Crypto Project Category: Start-Ups
Decentralized credit scoring and microcredit
Colendi project is a credit scoring system that can leverage new sources of information about borrowers
to assess creditworthiness in addition to traditional measures. This technology creates financing
opportunities for new markets of underserved individuals and businesses. This is accomplished by
evaluating complementary and distributed data segments of a user with the help of machine learning
based credit scoring technologies. Early in the project, it was already apparent that there existed
common data paradigms for storage and evaluation of data sources, which could be implemented
across seemingly disparate data streams sharing specific underlying properties.
For example, transaction histories are very valuable tools in assessing creditworthiness, as steady
purchase habits over time may reveal stability and regularity that imply higher probabilities of on-time
payments and therefore lower probabilities of default. Transactions can be leveraged to score credit
across sectors and industries, from simple hardware stores to global shipping companies. They share
certain common attributes such as date of purchase, amount, descriptions of items, and involved
However, the same exact model for scoring credit based on hardware store transactions cannot be
directly applied to global shipping companies, as the industries and transaction characteristics
are very different. The financial sector is fraught with the overextension of models that do not
assume an inclusive purpose, thus eventually falling to faulty assumptions. Therefore, it is
important to allow the parameterization of any transaction history module to accommodate the
major modes of its related credit evaluation across several industries and sectors. The fine-tuning
of these base models and necessary supporting data integrations require substantial efforts,
expertise, and resources.
Considering data, the richest collection belongs to the users. By allowing Colendi
to access certain smartphone and social media data, users will be able to obtain an
initial credit score even without a record of accomplishment. he scoring algorithm
is designed for machine learning to become ever more sophisticated. Users will also
be entitled to decide which data to provide to Colendi, and even access their
corresponding data held by Colendi data partners.
The data-integration process is arguably the hardest part of building a trustworthy credit scoring
platform. The process can easily have intricacies such as incorrect or missing data, usage of the wrong
format, and so on. Businesses should always onboard the profile data first to assess its quality as a
data resource and do compatibility check with the environment in which the data will be integrated.
This brings up a complex and cumbersome development issue, which regular businesses cannot
afford the time or resources, while bigger businesses have a hard time to prioritize it to make a
viable platform that is valid for any potential customer.
The inevitable result is an anachronism, underdeveloped credit scoring mechanism that fails to be
inclusive for a pronounced proportion of the society. Therefore, adding to its comprehensive credit
scoring technology, Colendi creates an incentivization system that is designed and tested for the
purposes of rewarding data integrators that bring new data to the network.
Colendi proposes a specialized protocol on blockchain for credit scoring along a complementary system
to bootstrap global network growth to radically transform credit scoring by covering both unbanked and
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