MicrosoftLive source

Unit8 empowers Swiss banks to optimize credit risk with Azure AI

Use case typeFraud detectionUpdated Jun 13, 2026

Unit8, a Swiss data science consultancy, leverages Microsoft Azure AI and machine learning to drive credit risk management for banks. Their solutions include AI-based credit scoring, churn prevention, fraud detection, and automated onboarding for financial institutions. By building centralized data platforms and enabling smarter customer interactions with chatbots and recommendation engines, Unit8 empowers banks to unify risk visibility, increase client retention, and ensure compliance, improving decision making and streamlining banking operations.

Organization
Swiss banks
Industry
Finance
Location
Switzerland
Published
January 2024

Reported outcomes

Strategic outcomes

Risk & complianceReduced fraud and risk lossesSpeed & agilityFaster credit decisioning and onboardingCustomer experience & trustIncreased customer retentionBetter decisions & insightUnified risk visibility and smarter decisions

Primary read

Use case focus

Showing 3 of 3

  • 1credit risk management
  • 2fraud detection
  • 3customer churn prediction
  • Banks face increasing fraud losses yearly (up to 5% of revenue)
  • Difficulty in gaining unified view of client risk and exposures
  • Manual onboarding and compliance create friction
  • Customer churn impacts long-term profitability
  • Implemented Azure AI/ML for credit scoring and fraud detection
  • Centralized data platforms provide single client view
  • Chatbots and voice bots automate customer support and reduce costs
  • Built compliance-ready analytics for onboarding and KYC
Technologies
  • Reduced fraud and risk losses via advanced analytics
  • Faster credit decisioning and onboarding for clients
  • Increased customer retention with early churn detection
  • Improved operational efficiency and compliance
Architecture

Data from multiple banking systems are consolidated into centralized data lakes and analyzed by Azure AI and ML models for scoring, fraud detection, and churn prediction. Results feed into customer-facing bots and internal analytics dashboards for unified operations.

Implementation partners1
Sources & evidence1
Live sourceStill referenced

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  • Cited source last checked Jun 12, 2026 — ok (0/1 broken).

Measures whether this deployment's public evidence persists — not whether the system is still in production.

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