AI tools in the underwriting process to assess and price risks more accurately."
Transparency Evidence & methodology 75/100 reference value · 92% confidence · 1 source

Review how this reference was scored and trace each normalized claim back to its documented source.

01

Scoring methodology

How scores are calculated

Customer Reference Value measures usefulness as a customer reference. Evidence Confidence measures the quality and traceability of available evidence, not independent verification.

Customer reference value75/100
  • Problem clarity20/20
    Measures whether the customer's operational problem is specific enough to compare.
  • Implementation depth25/25
    Rewards named components, data flow, integrations, and architecture detail.
  • Outcome specificity20/20
    Measures whether the reported benefit is concrete rather than a generic claim.
  • Quantified impact0/25
    0 metrics describe measurable impact.
  • Deployment scale10/10
    Rewards evidence of a live or scaled deployment and meaningful integration scope.
Evidence confidence92%
  • Source authority25/25
    The deployment is described by the adopting organization or a government source.
  • Claim traceability21/25
    10 of 12 key fields link to a named source.
  • Direct evidence20/20
    6 direct source quotes retained.
  • Date provenance10/10
    The publication date comes from the source page or publisher.
  • Source transparency8/10
    1 source reference document publisher, URL, authority, retrieval, and supported fields.
  • Implementation specificity8/10
    Rewards source-backed components, data flow, quantified impact, and a specific outcome.
02

Traceability

Sources & provenance

Field coverage shows which facts each source supports. Dates are shown only when documented by the source.

  1. Allianz

    Allianz customer story

    First-party
    https://www.allianz.com/en/mediacenter/news/business/it/230822_Allianz-Are-we-still-talking-about-AI-as-a-tool-of-the-future.html
    Source type
    Customer-published story
    Published
    Aug 22, 2023
    Supports
    • Customer
    • Business problem
    • Solution
    • Products
    • Solution components
    • Data flow
    • Integrations
    • technical area
    • use case category
    • Business outcome
    • outcome category
    • Metrics
    • Architecture
    • evidence quotes
    • Publication date

Date evidence

  • Published on source page Aug 22, 2023 · Allianz · First-party
    Open date source
Not separately sourced Industry, Region, Company size. Treat these normalized attributes as lower-confidence until a dedicated source is added.