Credit score is your multipass in the world of financial services. It helps you secure a loan, apply for a credit card, or rent an apartment. It’s a thread binding it all together in the intricate web of financial decision-making.

Today, the landscape of credit scoring is evolving, and it's not just about numbers and formulas anymore. AI, the powerhouse of modern technology, has woven its way into this domain, reshaping how lenders evaluate your creditworthiness.

In this article, I'll untie the workings of AI-powered credit scoring, explaining its benefits and challenges, algorithms, feature engineering, steps to build an AI-driven credit scoring system, and the coolest examples in Fintech. Find out how AI is revolutionizing an age-old system, changing how we access financial opportunities.

AI-powered robo-advisors lure billions in assets and thousands of users. For sure, they are here to stay, flaunting personalized insights and automated portfolio management.

Let’s delve into the process of developing your own robo-advisor from scratch. As you finish reading this guide, you'll pick up the essentials needed to create a top-class financial tool that can analyze users' financial situations, provide tailored investment recommendations, and manage portfolios seamlessly.

With release cycles becoming shorter and systems more complex, the need for quicker and more precise testing grows stronger. While there are lots of tutorials for unit testing, integration testing is often overlooked or confused with the former.

That’s why I start this article by explaining what integration testing is and why it’s indispensable. Also, I share recommendations from our solution development team to CTOs that work or intend to work with Java and are looking for best practices to solve the integration testing challenges and perfect their product.