Track your Income and Expenses with Ease
SpendTrack is a comprehensive mobile application that enables users to easily track their income and expenses. The solution uses AI/ML algorithms to read all bank SMS since inception and analyse and classify them based on transaction type, date, bank name, and merchant name for every user.
Benefits and Important features of SpendTrack
SpendTrack is the ultimate solution to easily track and categorize your income and expenses. Therefore, with automated SMS classification, payment reminders, and easy-to-use mobile and dashboard apps, you can take control of your finances. Moreover, with that you can make informed decisions about your spending.
Advanced Technology for Personal Finance Management using SpendTrack
Our innovative product, SpendTrack utilizes cutting-edge AI/ML algorithms. Additionally, our mobile app fetches and categorizes users’ bank transactional and payment due SMS. Additionally, this data is stored in a master data warehouse, enabling users to view categorized income and expenses. Furthermore, Kafka, as a message broker, speeds up data processing. Lastly, an access control list simplifies admin client management.
Categorical Classification and Merchant-Wise Classification using SpendTrack
Our solution offers categorical and merchant-wise classification, providing users with insights into income and expenses across various categories like shopping, travel, entertainment, and more. Additionally, the mobile app displays the total transaction sum within the selected date range. Furthermore, a payment reminders tab helps users keep track of pending dues with due dates, payment links. The admin dashboard facilitates client and user management, as well as data classification from SMS.
Unique Architecture and Measurable Impact using SpendTrack
SpendTrack features a unique architecture comprising the web app, Android app, and SDK. Users authenticate via the middleware/authentication layer and create a client profile. Notably, each organization receives a unique secret key for client use, which generates tokens for the client’s users in the SDK. Therefore, the ML engine utilizes named entity recognition (NER) to predict merchant names and due dates from payment reminder SMS which is accessible to Android users and the Web App Portal.
Unlock the Potential of Data Science with Aptus Data Labs
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