Project: LoneStar TL;DR: Making the application for loans less cumbersome through an easy breezy digital experienceStatus: DiscoveryShipping: TBD
Problem Alignment
The Problem
One of the business challenges that Upstart (and any lender) faces is validating the identity of those that apply for a loan. This verification ensures that the borrower is not using a false identity to fraudulently receive funds. Today, Upstart has a team of people that review documents provided by the borrower to verify their identity. A few problem areas that we are looking to solve for:
High-level Approach
Hypothesis:
If Upstart could easily identify borrowers during the identification process, it would greatly increase the amount of verifications in a shorter amount of time, resulting in less drop-offs and more approvals.
Assumptions:
Proposed Approach & Business Case
For both borrowers and Upstart’s internal teams, we will introduce a digital platform called Breezi that allows for both the borrower and Upstart team to identify and quickly approve or disapprove a borrower’s request for a loan. This will be a two-sided experience that leverages AI/ML engines in order to pre-qualify candidates as well as highlight metrics for approval teams at Upstart to make quick and accurate decisions on whom to approve outside of pre-qualified candidates. Finally, in order to differentiate from other lender’s like Better or LendingTree, we will also test a pilot in partnership with Redfin and Automobile companies. Additionally, Breezi will introduce an experience that will allow borrowers to upload necessary documentation (e.g. driver’s license), where Breezi will leverage image classification to take information from the license and instantly verify the identify of the borrower.
For the borrower, an individual will provide a certain amount of information, in which Upstart will collect and consume. A soft credit check will perform as well as analysis of spending habits to return a ‘pre-qualified’ approval. Once an approval is made, Upstart will collect the borrower’s bank information to deposit the account. In short, the borrow should be able to experience the following:
For the Upstart team, these users will be receiving all applicants’ data, regardless of immediate approval. They will be able to view insights powered by an ML engine that synthesizes spending habits, consumer’s personal data, and credit history to provide risk assessments that enables faster decision making for the team. In short, the Upstart team should be able to experience the following:
For Partners (e.g. Redfin, Mercedes etc.) , with whom we have a shared service agreement, will have access to Breezi. The use case here is so that when consumers come in for an in-person experience (e.g. viewing a potential home to purchase), that staff can easily leverage Breezi’s platform to quickly approve borrowers for money and move to the next step in purchasing the asset. In short, staff from our authorized partners should be able to:
Goals & Success
In terms of what success looks like for the above proposed solution and problem alignment, it’s important to note which metrics will attribute to the success of our solution. For both the borrower and Upstart team’s experiences, there will be separate success metrics for both. Those are:
Borrower Success Metrics
Metric
Description
Metric Area
Why is it important?
1
Borrower NPS
This will measure our loyalty and brand of the product/service we are offering
Net Promoter Score, Satisfaction with the Product
We can segment on protractors, detractors, and passives into different areas that will help us identify improvement areas
2
Monthly avg. # instant approvals
This will measure the average number of instant approvals per visitor to see how many instant approvals
Fast Approvals
This will help us see how many borrowers on average are instant approved
3
MRR
How much money we charge for this service per applicant on a monthly basis
Revenue
This will calculate how much revenue we are generating for the product we are providing per transaction
4
Monthly avg. # pending approvals
This will measure the average number of instant pending approvals per visitor to see how many instant approvals
Fast Approvals
This will help us see which loans are being applied to the most and which are generating the most revenue
5
Avg. time to complete application
Measure the average time it takes for the borrower to complete the application
Usability
This is a key metric to see how easy it is for a borrower to submit their information
6
Avg. time for instant approvals
Measures avg. time for instant approvals to take affect per borrower
Fast Approvals
This effectively measures the average time for approvals to be granted once an application starts
There are no rows in this table
rifi
Upstart Team Success Metrics
Metric
Description
Problem Area
Why is it important?
1
Avg. review time for applications
Measures the average time it takes to review non prequalified applications per borrower
Team Efficiency
This will help us see if Breezi helps speed up the process
2
Monthly avg. of non-prequalified applications that are approved by team
Measures avg. monthly applications that are manually approved by the team
Team Efficiency
This will help see how many applications are being reviewed manually vs automated by Breezi
3
OSAT
Overall satisfaction with Breezi to analyze and review applications/process
Product Delight
Let’s us know the team is satisfied with Breezi
4
WAU
This will measure Weekly Active Users with the team
User Engagement
This will help us pinpoint drop-offs or spikes of engagement for the Upstart Team
There are no rows in this table
Solution Alignment
Who Would Be Using Breezi?
The Borrower Experience
For the provider experience we want to focus on a few key areas:
⭐For the sake of this exercise, let’s assume the delivery team + cross-functional stakeholders met to size/discuss each feature in order to assign the RICE score ⭐
Borrower Features (Epics)
Feature
Description
Problem Area
RICE Score
1
Loan Selection
As a borrower, I’d like to be able to apply for a loan specific to a type of loan, so that I can borrow money from Upstart specific to my needs
Fast Approvals
10000
2
Provide Income and Personal Information
As a borrower, I’d like to provide income and personal information so that Upstart can verify my identity
Fast Approvals
10000
3
Instant Approvals
As a borrower, I’d like to get a instant approval, so that I can access loan money faster
Fast Approvals
10000
4
Provide Bank Information
As a borrower, I’d like to provide my bank information to Upstart, so that I can receive a direct deposit once my loan is approved
Fast Approvals
10000
5
Leverage MALI crypto
As Breezi, I’d like to leverage MALI’s cryptocurrency infrastructure, so I can process borrower transactions faster and get money into their accounts with haste
Fast Approvals
9000
6
Receive notifications
As a borrower, I should receive notifications from Breezi, so that I can be aware of important updates
Borrower Engagement
9000
7
Upload valid ID
As a borrower, I should be able to upload a valid ID, so that Breezi can verify my identify faster
Fast Approvals
10000
8
As Upstart, I’d like to integrate Veriff into Breezi, to allow for faster verification of borrowers
Fast Approvals
9000
There are no rows in this table
The Upstart Team Experience
For the Upstart Team experience, we will want to focus on a few key areas:
⭐For the sake of this exercise, let’s assume the delivery team + cross-functional stakeholders met to size/discuss each feature in order to assign the RICE score ⭐
Upstart Approval Team Epics
Feature
Description
Problem Area
RICE Score
1
Login and Account Setup
As an approver, I’d like to be able to log into Breeze, so I can view applications that need approval
Login and Registration
10000
2
View Pending Applications
As an approver, I’d like to be able to view pending applications, so that I can manually approve/reject them
Borrower Application Processing
10000
3
Search for Applications
As an approver, I’d like to be able to search for borrowers, so that I can quickly find borrowers I am looking for
Borrower Application Processing
10000
4
Review Risky Applicants
As an approver, I’d like to see borrowers who have been tagged as ‘risky’ and reasons why, so that I can make effective decisions quickly
Borrower Assessment
9000
5
Approve or Reject Borrowers
As an approver, I’d like to approve or reject borrowers, so that I can instantaneously let them know if their application status
Borrower Application Processing
9000
6
Borrower Analytics and Scores
As an approver, I’d like to see analytics and scores based in inputs and historical data, so that I can make effective decisions for pending applications
Borrower Assessment
9000
7
Notifications
As a borrower, I’d like to see important notifications from Breezi, so I know when to be informed and/or take action
Engagement
9000
There are no rows in this table
The Partner Experience
For the Partner experience, we will want to focus on a few key areas:
⭐For the sake of this exercise, let’s assume the delivery team + cross-functional stakeholders met to size/discuss each feature in order to assign the RICE score ⭐
Partner Features (Epics)
Feature
Description
Problem Area
Rice Score
1
Login and Access Breezily
As a partner, I’d like to access the Breezi Partner application, so that I can allow consumers to give input
Login and Access
10000
2
Review Options to Present to Borrowers
As a partner, I’d like to present different finanial loan options to buyers, so that I can easily discuss and convert them to purchase
Borrower Conversion
10000
3
Quick Approval
As a partner, I’d like for borrowers to be instantly approved, so that they can put up the necessary upfront costs
Borrower Conversion
10000
There are no rows in this table
High-level Diagram Of Data Input and Process
Sample Mocks
⭐For the sake of this exercise, the screens below were created from Figma, just to give an idea
Upstart Team App :
Partner Experience:
Product Strategy & Monetization
Who Will We Sell Our Product To?
Though our product will service as a B2C and a B2B product, we will primarily sell out product to the following ‘businesses’ and consumers:
How Does Breezi Make Up For Costs?
Costs & Revenue
Known Costs
Revenue Streams:
At a high-level we would sell Breezi via a service level agreement or contract agreement with partners. We will also charge a service fee per consumer, for the key value prop of providing instantaneous financial transactions within minutes via MALI crypto technology. This will enable us to:
Other Benefits:
Easier penetration into high-value markets such as Mortgage, Auto loan & lease and Personal loan:
Channels
Partnerships:
Social Media Channels and SEO:
Open Issues & Questions
Add a topic
Questions & Unknowns
Questions
Author
Upvote
Downvote
1
Is the partnership route opportunistic to them enough to purchase our product?
2
Do we already have an ETL mechansim to make sure data is normalized when consuming additional sources
3
From a legal persepctive, do we have to consider/abide by any new rules
4
What types of loans will we offer and what will we not?
5
Are we resourced enough Across the AI/ML, Engineering, and UI/UX team?
6
We don’t really know how much users are really willing to pay for his service
7
How much training and hiring will we need to do for the approval team?
8
In order to verify identity faster, can we leverage the AI/ML platform to scan a valid ID to speed up the process
There are no rows in this table
Resources
Want to print your doc?
This is not the way.
This is not the way.
Try clicking the ⋯ next to your doc name or using a keyboard shortcut (
CtrlP
) instead.