A note that outlines the development of a credit assessment model for the unbanked using unconventional data acquired from mobile phones

1. Author: Atyab Tahir
1
KREDITGEEK
Unconventional & Seamless Data| Real Time Credit Scoring| Instant Access to Money
KREDITGEEK aims to provide access to credit for people with little or no credit history – the
underbanked and the underbanked. Mainstream financial institutions have neglected this
group of customers for years due to their lack of solid credit rating, leaving them to be taken
advantage of by informal money lenders and pawn brokers. By use of its technology based
algorithm to make credit decision, KREDITGEEK is driven to bridge this gap and to provide
access to credit at fair and sustainable conditions to the non-prime market segment.
KREDITGEEK has developed a unique algorithm for scoring thin-file customers. Our value
proposition is that we would like to become a digital bank for the unbanked through use of
efficient of credit and risk
assessment. The
KREDITGEEK algorithm
would enable a fast,
convenient and effective
way to analyze the
‘bankability’ of customers
using unconventional data
from their phones. For this
we have developed a
proprietary credit scoring
technology, which uses
artificial intelligence and
machine learning to process up to 16,000 data points per application in order to determine a
KREDITGEEK
Better credit to
customers with no or
poor credit history
Home & Car Loans
Credit Cards & Ready Cash lines
Payday Loans
Pawn brokers & Informal Money lenders
Good Access to
formal Credit
No Access to
formal Credit

2. Author: Atyab Tahir
2
starting score for thin file customers within a few hours of interaction initiation. Working with
incomplete information, the algorithm would determine the correlation of various customer
behaviors to credit worthiness. It would eliminate the need of credit bureau in long term and
ensure a better decision quality using new data to fill in the gaps. KREDITGEEK would have
the ability to make credit decisions in real time data from various sources.
KREDITGEEK relies on machine learning and process automation across all drivers of the value
chaing from customer acquisition to collections.
KREDITGEEK could provide the basis for offering a wide range of consumer finance and digital
banking products to customers. These would include short term maturity loans like micro
loans ($30 to $300), to long term maturity loans like device and appliance financing ($ 200 –
$800). After the initial credit assessment, the customer would be given a minimum of $30 to
start establishing credit history. Over a period of time, KREDITGEEK would use information
from available data sources along with payment behaviors to enhance or decrease the limit
of customers. KREDITGEEK would use APIs of other apps and services to increase its data
collection sources, thereby increasing the potential to create a complete credit profile of its
customers.
KREDITGEEK is being designed as a standalone service, which could either be used by
individuals, MFIs, credit and leasing companies, and existing banks to reach out to the
underbanked. It would seamlessly integrate with banking applications to leverage the power
of data housed with potential partners.
This concept note was prepared by Atyab Tahir for Planet N Group and is the Intellectual property of Nadeem Hussain, Coach Planet N Group
Customer
Acquisition
Application
Scoring &
Under-
writing
Payout
Customer
Service
Cross-
Selling &
Retention
Collections
• Marketing
automation
• Customer use
based
offerings
• Cross channel
and cross app
flow
• 100% online
• Auto-
populated
using
tokenization
• 13 fields to be
provided by
customer
• Data scoured
from phone
and apps
• Initial credit
offering with
few hours of
interaction
• Credit limits
enhanced
automatically
using data
• Instant payout
to mobile
wallets
• Support
available for
accounts at
partner banks
• IBFT available
for non-
partner banks
• Multichannel
customer
services
including
phone, web
and apps
• Data driven
product
recommend-
ations
• Personal
finance
management
and
transaction
tracking
• Machine
learning
optimized
collection
process
• Default
predictions
and advance
warning
KREDITGEEK Partnership Model
POS Financing: Partner
with Stores, e-commerce
outlets, & PSPs to offer
consumer credit
Decision Outsourcing:
Help financial institions
offer credit to non-prime
customers
Data Analytics: Analyze
existing customer base of
banks, and FIs to gain
better insights