Top 10 Mobile Finance Apps for the US Market
Artezio Analytical Department has conducted a comprehensive research on mobile apps for personal finance tracking.
Personal Capital® heads the Top 10 finance apps that fully meet the requirements of US users. According to the research, the most popular features of Personal Capital® include easy budgeting, expense tracking, joint budget management, and credit resources monitoring.
Dollarbird ranks second in the rating. This app can be easily linked to separate accounts, and it allows users to enter payment data manually as well as get detailed bills.
Ranked third is Mint, the only app that is available on all platforms, including Amazon Kindle.
The Top 10 list includes:
8. Cost Track
In analyzing these user requirements, Artezio’s Analytical Department considered how convenient each app was for the users. Eugene Rozin, Lead Business Analyst at Artezio, believes data collection is still a problem that developers need to solve: “Despite serious competition from developers in this segment, users still don’t have a convenient tool that would allow them to automatically track their income and expenses without having to assiduously enter required data.”
All of the personal finance trackers in the study were evaluated against 11 criteria, including mobile platforms supported, cost, additional expenses (in-app purchases), budgeting, ability to link several accounts and monitor credit ratings, suspicious transaction reporting, and an expense calendar. Among the most popular functions were automatic monitoring of credit payments, centralized data collection of transaction history, and simplified data entry.
Artezio Analytical Department is in charge of the research and analysis of the existing program platforms and the latest technology trends in the US and European markets. We evaluate technical and functional aspects of apps and solutions against various criteria, including most popular functions, user experience and usability, security and scalability. Artezio, LLC specializes in projects on IoT, machine learning, Big Data, and Uber solutions.