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Storyboard Tekst

  • Dia: 1
  • Challenges in traditional Credit analysis
  • theres so much paper work to do to get approval for a loan to buy a machine for my cafe
  • credit history,income,taxes, ongoing loans
  • Traditional credit analysis methods often rely on limited data sources this causes inefficiencies in assessing borrowers risk Limited data points like credit history and income may not provide a full picture of a borrowers financial health
  • Dia: 2
  • Opportunity for innovation
  • how will my cafe survive the espresso machine is broken and i did not secure a loan
  • I was frustrated my loan got rejected as i did not have enough credit worthiness, i wish there was a way to be more inclusive by using other data that might help my credit evaluation
  • Dia: 3
  • The Fintech solution
  • Our solution uses alternative data sources such as transactional data to provide a more comprehensive credit assessment by using multiple and diverse data points we can get a holistic view of the applicants financial health
  • Dia: 4
  • Streamlined Loan application
  • applying for a loan is quick is easy through digital platforms the user friendly interface ensures a seamless application process
  • Dia: 5
  • Alternative Data collection
  • we collect a variety of alternative data points to build a comprehensive profile of each applicant Diverse data sources provide deeper insights into the creditworthiness of the borrower
  • Dia: 6
  • Advanced data processing and analysis
  • Our machine learning model analyse the data to deliver accurate and inclusive credit evauluations enhanced accuracy and inclusivity compared to traditional methods
  • Dia: 7
  • Intergrating green financing
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