Launching a smarter mortgage simulator
The first cross-European app transforming mortgages across seven countries. It delivers a seamless digital experience for customers, simplifying the mortgage process while equipping advisors with tools to boost conversion rates
Key highlights:
Overview
A standout feature of the Company is the Simulator, which allows customers to quickly and accurately simulate various mortgage options. This tool is invaluable for advisors and brokers, as it helps them assess whether to proceed with a borrower and identify the most suitable mortgage products tailored to the borrower’s unique needs and financial situation.
Problem
Mortgage brokers and landers face the challenge of rapidly analyzing financial strategies and estimating project costs. They are tasked with quickly searching for products to secure the most competitive rates in the market while assembling a comprehensive mortgage package for potential borrowers.
The ideal mortgage solution isn’t just about offering the lowest rate—it’s about finding or crafting a solution that aligns with the borrower’s specific context and project goals.
Brokers add significant value by leveraging their expertise to provide customized, context-sensitive solutions. However, without efficient tools, this process can be time-consuming and prone to inefficiencies.
Research
To refine the Simulator feature, my initial research focused on understanding its architecture map. This exploration provided clarity on how the feature was constructed and the rationale behind its design. The architecture map also helped organize data mapping, differentiating between mandatory and optional inputs required to present property rates effectively.
In parallel, I conducted one-on-one interviews with customers to gain insights into their workflows, challenges, and user journeys. This qualitative research aimed to uncover pain points and identify specific areas for improvement within the app.
Research findings
Excessive Mandatory Data: The Simulator required too much mandatory data, making it difficult for advisors to create simulations quickly and efficiently.
Time-Consuming Process: Each simulation took an average of 10-15 minutes, significantly slowing down advisors’ ability to serve clients.
Lack of Customization: The available mortgage products were not tailored to the specific needs of borrowers, limiting the tool’s effectiveness.
Technical Results Presentation: The simulation results were overly technical, making it hard for advisors to interpret and explain the outcomes to borrowers.
Inability to Share Results: Advisors lacked a way to pass simulation results directly to borrowers, hindering collaboration and decision-making.
No Loan Request Integration: Even when borrowers agreed on a simulation, advisors couldn’t seamlessly generate a “Loan Request” from the simulation, adding an extra layer of manual work.
User persona Insights
At first glance, it seemed that all advisors shared the same primary goal: facilitating the bank’s sale of mortgages.
However, deeper user research revealed diverse motivations and workflows among advisors. The creation of personas was instrumental in capturing these differences, allowing the team to tailor features to specific advisor needs. One particular persona emerged as a focal point during the design process:
Core Traits: This persona prioritized speed and efficiency, often relying on phone or face-to-face meetings to conduct quick simulations and assist in decision-making for borrowers.
Key Motivations: The need for fast, reliable simulations to provide immediate insights during interactions with clients stood out as a critical requirement.
This persona became a key reference point for defining and refining the Simulator’s functionality, ensuring it addressed the specific needs of this user type.
User tasks
By developing journey maps and analyzing common advisor tasks, I identified key procedural points that we should address to enhance its effectiveness:
1. Quick Simulations: Advisors need to run simulations quickly during client discussions, whether over the phone or in person, to aid immediate decision-making.
2. Loan Consolidation: Borrowers often consolidate multiple loans or assets to reduce their loan-to-value (LTV) ratio, impacting the available mortgage products.
3. Debt-to-Income Ratio (DTI): Advisors must factor in the borrower’s DTI, which can affect the interest rate and the suitability of specific lender products.
These insights ensured the design accounted for critical financial variables and operational efficiencies, directly supporting the advisors’ workflows and client interactions.
Structure
Based on insights gathered from surveys and interviews, I developed a feature map that strategically outlines five critical task streams for the high-fidelity prototype:
1. Adding Loan Details – Inputting necessary financial data related to the loan.
2. Providing Borrower Details – Collecting borrower-specific information to personalize simulations.
3. Filtering and Selecting the Best-Fit Product – Enabling advisors to quickly identify and choose the most appropriate mortgage product.
4. Printing and Sharing Simulations – Allowing advisors to easily present simulation results to borrowers in a professional and accessible format.
5. Creating Proposals – Seamlessly generating loan proposals from the selected simulations.
6. Convert to Loan Request – Enabling advisors to finalize and submit simulations as formal loan requests directly within the platform.
This framework, rooted in the site map and user research, served as a foundation for guiding design decisions and ensuring alignment with user needs.
Sketching and idea validation
Using rapid sketching, I explored multiple design ideas and iterated quickly, gaining valuable feedback and sign-offs from the internal team and clients. This collaborative process enabled us to refine design patterns and achieve a shared understanding of the key aspects of simulation flow.
Key outcomes from this process included:
Identifying and defining screen types capable of handling multiple tasks, such as consolidating loans or applying discounts.
Validating workflows that would simplify complex tasks while maintaining functionality and efficiency.
These sketches and validations were instrumental in shaping a design that was both intuitive and effective, ensuring the final product met the needs of its users.
From Lo-Fi to Hi-Fi
Testing with low-fidelity prototypes provided crucial insights into user expectations and workflows. Observing user interactions and discussing their requirements and schedules highlighted areas for improvement. These observations informed the creation of a high-fidelity prototype that incorporated key features, such as:
• Visualization Tools – Improved data presentation for better user comprehension.
• Help Tooltips – Contextual assistance to guide users through the simulation process.
• LTV Slider – A dynamic tool to simplify adjustments in loan-to-value ratios during simulations.
New Challenges
The high-fidelity prototype, designed to simulate the actual experience, showed unexpected user concerns despite successfully completing simulations.
These challenges provided valuable insights for further refinements:
1. Understanding “Green Mortgages”: Users needed clearer explanations about specific terms like “green mortgage.”
2. Handling Multiple Borrowers: Users expressed a need to manage scenarios involving more than one borrower.
3. Revisiting Cases: Questions arose about handling borrowers who return after a long gap (e.g., three months).
4. Borrower Mismatches: Advisors faced difficulties working with cases where a borrower did not fit any available product.
5. Product Comparisons: A new requirement emerged for comparing various mortgage products for one or two borrowers simultaneously.
Considerations for Long-Term Development
To further improvement the platform and meet user expectations, the following long-term features are planned:
1. Flexible Simulation: Enable advisors to get simulations from multiple places, such as the in-app widget or the landing page.
2. Product Comparison: Introduce a comparison feature for various mortgage products, allowing advisors to present options clearly.
3. Simulations for Multiple Properties: Allow advisors to create simulations that include multiple properties in a single analysis.
4. Advanced Settings: Provide more specific configurations tailored for experienced advisors.
5. Customized PDFs: Enable advisors to personalize simulation PDFs, incorporating branding or specific borrower details.
6. Note Collection and Sharing: Ensure that notes taken during meetings are automatically saved and shared with borrowers to maintain continuity.
Lessons Learned
Engaging customers early and verifying assumptions through conversations and testing helps eliminate ideas before investing significant time and resources.
During beta launches, focus on delivering essential features over refining the UI. Usability can be improved iteratively, but functionality must meet immediate user needs.
Users prioritize solutions that solve their problems effectively. Focus on creating valuable and desirable features before refining usability or adding delight.
Identify and address complex components or interactions early in the design and development process to avoid delays and minimize the risk of derailing release cycles.
Close collaboration with product managers, designers, and QA teams ensures smoother workflows, reducing inefficiencies like back-and-forth “GitLab ping-pong.”
Splitting larger tasks into smaller, manageable pieces leads to faster and more efficient progress.
Encouraging developers to proactively address potential implementation challenges fosters open communication loops. Early discussions help prevent small concerns from escalating into larger problems.