Consumer banking ica
Montāžas Teksta
- Slidkalniņš: 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
- Slidkalniņš: 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
- Slidkalniņš: 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
- Slidkalniņš: 4
- Streamlined Loan application
- applying for a loan is quick is easy through digital platforms the user friendly interface ensures a seamless application process
- Slidkalniņš: 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
- Slidkalniņš: 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
- Slidkalniņš: 7
- Intergrating green financing
Izveidoti vairāk nekā 30 miljoni stāstu shēmu