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- The bank manager checks if John is eligible for a personal loan through his credit score to ensure his credibility of paying back the loan
- .
- John, a 35 year old man working as a salesman, wishes to renovate his home
- Scene 1 John applies for a personal loan
- John realized his credit score was too low to be eligible for a personal loan as he rarely uses his credit card and his loan was rejected by the bank
- The bank clerk asks John about his employment status, age and purpose of loan
- what is your employment status?
- John decides to go to the bank to apply for a personal loan
- A fintech specialist visited the bank and conducted a training workshop on the usage of alternative data for credit evaluation. He introduced machine learning to the staff for them to find out customers' repayment history such as their rental and utility payments to determine if they are eligible for the loan.
- Scene 2 The next day during an office meeting
- I suggest that we use alternate sources of data for credit evaluation.
- How do we collect the data?
- What kind of data?
- John receives a message from the bank informing him that his loan application is successful after the bank staff checked his clean bill payment and repayment history and decided that he is eligible for the loan
- John is persistent on renovating his home and reapplies for a personal loan again from the same bank but this time he does it online instead of heading down to the bank through alternative lending.
- Scene 3A few weeks later
- Let's reevaluate this customer's loan application!
- The bank staff receives John's loan appeal and they utilize their new machine learning technology to score John based on his payment behaviour.
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