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AWS Financial Services Canada

Intact Financial Corporation

Document Processing · Risk Management

It could significantly improve agent efficiency by off-loading repetitive issues to a chatbot and automatically notifying a supervisor when a challenging interaction required assistance. The company sought to build a system that would automatically unlock insights from calls at scale to improve customer service and uncover business opportunities.

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10% calls automatically transcribed within 4–6 hours
15x
Quality auditors are now 65% more efficient, and the agent coaching insights garnered from the calls have reduced agents’ call handling time by 10%.
Up to 20,000

Reported impact

Business outcome

Intact continues to deploy the CQ suite across an increasing number of business units and use cases. “With Amazon Transcribe, we are able to use the same infrastructure, the same solution, and the same functions to deploy the product in different contexts with different AI models based on the same call transcript foundation,” says Brouillard. Key reported metrics include faster call audits 15x; 15x; reduction in average handling time 10%.

  • Customer Experience
  • Productivity Improvement
  • Scalability

Solution

Learn how Intact Financial Corporation enhanced customer service with data-driven insights from Amazon Transcribe. Intact Financial Corporation (Intact) is the largest provider of property and casualty insurance in Canada, a leading provider of global specialty insurance, and a leader in commercial lines in the UK and Ireland. The company has a global network of customer service centers that handle as many as 20,000 calls per day. Regular audits of these calls are a crucial mechanism for understanding and delivering delightful customer experiences. Call auditing is traditionally a manually intensive, time consuming, and expensive process. Call quality management analysts listen and rate calls one at a time. As a result, analysts review less than 2% of the overall call volume. Source data is ingested through Amazon Transcribe.

Data flow

Source data is ingested through Amazon Transcribe.

Solution architecture

1 components · 1 layer
  1. Ingest
    • Amazon Transcribe Transcribes call audio or speech into text for downstream analysis.

Architecture clues

  • Intact can now boost transcription accuracy with Amazon Transcribe’s automated language identification and multilingual transcription features which accurately transcribe the text in the language used even as the speaker
  • The company has a global network of customer service centers that handle as many as 20,000 calls per day.
  • Working alongside an AWS solutions architect, Data Lab built a secure, serverless architecture for CQ.

Evidence from the source

10% calls automatically transcribed within 4–6 hours
15x
It could significantly improve agent efficiency by off-loading repetitive issues to a chatbot and automatically notifying a supervisor when a challenging interaction required assistance. The company sought to build a system that would autom
Quality auditors are now 65% more efficient, and the agent coaching insights garnered from the calls have reduced agents’ call handling time by 10%.
The Intact Lab sought to build the foundation of CQ around a speech recognition service that would automatically convert all the customer calls into text for further analysis.
Up to 20,000
Transparency Evidence & methodology 90/100 reference value · 87% 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 value90/100
  • Problem clarity20/20
    Measures whether the customer's operational problem is specific enough to compare.
  • Implementation depth20/25
    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 impact25/25
    7 metrics describe measurable impact.
  • Deployment scale5/10
    Rewards evidence of a live or scaled deployment and meaningful integration scope.
Evidence confidence87%
  • Source authority20/25
    The main evidence is an official vendor-published customer story.
  • Claim traceability21/25
    10 of 12 key fields link to a named source.
  • Direct evidence20/20
    6 direct source quotes retained.
  • Date provenance8/10
    The publication date comes from publisher-controlled metadata.
  • Source transparency8/10
    1 source reference document publisher, URL, authority, retrieval, and supported fields.
  • Implementation specificity10/10
    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. AWS

    Intact Financial Corporation customer story

    First-party
    https://aws.amazon.com/solutions/case-studies/case-study-intact-financial/
    Source type
    Vendor-published customer story
    Published
    Oct 1, 2024
    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

Not separately sourced Industry, Region, Company size. Treat these normalized attributes as lower-confidence until a dedicated source is added.

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