MORTGAGE B2B SaaS 

OCROLUS MORTGAGE 

Mortgage product that leverages AI technology to accelerate the income verification process.

OVERVIEW

Ocrolus is a fintech company that uses AI-driven software to help small business and mortgage lenders to automate and analyze documents so they can make higher-quality lending decisions.

Our mission was to help mortgage lenders scale their business by expediting their underwriting process, so that they can make quicker lending decisions, and borrowers will get their loans approved faster to buy their dream homes.

Our team's goal was to design an intuitive user interface that can integrate with our customer's systems.

ROLE
Product Design Lead
UX Research Lead

TASKS
Lead UX design and research, facilitate design sprint workshop, conduct customer interviews & usability testing.

Example of Encompass loan origination system (LOS). It is a widely used system in the mortgage industry. 

NEW MORTGAGE TECHNOLOGY

Mortgage lenders use outdated loan origination systems (LOS) that have inefficient user interfaces.

Part of their workflow is that they have to manually verify multiple types of documents, including income statements, tax returns, & bank statements. It's time-consuming and leads to delays in loan approvals.

Our challenge was how might we develop an intuitive user interface and experience to help mortgage lenders expedite their income verification process?

BUSINESS CASE 

Why is it valuable to mortage lenders that we automate their process?

Income verification is a critical process when executing mortgage loans. Automating that process can make an underwriter's workflow a lot more streamlined and efficient.

Lenders who adapt to new technologies benefit from:

• Verifying multiple types of income quickly, which leads to more sales and increased business.
• There are many borrowers who claim self-employed income, and it's a very tedious and complex process. Automating these documents would significantly speed up the loan process.
• Advanced AI technology can reduce the risk of fraudulent mortgage documents, so lenders can make higher-quality decisions.

DESIGN THINKING FRAMEWORK

To help guide our product design, our team incorporated a Design Thinking framework. 

1. Define & identify opportunities in the mortgage lending space.
2. Conduct qualitative research to understand our customers needs and pain points.
3. Leverage design sprint workshops to rapidly ideate and prototype designs.
4. Conduct usability tests to test protytpes and let user feedback inform iteration process. 

USER RESEARCH 

To discover our product market fit with mortgage customers, we conducted exploratory research to deeply understand the needs, pain points, and opportunities in the mortgage process.

In 2022, I collaborated closely with the product marketing team to lead user and market research for Ocrolus' first major mortgage industry study.

Our research uncovered:

• Mortgage is a very complicated process.
• There are 4 major stages. A loan application generally starts from a Loan Originator and ends with Closers who have the final say before they qualify a borrower for a loan.

Other key insights we learned are:

• Reviewing and validating document data is a time-consuming & manual process.
• Overwhelming 90% of people we interviewed said a tool that could automate income information would be extremely valuable.

UNCOVERING CUSTOMER NEEDS

Our research validated the assumption that automating income would deliver high value to our mortgage customers.

But we needed to dig deeper. We needed to better understand how the mortgage income verification process works, so we conducted more targeted research.

We uncovered 4 key insights:

Income Types

• There has been an increase in self-employed borrowers. They have a complex set of documents to verify and it's become very time-consuming to calculate their income for loans.
• We learned that loan processors want a customizable interface that allows them adjust data based on income types.

Accuracy & Trust

• The most important part of the process for a mortgage loan is to make sure the data is absolutely accurate. Errors in data have severe consequences and can cause a lot of pain for both the lender and borrower.
• Automation software that improves the quality of the data will help build trust in new technology.

Transparency

• Mortgage teams need to be able to easily track, verify, update, and record during every step in the process.
• Mortgage specialists also need to see exactly how calculations are made, so it must be easily seen in the interface.

Technology

• One frequent complaint from mortgage loan professionals is that mortgage systems can be inefficient and difficult to use.
• They desire to have their data automated but are cautious.
• They need to trust that automation will be accurate and allow them to retain control on their tasks. AI technology needs to assist and not take over their jobs.

PRODUCT DESIGN IDEATION 

In the next step in our development process I faciliated a design sprint workshops to help our team rapidly ideate, prototype, and user test. Many on the sprint team haven't done a workshop like this before.

Since the project was on a very tight timeline, I designed an accelerated version of the design sprint where we ideated and created a solution within 2 days.

Key activities we did were:

• Lightning Demo
• Team researched and gathered inspirations and references.
• 4-Part Sketch
• They then did a series of concept sketching to illustrate what a potential solution can be.
• We then voted on a couple of solution ideas, created the user flow, and the UI designers helped create the storyboard.

PROTOTYPE VERSION 1

Based on our customer research and design sprint results, our UI designers created a prototype for rapid user testing.

Key features that we needed to include were: 

• An interface for self-employed income calculation
• Customizable wage earner income types
  Ability to add comments to files
• Simple interface that is intuitive to use.

USER TESTING

We tested the first prototype and we learned that:

• Self-employed feature was a major win and extremely valuable.
• They loved the ability to customize wage earner income types easily.
• Ability to add comments/notes also tested very well.

I shared the results with the team and we identified improvements to be made to the design.

CUSTOMER FEEDBACK

This participant has been in mortgage industry for 15 years and was so surprised there isn't a product already like this on the market. She's even thought of building one herself. So she was very excited about discovery our new product build.

PROTOTYPE ITERATION

Our first prototype version yielded positive results. But we made improvements based on the user feedback we collected. 

We discovered that for self-employed income calculations, all users wanted was to replicate a Fannie Mae 1084 form because they have already developed a mental model and certain processes to complete the form.

Fannie Mae 1084 form is a standardized document that they use to calculate self-employed income. It is a tedious process and if the data can be automated, it would significantly improve and speed up their workflow.

CURRENT ENCOMPASS INTERFACE

This what the Encompass loan origination system looks like. It is being used by at least 90% of mortgage specialists. Most are also using outdated PCs and Windows software. 

There hasn't been a lot of innovation in loan origination systems so even though it is frustration and not intuitive to use, mortgage lenders rely heavily on this software since there isn't a good alternative.

OCROLUS MORTGAGE AUTOMATION

Ocrolus launched their first mortgage product Q4 in 2023. But at the time when I built this case study, it was under an NDA agreement. In this image, it is  a replica of the beta version that will be launched.

Through our user data learnings to deeply understand a mortage lenders processes and point points, coupled with AI technology, a well-designed loan orgination user experience will help lenders speed up their entire underwriting process, and create a faster borrower experience.

OUTCOME + REFLECTION

Reflecting on my work on the Ocrolus Mortgage , I gained invaluable insights as a product designer through utilizing UX research and Design Thinking framework to inform our design and product decisions. The research and user testing data we collected guided our desing and product team to focus on building features that our clients actually need. 

This experience also gave me the opportunity to delve deeply into the mortgage lending culture, learning how people utilize technology. It was an insightful experience learning to identify significant opportunities to improve their processes, technology, and user experience. Also, working collaborately with the product marketing team, I learned the process of defining the right product market fit, and understanding how to engage with mortgage customers for a successful user adoption.

This project was a huge team effort, and I collaborated cross-functionally with designers, engineers, product managers, product marketers, product growth strategists, and customer success teams. I faciliated our first design sprint workshop, inviting our team to learn how to develop a product using  Design Thinking framework and how to ideate, prototype, and test rapidly.  Our team really enjoyed the workshop process and it helped to streamline their work as well as create better alignment with team goals. 

The user and market research we conducted was published in a white paper and it's been widely distributed in the mortgage industry. 

Download white paper