AI

Startups – Varo Money uses AI to Improve Customers Financial Health

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.

Further Reading/References

Summary

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.

Ajitesh Kumar

I have been recently working in the area of Data analytics including Data Science and Machine Learning / Deep Learning. I am also passionate about different technologies including programming languages such as Java/JEE, Javascript, Python, R, Julia, etc, and technologies such as Blockchain, mobile computing, cloud-native technologies, application security, cloud computing platforms, big data, etc. I would love to connect with you on Linkedin. Check out my latest book titled as First Principles Thinking: Building winning products using first principles thinking.

Recent Posts

Large Language Models (LLMs): Four Critical Modeling Stages

Large language models (LLMs) have fundamentally transformed our digital landscape, powering everything from chatbots and…

3 weeks ago

Agentic Workflow Design Patterns Explained with Examples

As Large Language Models (LLMs) evolve into autonomous agents, understanding agentic workflow design patterns has…

3 weeks ago

What is Data Strategy?

In today's data-driven business landscape, organizations are constantly seeking ways to harness the power of…

3 weeks ago

Mathematics Topics for Machine Learning Beginners

In this blog, you would get to know the essential mathematical topics you need to…

2 months ago

Questions to Ask When Thinking Like a Product Leader

This blog represents a list of questions you can ask when thinking like a product…

2 months ago

Three Approaches to Creating AI Agents: Code Examples

AI agents are autonomous systems combining three core components: a reasoning engine (powered by LLM),…

2 months ago