Acordo Certo's Transformation with Google Cloud: A Case Study on Data Intelligence and Machine Learning
Technology Category
- Analytics & Modeling - Machine Learning
- Infrastructure as a Service (IaaS) - Cloud Computing
Applicable Industries
- Equipment & Machinery
- Telecommunications
Applicable Functions
- Procurement
Use Cases
- Leasing Finance Automation
- Smart Contracts
Services
- Cloud Planning, Design & Implementation Services
- Training
About The Customer
Acordo Certo is a financial services company based in Brazil. The company's mission is to deliver financial wellbeing for defaulting consumers by simplifying debt tracking, negotiation, payment, and notification processes. The company provides a digital, comfortable, end-to-end experience for its customers. Acordo Certo has over 40 partners and nearly one million new subscriptions per month on its platform, generating dozens of billions of registrations. The company uses data intelligence and machine learning to learn about consumer profiles and maintain customized, assertive communications with each of them.
The Challenge
Acordo Certo, a Brazilian financial services company, was facing significant challenges with its existing cloud services provider. The company's mission is to simplify debt tracking, negotiation, payment, and notification processes for defaulting consumers. However, the company's platform was experiencing performance issues, particularly with large-sized queries. The existing solution was costly, inefficient, and unable to deliver the desired results. The company needed a robust solution that could handle the vast amount of data generated by its nearly one million new subscriptions per month and dozens of billions of registrations. The company also needed to process this data to learn about consumer profiles and maintain customized, assertive communications with each of them.
The Solution
Acordo Certo migrated to Google Cloud's BigQuery, which provided easy, managed processing at scale. BigQuery became the company's data warehouse, consolidating data generated or imported by its internal systems. The company also adopted Google Kubernetes Engine (GKE) for running the web app, which reduced the go-live time of new features to under five minutes. The company used preemptible virtual machines to handle unpredictable peaks in request volumes, resulting in a cost reduction of 80% compared with previous VMs. Acordo Certo also used Cloud Composer to organize and orchestrate over 200 jobs every day to update the database using partner files. This data was processed and transformed using BigQuery together with Dataflow, which responded to complex queries in under 10 seconds and provided validations on tables with billion-scale volumes. AutoML’s tools enabled training and scoring machine-learning models in about 30 minutes.
Operational Impact
Quantitative Benefit
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