Oportun, is a mission-driven fintech that puts its 2 million members’ financial goals within reach, needed a better way to quickly identify and remediate potential security risks to its members’ personally identifiable information (PII). In this architecture, Carlos from Oportun discusses their primary goal was to reduce risk as much as possible so that member PII is safer in the event of inadvertent access. Oportun makes heavy use of Amazon Macie–automated data discovery to identify Amazon S3 buckets with potential PII in a cost-effective and scalable way. With automated data discovery, Oportun doesn’t have to scan every single Amazon S3 bucket completely. Instead, it can identify and prioritize which Amazon S3 buckets must be remediated to accelerate risk reduction. They were able to achieve 95 percent data discovery accuracy using Amazon Macie.
To dive deeper into discovering sensitive data with Amazon Macie check out:
Discovering sensitive data with Amazon Macie – https://docs.aws.amazon.com/macie/latest/user/data-classification.html
and here is the full Oportun case study:
Oportun Increases the Accuracy of Sensitive-Data Discovery by 95% Using Amazon Macie – https://aws.amazon.com/solutions/case-studies/oportun-case-study/
For more information about Oportun, please visit www.oportun.com
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