OpenAI Financial Services Global

Klarna

Customer Service Automation · Marketing Personalization

Klarna needed to improve online shopping discovery, automate high-volume customer service, and increase employee productivity while preserving quality across global fintech operations.

$40 million USD estimated profit improvement in 2024
2.3 million conversations in the first month
25% drop in repeat inquiries
90% of Klarna employees use OpenAI-powered generative AI tools daily

Reported impact

Business outcome

Klarna reduced customer-service handling time, cut repeat inquiries, improved profit potential, and extended AI usage from shopping and service into broad enterprise productivity across the organization.

  • Customer Experience
  • Productivity Improvement
  • Revenue Growth

Solution

Klarna uses OpenAI across both customer-facing experiences and internal work. On the shopping side, the company launched an early ChatGPT plugin so users can describe what they want conversationally and receive recommendations linked into Klarna’s search-and-compare experience. For service operations, Klarna deployed an AI assistant powered by OpenAI to handle multilingual support, refunds, returns, and personal-finance guidance across its global customer base. The assistant now resolves a large share of customer-service interactions with human-level satisfaction and much faster handling times. Klarna also rolled out ChatGPT Enterprise to employees worldwide so teams in communications, marketing, legal, software, and customer service can work with protected company data inside a familiar interface. This combination lets Klarna use AI for discovery, support, and internal execution while continuously encouraging experimentation from leadership down.

Data flow

Shopper prompts flow from ChatGPT into Klarna’s product-discovery and price-comparison surfaces, while service requests are handled by the AI assistant across multilingual customer-support channels. Internally, employee tasks and sensitive company work are routed through ChatGPT Enterprise with protected data handling.

Solution architecture

3 components · 1 layer
  1. Serving
    • ChatGPT plugin Lets shoppers describe desired products conversationally and receive recommendations connected to Klarna’s comparison tools.
    • AI assistant Automates multilingual support, refunds, returns, and related shopping or payment service tasks.
    • ChatGPT Enterprise Provides protected AI access for Klarna employees across business functions worldwide.

Architecture clues

  • AI assistant is available in 23 markets, 24/7, and communicates in more than 35 languages
  • ChatGPT Enterprise is deployed globally with protected company data
  • Klarna was the first European company and first fintech to launch a ChatGPT plugin
  • Leadership explicitly pushes employees to test and explore AI use cases

Evidence from the source

"90% of Klarna’s employees are using generative AI tools powered by OpenAI daily"
"Customers now resolve their errands in less than 2 mins compared to 11 mins previously"
"It is doing the equivalent work of 700 full-time agents"
"The AI assistant has had 2.3 million conversations, two-thirds of Klarna’s customer service chats"
Transparency Evidence & methodology 100/100 reference value · 89% 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 value100/100
  • 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 impact25/25
    4 metrics describe measurable impact.
  • Deployment scale10/10
    Rewards evidence of a live or scaled deployment and meaningful integration scope.
Evidence confidence89%
  • 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
    4 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 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. OpenAI

    Klarna customer story

    First-party
    https://openai.com/index/klarna/
    Source type
    Vendor-published customer story
    Published
    Mar 28, 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

  • Published on source page Mar 28, 2024 · OpenAI · 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.