Deko Pay

Deko is a multi-lender payment platform designed to enable flexible checkout finance for both merchants and consumers. Its core proposition is to support any basket, anytime, anywhere, allowing businesses to offer tailored financing options seamlessly within the purchasing journey.

The platform connects multiple lenders in a single ecosystem, intelligently matching customers with suitable finance options to improve conversion rates and create a smoother checkout experience. By centralising lender integrations, Deko reduces complexity for merchants while increasing accessibility to finance for end users.

With a strong focus on scalability and continuous expansion, Deko evolves its offering to meet diverse business needs, positioning itself as a trusted partner in retail finance. Its product culture is grounded in clear values - doing the right thing, being bold, and operating as one team - which support collaborative delivery and customer-centric decision-making.

Pre-Qualification Tool

Reducing drop-off and increasing trust through upfront eligibility insights

Overview

The Pre-Qualification Tool was introduced as a key enhancement to the Deko finance application journey, addressing one of the most critical drop-off points: user hesitation before applying for finance.

Many customers abandoned the process due to uncertainty around approval and concerns about negatively impacting their credit score. The goal of this project was to introduce a low-friction, confidence-building step that would allow users to check their eligibility upfront through a soft credit check, without affecting their credit profile.

By providing early feedback on loan eligibility and potential borrowing limits, the tool aimed to increase trust, reduce uncertainty, and improve conversion across the application funnel.

My Role

Product Designer

I worked within a cross-functional product team, contributing to:

  • product discovery and workshop facilitation

  • defining user journeys across multiple personas

  • designing wireframes, prototypes, and high-fidelity interfaces

  • running user testing and validation sessions

  • collaborating with product, engineering, and external stakeholders (lenders, merchants)

Team Structure

The project was delivered within a cross-functional team, including:

  • Product Designer (my role)

  • Product Manager

  • Frontend and Backend Engineers

  • QA (in later stages)

The Challenge

The project involved both product and business uncertainty.

From a product perspective, we needed to design an experience that could:

  • provide meaningful eligibility feedback with minimal user input

  • remain simple and fast, avoiding friction in the pre-application stage

  • balance clarity with the inherent uncertainty of credit decisioning

From a business perspective, there were several unknowns:

  • whether lenders would support the use of soft credit checks within their strategies

  • how to manage the cost of credit checks at scale

  • whether merchants would be willing to integrate the solution

  • how to design an MVP without a clearly defined precedent in the market

To address these uncertainties, we ran a series of discovery workshops to define the product direction and align stakeholders.

Product Goals

The product needed to create value across three key user groups:

Customers
To provide a clear indication of eligibility without impacting their credit score, increasing confidence and reducing hesitation before applying.

Merchants
To improve conversion rates, increase average basket value, and create a smoother purchasing experience by reducing payment uncertainty.

Lenders
To increase application volume and loan value while maintaining fair and responsible lending practices.

Research & Discovery

We began with market and competitor research, which revealed that while pre-qualification existed in the credit card space, there were no standalone solutions for retail finance. This positioned the project as both an opportunity and a risk.

To validate the concept, we worked closely with:

  • lenders, to align on feasibility and define MVP requirements

  • merchants, through focus groups to understand integration needs and business expectations

  • end users, through iterative testing of early concepts

Merchant feedback confirmed strong interest, particularly around ease of integration and its potential impact on conversion.

Design & Validation

We adopted a rapid, iterative approach, guided by a “fail fast, fail cheap” mindset.

Early concepts were translated into wireframes and clickable prototypes, which were tested in multiple rounds:

  • Initial in-house testing, focusing on clarity and usability

  • Iterative refinements, based on feedback around form length and output clarity

  • Guerrilla testing, conducted in real-world environments to gather broader insights

One of the key learnings was that users preferred clear, definitive outcomes (e.g. loan amounts) over abstract probability scores, and that minimising form length was critical to maintaining engagement.

MVP Strategy

To reduce cost and risk, the MVP was designed as a partially manual solution, with lenders supporting eligibility checks behind the scenes.

This allowed us to:

  • validate the core value proposition

  • test real user behaviour in a live environment

  • minimise upfront technical and operational investment

Following alignment with internal and external stakeholders, the product was launched to market for further validation.

Outcome & Impact

The Pre-Qualification Tool proved to be a commercial success across all stakeholders:

  • Increased customer confidence and reduced pre-application drop-off

  • Improved conversion rates for merchants

  • Generated additional lending opportunities and revenue for lenders

The success of the MVP enabled continued investment in the product and further iterations.

Post-MVP Evolution

Building on the initial success, the next phase introduced affordability checks, providing more precise insights into how much users could borrow.

While more accurate, this introduced additional complexity and required a more detailed data input, highlighting the ongoing balance between accuracy and usability in financial products.