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Crypto Project Category: Start-Ups

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    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
    banked populations.

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