Fraud protection at scale

Dan Petty & Ron Liu

At Credit Karma, we want our members to make financial progress — and we believe that the security of our members’ personal, financial and tax information is the cornerstone of that mission. This is why we invest heavily in security measures to help protect our members from fraud, abuse and cyber crime.     The systems […]

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Microservices: From REST to Thrift and GraphQL

Volodymyr Ladnik

Microservices architecture is very popular these days, and is coming into increasing use at Credit Karma. While there are many reasons to develop microservices, their use comes with a number of potential pitfalls. This article describes a couple of those drawbacks and what we’re doing about them. Our first microservices presented REST APIs. REST provides […]

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Value-Driven Software Documentation

Jim Haungs

Documentation is a tough sell to software engineers. We want to invent amazing features and write code, and when we finish doing that, we want to do it some more. We don’t want to take the time to sit down and actually describe what we’ve done. But if we don’t, how is anyone else — […]

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Empathic Collaboration

Vertika Srivastava

My product-focused engineering team at Credit Karma works on a wide variety of projects: designing product experiences, building front-end features, spinning up back-end services and  analyzing data. We interact with a diverse set of people to get these things done. At one point, we might be asking for help from a platform engineer, and at […]

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Frequentist Stopping Rules

Robert Neal

Stopping rules are what make most frequentist (a.k.a. classical) statistical tests valid. Unsurprisingly, they tell you when to stop an experiment, and equally unsurprising, they are rules that must be followed in order to get statistically valid experiments from statistical tests that depend on them. However, despite stopping rules being critical to the interpretation of […]

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JSON and the Confusion of Formats in Big Data

Yongjia Wang

In the era of big data, the choices of data formats are dazzling, and the concept of data format itself can be confusing. Our data platform team found it helpful to breakdown this topic based on the three major stages in the life cycle of data: in-memory representation (logical format), on-the-wire serialization (exchange format), and […]

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