Launch year: 2017
Country: France
Funds raised: 1.75 million euros in 2016 for Yelloan (founded in 2015)

Algoan provides a consumer onboarding platform for credit institutions and brokers

Concept description

  • Created in 2017, Algoan is the result of a French fintech’s pivot from B2C to B2B (Yelloan, founded in 2015). Their product simplifies the conditions of access to credit, while meeting the requirements of banking institutions.
  • Obtaining a loan is proving to be increasingly difficult, particularly since it requires a lot of investment in terms of time (number of appointments with banks to be planned, administrative documents to be collected and reviewed, etc.). In addition, the conditions for accepting loans have been tightened, taking into consideration a certain number of parameters relating to the borrower’s solvency and reliability. These conditions also tend to marginalize certain populations: people with inconsistent revenue, self- and unemployed people, etc.
  • The arrival in 2018 of the European revised directive on payment services (PSD2), which compels banks to share customer data (with their consent) with third parties, promotes banking transparency and could facilitate credit granting conditions by streamlining the usage of these datas in the customer risk analysis.
  • Based on these observations, Algoan’s strategy is in line with this approach by proposing to simplify access to credit through the implementation of a 100% digital and simplified customer journey, making it possible to:
    • Reduce the time it takes to ask for a loan (approximately ten minutes) and potentially obtain it
    • Minimize the risk of customer exclusion through accurate risk analysis

Value proposition

  • Algoan’s value proposition is embodied as an innovation in customer experience and credit scoring. This fintech offers banks and brokers a white labeled technology that allows a simplified analysis of the banking behavior of an individual or a professional asking for a credit
  • Simplification of the customer journey through the implementation of a chatbot integrating KYC services
    • The application uses a chatbot allowing the loan applicant to enter information on the good he wishes to finance (description, price, etc.). Once the application is completed, the user can easily share his banking datas by using a PSD2 data aggregator and linking his various bank cash accounts. From that moment on, the application with the applicant’s consent retrieves his bank details (salary, allowances, credit, rent, etc.) in order to establish his risk profile
  • Development of a credit scoring system for more accurate risk analysis
    • As soon as the customer data is retrieved by the application, the applicant checks the accuracy of the data. Once this is done, the data is analyzed to establish a credit score. This type of scoring, based on criteria of reliability and solvency of the applicant allows:
      • Evaluating and reducing the risk of fraud
      • Determining whether the applicant will be able to repay the loan
      • Establishing a customer profile for the bank
  • Obtaining and signing the loan agreement online through electronic signature
    • If the credit scoring is positive, the application then offers several possibilities in terms of loan offers (rate, monthly payment, repayment period, etc.). The candidate then selects the type of offer he wants to obtain and the chatbot asks him to complete his file by filling in a certain amount of information about his identity (identity papers, address, telephone number, etc.). From that moment on, the applicant can instantly get his loan via a digitally signed contract.

Illustration (Video)

PHP Code Snippets Powered By :
Scroll to Top