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AI for Good Innovate for Impact

Use Case- 3: AIZEN – CreditConnect-EV

[CreditConnect-EV]

Organization: AIZEN

Country: South Korea Contact Person(s):
Jihoon Lim, Jihoon.lim@ aizen .co
Jung Seok Kang, js.kang@ aizen .co

1 Use Case Summary Table

Item Details
Category Finance

A persistent financing gap is slowing the conversion to electric
twowheelers (E-2Ws) across Southeast Asia. Conventional lenders lack
Problem Addressed
the granular, real-time data and analytic tools needed to price risk accu-
rately, leaving many riders and fleet operators without affordable credit.

Internet of Things(IoT)-driven data capture: Continuous telemetry from
E-2W batteries (System on a Chip(SoC), temperature, charge cycles) and
on-bike sensors (speed, mileage, acceleration).
Behavioural analytics: Riding patterns, payment history, and geospatial
usage profiles enrich credit signals.
Key Aspects of Solu- Automated Machine Learning(AutoML) risk engine: Our proprietary
tion AutoML pipeline ingests these high-frequency data streams, predicting
residual value, default likelihood, and optimal loan terms in near real
time.
Embedded financing: Insights flow directly into the CreditConnect-
Electric Vehicle(EV) platform, enabling partner lenders to approve or
price loans that would be infeasible under traditional scorecard models.
Big-data telemetry, AutoML modelling, Predictive risk scoring, Edge/
Technology Keywords Cloud IoT, Application Programming Interface(API)-first embedded
finance

Data Availability Private

Metadata (Type of
Data) Text

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