Dharma is my User Experience Capstone Project for Springboard.

Before I moved to Boston, MA, I had purchased my first home in San Diego, CA. The whole process was an absolute nightmare and the credit union I worked with was still stuck in the Stone Age, requiring me to physically scan and fax important documents. This was a problem that I saw, and experienced, first hand. When I decided to focus on a space (financial technology) that I had prior knowledge and experience in, I knew I wanted to create an app that would address this challenge.

Clare Nguyen

UX/UI Designer

Applying for a loan, mortgage, or even renting an apartment requires you to provide the lender or landlord with your financial information. Most of the time, your financial information can be difficult to gather and put together.

This problem is a tale as old as time – or at least as old as the 1200s! As society has advanced, so has the amount of information you need to supply. Strangely enough, one would think that with today’s technological advancements, physical papers would be a thing of the past or that everything would (mostly) be electronic, all located somewhere in the mysterious abyss known as “the cloud.” Unfortunately, this is not the case. I wanted to see how I could solve this challenge.

When I initially embarked on my journey, one of the first things I did was explore the financial tech space and see what my competition would be. Financial technology is defined as “new tech that seeks to improve and automate the delivery and use of financial services.”

Firstly, I wanted to see if what I was designing had never been done before (Spoiler alert: it has). Secondly, I wanted to see the competition in order to figure out their pitfalls and build an app that would be improved and better. Why reinvent the wheel?

As Picasso once said, “Good artists borrow, great artists steal.”

Pros: By logging in with your financial institution, Finicity is able to take a “screenshot” of the transactions. The AI then determines whether or not you qualify for the loan within minutes.

Cons: Based off of the brief video, I wasn’t able to tell if you could add more than one institution. It is unclear whether the AI is limited to one financial institution. How would you add additional assets?

Pros: Same model as Finicity. By logging in with your financial institution, Blend is also able to take a “screenshot” of the transactions. The AI then determines whether or not you qualify for the loan within minutes.

Cons: Blend also does not address whether or not you can add more than one financial institution. Neither Blend or Finicity address how you would include a co-signer or guarantor either.

Pros: Trulia is typically used for house or apartment rentals. Even though you cannot lend through Trulia, you can create a “rental resume,” where you input information about your income, credit score, and more.

Cons: Unfortunately, there is no verification when it comes to what an individual can submit. They can put in bogus information and the broker would have no idea.

I discovered that including a guarantor or co-signer in the apartment rental process was tedious. It was tough for my interviewees to play the middleman between their guarantor/co-signer and the landlord or broker. This actually delayed things a bit as the applicant would have to tell the guarantor what documents they needed, the guarantor would collect it, and then the applicant would have to forward those over to the landlord or broker. It definitely slowed things down.

But the biggest problem I noticed was that both borrowers and apartment applications experienced constant miscommunication between themselves and the lender or landlord. For example, there was one guy who was applying for a home loan. He said he spent over a month going back and forth with the underwriting agent because they kept telling him to resend documents he had already provided them. There was no way of determining whether or not they were actually receiving his documents or if they were simply disorganized and kept misplacing them.

The first order of business was to organize all of the data points by creating an Affinity Diagram. This diagram broke segments of each interview into seven different categories. After reviewing the data, I came to the conclusion that users fell into two categories: confident or anxious.

Those who were confident tended to be more established. They were older (in the 27-32 age range), had a stable career, and were very financially smart. They knew whether or not they would qualify for a loan.

The anxious users were predominantly made up of those who applied to rent an apartment. Most of them had no prior experience renting an apartment before, had no full-time jobs as they were students, and had to rely on their parents as guarantors/co-signers.

With a clear understanding of what issues I needed to address in my app, I created a persona to help keep me anchored to the original challenge.