Now acquired by

Effectiv is a no-code fraud detection platform designed for large financial institutions to combat fraud across various use cases, including onboarding verification, account takeovers, and anti-money laundering (AML) detection. By providing customizable risk workflows and real-time decisioning, Effectiv empowers businesses to identify and mitigate fraud efficiently.

As a Product Designer on Effectiv, I played a key role in shaping feature implementations and conceptualizing a 2.0 uplift to enhance usability and workflow scalability. I conducted extensive user research to uncover pain points, redesigned navigation and workflows to minimize user confusion, and created onboarding enhancements to help new users integrate seamlessly. Additionally, I developed interactive workflow-building tools to make strategy implementation intuitive. While the 2.0 uplift didn’t move into development, the insights and solutions addressed major usability gaps, ensuring a more efficient and user-friendly fraud prevention experience.

B2B

AI

Fraud Detection

Risk Prevention

My Role

Product Designer — Design, Interaction Design, Visual Design, User Flows, Rapid Prototyping

Year

Apr 2023 - Feb 2025

Scope of Work

Product Design

Tools used

Figma

UX for a frictionless fraud detection

Designed intuitive, no-code workflows for fraud detection, allowing financial institutions to adapt risk strategies effortlessly. Implemented a JSON panel integration, enabling users to view and modify raw case data for increased transparency and flexibility in decision-making.

Elevating case interactions

Redesigned case workflows to enhance visibility and navigation, ensuring fraud analysts could review, update, and resolve cases quickly. Introduced structured case histories and improved UI clarity, making it easier to track actions and collaborate across teams.

Scaling with thoughtful design

Conceptualized the Effectiv 2.0 uplift, focusing on workflow improvements, UI enhancements, and better automation. Although it wasn’t developed, the research and solutions addressed key usability gaps, laying the foundation for a more scalable and user-friendly fraud detection platform.

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