Fintech Startup FinArt Keeps Track of Expenses Using AI and ML

The traditional financial services industry has undergone a radical transformation in recent years. India has created an ecosystem that provides fintech players with an opportunity to exponentially grow into big businesses. Fintech startups are now delivering innovation that was previously difficult to achieve.

The global fintech market size is expected to grow to $124.3 billion by the end of 2025 at a CAGR of 23.8%. With a range of options, including e-wallets, digital payments, UPI, lending and insurance, the variety of services provided in this sector are immense and have changed the way consumers carry out their daily transactions. 

With a vision of keeping track of expenses and focus on user interface and privacy, money managing app, FinArt is utilising artificial intelligence and machine learning to fulfil its dream. Founded by Dinesh Garg and Harvinder Singh in 2016, FinArt, a bootstrapped startup, works on securing expense tracking and personal money management.

Flagship Product

FinArt is an android mobile application that processes business SMS alerts to keep track of expenses, bills, cashback/refunds, account balances, active subscriptions and more. It is an automated money management app, which transforms SMS inbox into smart expense reports for all banks and credit cards. The app provides intuitive reports and trends to give insights on any spending. Also, it has an automatic bill reminder, which notifies the due date from time to time. 

Use of AI/ML

FinArt has AI and ML capabilities that help in accurate and complete tracking of expenses, due bills, subscriptions, among others. The machine learning engine of FinArt processes a varied set of SMS formats, applies a huge set of regular expressions to evaluate different data points including expense amount, expense date, merchant name, expense categories, bill due date etc.

The core engine supports all major languages including English, Hindi, Tamil, Malayalam etc. and is adaptable to user interventions in the processed data, which essentially means users can tailor the app to their preferences. The company uses multiple technologies and techniques for AI/ML, including steam analytics, data pre-processing, etc. Also, the core elements of FinArt include SMS processing engine, language translation module, information extraction, action triggers, transformation personalisation, etc. According to the founders, AI and machine learning are the key drivers to position FinArt as a premium alternative to other free apps available in the market.

Core Tech Stack

The core tech stack of FinArt is built on fundamental principles of minimalism and end-user experience. Some of the frameworks used in the development are React Native, Flutter, DynamoDB and many customer proprietary engines. The company uses Java, Python, JavaScript, Android Studio and few other supporting tools to develop and maintain the app.

Challenges Faced

Talking about challenges faced, according to the founders, one of the biggest challenges they have faced is to convince users to pay for an app when there are free alternatives available. FinArt is a subscription-based app, and the developers consistently improved the app experience with deep AI and machine learning.

Potential Competitors

According to the founders, there are several apps that operate in similar space such as Walnut and Money View. These startups also provide SMS-based money management solution, but their monetisation model is based on financial product recommendations. 

Future Roadmap

The app has recently entered the top-grossing list on Google Playstore and in the next five years, the founders are expecting to make FinArt a household name by providing an unmatched experience to the subscribers.

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Ambika Choudhury
A Technical Journalist who loves writing about Machine Learning and Artificial Intelligence. A lover of music, writing and learning something out of the box.
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