Varo Money, a fintech startup, is using AI (machine learning) along with mobile banking to improve customers’ financial health. It recently raised $45 million from a private equity giant, Warburg Pincus and The Rise Fund, a global impact fund.
The following are some of the features of Varo Money product which looks to have been created using machine learning algorithms/techniques.
- Predict cashflow projections for informed spending: This is one of the key features of Varo Money AI-powered product. A supervised learning problem which could be solved using multilinear regression analysis. The underlying machine learning model could take into account some of the following features to predict the cashflow in near future:
- Cashflow sources including regular income, extra money/earnings etc
- Classifying the spending habits (required spend such as bills,loans etc, nice-but-not-necessary)
- Customer profile attributes such as employability information, age, gender, location etc.
- Expenditure tracking
- Classifying the customer profile based on account information aggregation; This could/would be used for customizing product offerings to better fit/suit the customer needs. Here a combination of supervised and unsupervised learning algorithms may be used for various different purposes.
Given the fact that customers use mobile for all practical purposes and the information required for Varo Money AI products could easily be accessed from mobile device given the usage of mobile phones/tablets, it may not be difficult to comprehend why Varo Money is combining machine learning with mobile banking for offering their banking products to their customers.
Technologies behind Varo Money Products
The following is a list of technologies which looks to be used to build the Varo money mobile banking products:
- Java and related technologies such as Spring, Hibernate
- Microservices architecture, REST-based integrations
- Rules engine technology including event processing, real-time data analysis using tools such as Drools
- CI/CD tool such as Jenkins
- AWS for cloud computing platform
- Machine Learning, AI and NLP technologies
- Spark/MLib, TensorFlow
- AWS ML
For greater details on career opportunities, visit Varo Money Career page.
Did you find this article useful? Do you have any questions about this article or understanding AI and related technology details in relation to Varo Money products? Leave a comment and ask your questions and I shall do my best to address your queries.
He has also authored the book, Building Web Apps with Spring 5 and Angular.
Latest posts by Ajitesh Kumar (see all)
- 13 Programming Languages used for Machine Learning - January 6, 2019
- Linear Regression Explained with Real Life Example - December 29, 2018
- Top 5 Machine Learning Introduction Slides for Beginners - December 24, 2018