{"id":10481,"date":"2026-07-07T10:53:49","date_gmt":"2026-07-07T10:53:49","guid":{"rendered":"https:\/\/www.version1.com\/en-us\/?p=10481"},"modified":"2026-07-07T10:53:49","modified_gmt":"2026-07-07T10:53:49","slug":"cutting-costs-by-45-and-achieving-99-99-uptime-for-a-major-us-mortgage-servicer-with-aws","status":"publish","type":"page","link":"https:\/\/www.version1.com\/en-us\/cutting-costs-by-45-and-achieving-99-99-uptime-for-a-major-us-mortgage-servicer-with-aws\/","title":{"rendered":"Cutting costs by 45% and achieving 99.99% uptime for a major US mortgage servicer with AWS"},"content":{"rendered":"\n
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Client Profile<\/h3>\n

Technology Partners:\u00a0<\/strong>AWS<\/p>\n

Customer Since: <\/strong>2025<\/p>\n

Employees: <\/strong>Approximately 1,000<\/p>\n

Sector: <\/strong>Financial Services<\/p>\n

 <\/p>\n

Overview<\/h3>\n
\n

A large US mortgage servicer faced a set of familiar challenges: legacy infrastructure that constrained cost efficiency, scalability and speed. Cost \u2013 On\u2011premise infrastructure required year\u2011round payment for peak capacity, with hardware and administrative overheads pushing costs toward \u00a3500k. Scalability \u2013 Volume spikes caused batch jobs to overrun, slowed payment processing, and required slow hardware.<\/p>\n<\/div>\n

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A large US mortgage servicer faced a set of familiar challenges: legacy infrastructure that constrained cost efficiency, scalability and speed.<\/p>\n<\/div>\n

    \n
  • Cost<\/strong>\u00a0\u2013 On\u2011premise infrastructure required year\u2011round payment for peak capacity, with hardware and administrative overheads pushing costs toward \u00a3500k.<\/li>\n
  • Scalability<\/strong>\u00a0\u2013 Volume spikes caused batch jobs to overrun, slowed payment processing, and required slow hardware procurement cycles to scale.<\/li>\n
  • Speed<\/strong>\u00a0\u2013 Quarterly deployment windows meant product teams waited months to release updates while competitors delivered changes rapidly.<\/li>\n<\/ul>\n

    Version 1 was selected to modernise the platform, reducing cost while improving reliability.<\/p>\n

     <\/p>\n

    Implementing a cloud native managed service solution<\/strong><\/h4>\n

    We re\u2011architected the platform using a cloud\u2011native, managed service model \u2013 allowing teams to focus on customer\u2011facing enhancements instead of their infrastructure<\/p>\n

    We right\u2011sizing workloads across AWS services including\u00a0Lambda, Fargate, RDS, SQS<\/strong>, and\u00a0EventBridge<\/strong>, enabling the customer to gain better performance, control, and compliance.<\/p>\n

    <\/h2>\n

    Delivering measurable bottom line benefits for the customer<\/strong><\/h4>\n

    The solution turned the challenges of cost, scalability and speed into competitive advantages:<\/p>\n

      \n
    • Cost<\/strong>\u00a0\u2013 Infrastructure costs were reduced to \u00a3275k, a 45% reduction.<\/li>\n
    • Scalability<\/strong>\u00a0\u2013 Automated scaling removed capacity constraints and enabled the business to meet demand without disruption.<\/li>\n
    • Speed<\/strong>\u00a0\u2013 Moving to a fully automated deployment pipeline turned quarterly releases into small, frequent changes. Features are now launched when they\u2019re ready and not tied to long term release cycles.<\/li>\n<\/ul>\n

      The new solution has transformed availability from \u201cgood enough most of the time\u201d to 99.99% or under an hour of downtime a year and ensured that their infrastructure has changed from an inhibitor to a competitive advantage.<\/p>\n <\/div>\n \n <\/div>\n 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