{"slug":"lloyds-banking-group-cuts-mortgage-income-verification-from-days-to-seconds-with-ml","url":"https://findausecase.com/use-cases/lloyds-banking-group-cuts-mortgage-income-verification-from-days-to-seconds-with-ml","title":"Lloyds Banking Group cuts mortgage income verification from days to seconds with ML","description":"Lloyds Banking Group, the UK's largest digital bank, migrated 15 modelling systems from on-premise infrastructure to Google Cloud's Vertex AI (now Agent Platform), giving over 300 data scientists and AI developers scalable machine learning capabilities. In six months the bank ran 80 new ML experiments and launched 18+ GenAI systems into production, including an algorithm that reduces the income verification step in mortgage applications from days to seconds. The migration also cut unplanned ML platform downtime to zero and saved 27 CO2 tonnes of operational emissions.","company":"Lloyds Banking Group","industry":"Financial Services","country":"United Kingdom","aiCapabilities":["Document Intelligence","Machine Learning"],"technology":["Google Cloud Vertex AI","Gemini Enterprise Agent Platform","BigQuery","Cloud Storage","Dataflow","Google Kubernetes Engine","Pub/Sub","Managed Service for Apache Airflow"],"deployment":"Public Cloud","problemStatement":"Lloyds Banking Group's previous ML platform did not allow data scientists to experiment at scale, and the bank needed a scalable, reliable cloud platform to meet customers' evolving expectations for financial partnership and data-driven insights.","solutionApproach":"Lloyds Banking Group migrated 15 modelling systems, comprising hundreds of individual models, from on-premise infrastructure to Google Cloud's Vertex AI (now Gemini Enterprise Agent Platform), giving over 300 data scientists and AI developers a shared platform with consistent guardrails and the flexibility to use third-party, open-source, and Google's Gemini models.","businessValue":"The migration cut unplanned ML platform downtime to zero, enabled 80 new ML experiments in six months, launched 18+ GenAI systems into production including an algorithm that reduces mortgage income verification from days to seconds, and saved 27 CO2 tonnes of operational emissions.","evidence":{"band":"high"},"sourceUrl":"https://cloud.google.com/customers/lloydsbankinggroup","dates":{"publishedAt":"2026-09-26T05:45:36.536Z","publishedAtSource":"pipeline","updatedAt":"2026-09-26T05:45:36.536Z"},"license":"Open for reading and citing with a link to https://findausecase.com/use-cases/lloyds-banking-group-cuts-mortgage-income-verification-from-days-to-seconds-with-ml. Bulk republication requires permission."}