How to do quick user assign in kanban in Odoo 17 ERP
Nova Stanford 2016
1. Misha Gideon Nicky Loek
120 interviews
Enabling immigrants access to credit
through global credit data integration
2. This week:
5
Total:
88
Interviews
Key hypotheses
From B2C to B2B
From everyone to FCUs
From buying credit reports to
credit analytics
From lender to CRA
No lending license, become
a CRA
40+
60+
60+
10
5
Pivots # interviews
Customers can’t access
credit products
Lenders need
international data
They will be willing to
pay $100+
Nova can access this
data at a CPA of less
than $50
Nova is legal
Hypotheses
tested
Pass
Pass
Pass
In
progress
Pass
Pass/fail
3. This week:
5
Total:
88
Credit without borders
Interviews
Key stats
$220Bn
market
60%
approv
al rate
$1,000+
CLTV to
Lender
$100
ARPU
50%
Gross
Margin
$20 Av.
cost
per
report
$10/$120
b2B/b2C
CPA
3%
default
rate
3 pilots
[NEW]
$200
CLTV to
Nova
5. This week:
5
Total:
88
Interviews
Nova has evolved
Esoteric
asset
financing
crowdfunding
Student Credit Lines @
Student Loan Rates
International Student
Credit Cards
Student
Lending
Solution for
Corporate
Sponsors
Foreign
Professional
LeadGen
International Credit
Data Aggregator for
B2B
Startup Garage (Fall ‘15) Lean Launchpad (Winter ‘16)
Where we started
6. Scrape international data
This week:
5
Total:
88
Interviews
Original BMC
Key Activities
Key Partners
Value Props
Customer Relationships
Channels
Customer Segments
Revenue Streams
Connect and map to FICO
Local banks will be willing to partner
International banks will be willing to partner
Borrowers access more/cheaper products
CUs underwrite better, faster, cheaper
Nova provides new and valuable data to CRAs
Education to immigrants on USA system
Existing GSB relationships
Non-GSB customer relationships
Leads from FCUs
Non-immigrant workers
Lenders
Immigrants
Receive $100 per B2B underwrite decision
International CRAs will be willing to partner
capital in the US and realize their
potential
Data marketing at immigrants
7. Holding customer hand to export international data
This week:
5
Total:
88
Interviews
Business Model Canvas
Key Activities
Key Partners
Value Props
Customer Relationships
Channels
Customer Segments
Revenue Streams
Connect global CRAs together
Credit unions underwrite immigrants
Secure lending license asap!
More/cheaper products
CUs underwrite better, faster, cheaper
CRAs a data provider not a customer (yet!)
Education to immigrants on USA system
National Organization of Credit Unions
GSB connections for mentors and advisors
A tonne of bottom up research!!
CUs bring us leads
H-class immigrants
Direct marketing a second order priority
Lenders
Workers in home country
Receive $100 per B2B underwrite decision
Customer approval avoids need for CRA integration
10. Immigrants feel like “second class citizens”
● Secured cards
● Exorbitant rates with tiny credit limits
● Rejection
● Resort to taking loans from family or
local immigrant diaspora
This week:
5
Total:
88
Interviews
Story 1: Second-class citizens
Validated in 40+
interviews
11. This week:
5
Total:
88
Interviews
Customer relationships and segments
Selling to all lenders
Targeting Aussies in
Silicon Valley
Credit Unions with a high
immigrant base
H-1B visas from India and
China
What we thought What we learned
Customer
relationships
Customer
segments
BMC
12. Interviews
This week:
5
Total:
88Credit without borders
● Absence of credit
options
● Distrusting of
products, want to
have a trusted brand
name
● Value simplicity
● Desire for growth and
serving their needs
Validated in 40+ interviews
14. Lenders have hacks in the absence of
proper information. Auto manufacturers
have programs for foreign professionals
without credit history. Credit Unions, in the
absence of good quality data, make non-
data driven lending decisions based on
affiliate networks or incomplete
information. They all have a need for
good quality international credit
information.
This week:
5
Total:
88
Interviews
Story 2: Quality data solves
a real pain point
Validated in 60+
interviews
15. This week:
5
Total:
88
Interviews
Promising large scale
origination
Partnering with CRAs
Focusing on global
Channels, partners and regulatory
Delivering pure B2B
Data aggregation
US data import
Channels
Key
partners
Reg.
What we thought What we learnedBMC
16. This week:
5
Total:
88
Interviews
Bottom-up: door-to-door
with Bay Area credit
unions
Through the middle:
mapped the credit union
space and COLD CALLED
Top-down: National Credit
Union Foundation, Filene
We got out the building
Interviews: foreign
professionals and Stanford
students
Survey: immigration
survey
Feedback: various MVP
processes
US CRAs: US credit
reporting agencies
Int’l CRAs: international
CRA partnerships
Regulation: process, timing
and cost of becoming a
CRA
17. This week:
5
Total:
88
Interviews
Story 3: Disrupting the CRAs
Regulation to become a consumer
reporting agencies is much easier than to
become a lender and we can get a CRA
license quickly and inexpensively
Validated in 20+
interviews
18. This week:
5
Total:
88
Interviews
“Stories” have translated into thematic shifts
User pays
Broker / issuer of financial
products
Partner pays
CRA
Revenue
streams
Reg
What we thought What we learnedBMC
19. ● No fatal flaw in business model
● Nova will be regulated as a consumer
reporting agency (CRA) because (i) retain
consumer information and (ii) receive
revenue from lenders
● No licensing required to become a CRA
simply requires proper disclosure (1.5
weeks)
● Nova cannot deny services to US citizens
● >50% chance of getting a patent!
Interviews
Nova will be regulated as a CRA
● Engaged Pillsbury Law through
Startup Legal Garage
25. Interviews
Market sizing
42.1MTotal Global Citizens in the
US as of 2015
1.4MNew-to-country students and
professionals in the US in
2014
$155BPotential revenue from
Global Citizens in the US
26. This week:
5
Total:
88
Interviews
Channels - what we found and did
What we foundWhat we did
Virtual product, virtual channel Data aggregator, validator, processor
B2B channel sell through lenders White-labeled Nova terminal
B2C channel origination through website Nova landing page. Started (digital) marketing
Virtual product B2B: data visualization & summary
Start with Nova dashboard. Later API integrations
with existing underwriting software
Future channel potentially selling aggregated data
Maintain database with as much raw data as
possible to gather
Editor's Notes
Without tailored products, they resort to taking loans from family and local immigrant diaspora to fill their credit needs. If someone was able to offer them proper credit products, this would have a powerful word of mouth effect (like the mythical Israeli auto lender “Eric” who gets new arrivals better deals).