With a stricter approval target on the lending algorithm, many new and existing users were getting declined for loan applications. This lead to most new users dropping off shortly after the loan decline. I was tasked with finding a way to reduce this drop-off.
40% increase in the # of users retained after loan decline.
Product Designer
Product Manager
2 Engineer
Data Analyst
QA Analyst
Week 1: Design
Week 2: Develop
Week 3: QA & Launch
The current loan decline flow forces users out of the app, with little context on what they can do to become qualified for a loan.
We see 70% of users deleting the app after a loan decline.
Graphic is frustrating to users
Users rarely have a second account
Unclear what to do to qualify
Have a clear path for how to qualify for a loan
% of users retained
Curbing risky loans through the ML based algorithm
% of loans defaulted
Build and keep trust with users through reliable service
# of loan decline support tickets
Users voice there concerns in reviews, to customer support, and during interviews
The business metrics are set during leadership meetings to align with investors
Product works cross team to determine what is indicative of a good experience
With a fake door test we were able to see what users were most inclined to interact with when if came to growing their loan eligibility.
We see 20% of users completed other feature flows such as bill pay & buying airtime.
Users are interested in becoming eligible
Not all users engage with the same features
We need more incentive to retain more users
Our data analyst showed the team that more than half the users were clicking into the rewards tab after loan decline.
The current “rewards” tab was nothing more than analytics on most likely empty data. No wonder users deleted the app afterwards.
We have a clear user incentive
We can utilize organic movement
The rewards tab is a blank slate
We know users are open to trying other features to grow their loan eligibility. We also know users are organically moving to the rewards tab in hopes of some money.
Using the incentive of monetary rewards, I developed a First Time User Experience that exposes users to all features within Umba.
Creates user habits around banking features
Leaves the users with a positive experience
Give users a head start to grow eligibility
40% of users retained
Features like bill pay & airtime turned out to be sticky features
<5% of loan defaulted
We set key levers that users can pull to affect our algorithm
2 week ticket backlog cut to 1 day
CE & Product set shared metrics that aligned our teams
Released in stages of users by 10%, 30%, 100%
Worked with finance to set reward amounts relative to average acquisition & retention costs
Partnered with CE to get support ticket data and consistent reporting on ticket backlog
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