Competitor analysis

To inform the redesign, I analyzed four industry leaders: Monzo, Revolut, Abound, and N26. These platforms were chosen based on their superior user retention and reputation for providing the most efficient loan application funnels in the market.

Loan calculation workflow

The public loan calculator acts as a "Low-Friction Hook." Ema can check the rate by adjusting the sliders without the commitment of an application. There is an intuitive graph visualization, which shows the loan amount as well as the interest amount. Once Ema has spent 60 seconds "playing" with the sliders, she has a psychological "Sunk Cost" and is more likely to click the "Apply Now" button.

Application Process

Ema then goes through a quick questionnaire with the purpose and income questions and an open banking linking which allows to receive a personalized offer. During this process the AI engine is leveraged by analyzing the Credit Bureau score and if the AI sees a history of stable utility payments (alternative data), it can offer a 0.2% "Reliability Discount" directly in the offer. The signature is allowed via a Smart id/Mobile id identification. The process is smooth and quick, there are no lengthy KYC forms to be filled out.

UI Design

The calculator screen contains the traditional sliders for the loan amount and duration. There is an intuitive graph visualization, which shows the loan amount as well as the interest. The summary provides the exact amounts and APR interest rate.

AI functionalities and architecture

The platform leverages AI across three critical vectors:

1) Predictive credit scoring and discount logic based on historical banking data;

2) Real-time auto-correction suggestions to streamline the KYC funnel;

3) Automated fraud detection to secure the identity verification process.

For instance, if a user uploads a utility bill where the address is slightly different from the National Registry, the AI doesn't just "Error Out." It uses Natural Language Processing (NLP) to reconcile the two (e.g., identifying that "St." and "Street" are the same) and asks the user: "We noticed a small difference; which one should we use for card delivery?".

Expected Outcomes

1) 35% Reduction in KYC Abandonment: Improving the onboarding funnel to retain more users during the verification phase.

2) 33% Uplift in Conversion Rates: Driving higher loan application completions through a more intuitive calculator interface.