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- After Andrew finished doing traditional credit analysis on the 2 individuals and 2 business owners, he realized that the process is slow and inefficient and he talked about it to his supervisor. His supervisor Tom also agreed with him as traditional credit analysis is too tedious and does not provide customer satisfaction and it targets too narrow of an audience. Additionally, traditional credit analysis is outdated and it can overlook various factors and thus making incorrect predictions about certain borrowers.
- Well Done Andrew! I think your idea is an great idea and definitely will benefit our bank in the future and I am going to allow you to arrange a board meeting and you can express your ideas to the higher-ups
- Yes i agreed, I also do think that the traditional way of doing credit analysis is too tedious and slow. Do you have any suggestions?
- Intern Andrew
- Additionally, traditional credit analysis is outdated and it can overlook various factors and thus make incorrect predictions about certain borrowers
- Supervisor Tom
- www.zoom.com
- Good Morning Supervisor, I have finished doing traditional credit analysis however I realized that the process is slow and inefficient
- Supervisor Tom urged Andrew to come up with a better way to evaluate people's credit scores if traditional credit analysis fails. Andrew decided to employ modern technologies to perform credit analysis, such as alternative data and machine learning, because it is better suited to today's digital consumer. In comparison to traditional credit analysis, it's also a considerably faster and more accurate approach.
- Hmm... We could use modern technology like using alternative data and machine learning to perform credit analysis to better cater to the digital consumer in today's context
- ���www.zoom.com
- Supervisor Tom
- Okay, here's to brush up on your knowledge. If there is a client who doesn't have much credit data for credit scoring, how would you suggest we evaluate her credit scoring?
- Andrew arranged a meeting with the board as his supervisor had given him a chance to express his idea of using alternative data and machine learning as well as modern modelling technique to do credit analysis as the bank current approach of evaluating credit risk of consumers and small business owners are too outdated or unattractive. Additionally, Alternative credit sourcing combines multiple sources such as airtime usage, digital payments, social media usage, geolocation and bill payment history.
- This will help the bank as traditional credit analysis is too inefficient and by improving our method of analysis will help to boost our bank profit
- Using Alternative Data, Machine Learning and Modern Modelling Technique
- The Next Day...
- Good Afternoon, Mr Lim, I am Andrew and My Supervisor and I would like to arrange a meeting with you to discuss about adopting a better credit analysis method
- In the meeting, many of the higher-ups are unable to work with insufficient data and each process takes time and they feel that the traditional credit method is too inefficient and changes must be made. Additionally, the chairman of board was not satisfied with the low success loan rate and customer satisfaction and asked me to suggest a way to improve our method of analysis in order to have more qualifying loan applicants. In this case, we should use alternative data and machine learning as it is more efficient and it can bring up data points that the traditional methods might have glossed over
- Vice Chairman: Mr Timothy Ong
- Chairman of Board: Mr David Lim
- We are unable to work with insufficient data and each process takes time
- Senior Executive Officer:Ms Veronica Chong
- University Intern:Andrew
- Chief Executive Officer:Mr Jerry Chan
- We should make use of alternative data and machine learning
- In the meeting, Andrew explained his ideas and proposal for alternative data and machine learning. Alternative data and automation with machine learning builds a profile of thin-file customers that do not have historical credit with financial institutions in the past which give our bank the potential to adopt them as your customers. On the contrary, the quality of the analysis is even more accurate than traditional analysis. Our new approach unearths new relationships and a better understand of the customer from the data pulled. As a result, the chairman of board accepted my proposal and decided to implement it.
- Vice Chairman: Mr Timothy Ong
- Chairman of Board: Mr David Lim
- Great Idea and Proposal! We should be able to work with sufficient data and process should be efficient
- Alternative data and automation with machine learning builds a profile of thin-file customers that do not have historical credit with financial institutions in the past which give our bank the potential to adopt them as your customers
- Senior Executive Officer:Ms Veronica Chong
- University Intern:Andrew
- Chief Executive Officer:Mr Jerry Chan
- Scene3: Bank arranges board meeting
- Why do we have low success loan rate and customer satisfaction?!
- We need to improve our method of analysis in order to have more qualifying loan applicants.
- Well done Andrew! We will implement alternative data and machine learning to perform credit analysis!
- On the contrary, the quality of the analysis is even more accurate than traditional analysis. Our new approach unearths new relationships and a better understand of the customer from the data pulled
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