Friend Suggestions At Cash App

Angelo Monteux
Friend Suggestions At Cash App

At Cash App, customers can invite their friends to join the platform and be rewarded for doing so. We built a ML model to populate a “Suggested Friends” section in the Invite Friends screen to help customers quickly find friends to invite without having to scroll through their whole contact book. In this post, we describe how we built it,...

Barbie beats Oppenheimer at the box office - and on Cash App too

Hamdan Azhar
Barbie beats Oppenheimer at the box office - and on Cash App too

Cash App is a vital part of the US economy, providing a crucial tool for people to send and receive Peer to Peer (P2P) payments, obtain a free debit card, and even buy and sell bitcoin and stocks. As data scientists, we’re especially psyched about our robust dataset which gives us an exciting glimpse into how people use Cash App...

Blizzard: A Lightweight, Yet Powerful ML Feature System for Prototyping and v1 Use Cases

Christopher Skeels
Blizzard: A Lightweight, Yet Powerful ML Feature System for Prototyping and v1 Use Cases

Introduction This post is about Blizzard, a machine learning feature system we’ve built at Block’s Cash App for prototyping and early v1 production ML use cases. Blizzard demonstrates how a tremendous amount of value can be obtained by pairing a Python library with a data warehouse. While we already have a robust production-oriented feature system at Cash, that system has...

Improving customer support intent classification with additional language model pretraining

Victor Li and Dean Wyatte
Improving customer support intent classification with additional language model pretraining

Abstract: Labeled data are a crucial component for many NLP tasks, but are typically time consuming or otherwise costly to collect. Here, we describe how we improved sample efficiency of labeled data for a customer support intent classification task with additional language model pretraining on Cash App support cases.

Cash App goes to Washington

Isaac Tamblyn

Cash App will be in Washington, D.C. this week, attending the 37th AAAI Conference on Artificial Intelligence. We will be presenting our results on fintech-kMC, a simulation tool we recently built to test and verify machine learning models and workflows using synthetic data. The work will appear as part of the AAAI-23 Bridge Program - AI for Financial Services. We...

Risk at Cash

Isaac Tamblyn

In the few years since we started, Cash has developed a robust and effective approach to managing customer-facing financial risk. Our approach lets us operate in local markets which have often been ignored by traditional banks, offer products which previously seemed infeasible, and respond to changes rapidly. Fraud is a high-stakes game that takes constant work to stay ahead of...

Model Review

Jes Ford
Model Review

Code Review is an integral part of software development, but many teams across industry don’t have similar processes in place for the development and deployment of Machine Learning (ML) models.