Thank you for your time today. First of all, may we ask you to introduce an overview of your company?
Our company was established in February 2006 as a non-bank company.
We have 450 employees in total and mainly provide consumer finance for home appliances, furniture, smart phones and so on. Recently, we have started to focus on Buy Now Pay Later service and would like to support the purchase of daily necessities in the future.
Thank you very much. I see that you have been in business as a non-bank for about 17 years. What challenges did you encounter before implementing our service in 2021 ?
There were four main issues.
(1) The speed of screening got more important in the market, and there was an urgent need to increase the ratio of automated screening.
(2) Due to time constraint on screening, could not fully utilize credit information, though there was plenty of information.
(3) Screening criteria have become more complexed, due to the use of various Electronic Know Your Customer (EKYC) methods, making it difficult to make appropriate judgments manually.
(4) About 30% of applications were from unbanked customers who do not either have bank accounts, nor external credit information.
I see. May we understand that you considered introducing our service to solve those issues?
Yes. External credit information and EKYC have a large amount of attribute information and alternative data including negative information. It was impractical to utilize all of the data by manual examination under the time constraints of screening. We thought that Artificial Intelligence could simultaneously improve the speed of examination and create a new examination model that fully utilizes such data.
(ACSI office)I see. Certainly, our AI credit scoring service, which takes advantage of the strengths of AI, can score and return results within a few seconds, which is nearly impossible for a person to handle in a short period of time, so it may be useful. How did you feel after you actually started with POC?
When we saw the actual situation of approving riskier customers and, conversely, rejecting safer customers, clearly expressed in numerical values, our expectations for the benefits of introducing an AI credit model have increased.
Duly noted yours. Now, what kind of results did you feel after the actual implementation?
I believe that we have been able to promote the digitalization of screening based on data rather than a personalized screening model. In addition, I feel that data analysis using AI credit scores as a starting point has facilitated early identification of issues and adjustment of screening criteria in response to changes in the market.
Well, since credit process is the core of your business, we are happy to hear that you have been able to transform from a personalized screening model to a digital one. So, are you satisfied with our solution?
Yes, we are very satisfied with the service, because although the AI model is complex, we do not have to worry about the details of the model, and we can consult with GAILABO in Japanese and English to confirm our issues, develop the model, and identify current problems. I feel that it is wonderful that they are able to develop models and identify current problems in a speedy and thorough manner.
I really appreciate you saying so. We will continue to make every effort to satisfy your company in the future.
By the way, what kind of company do you think GAILABO’s service is best suited for? Please let us know if it is not too much to ask.
I think it is a company in the growth phase, especially non-banks that are about to introduce AI scoring, or companies that have already introduced AI scoring but have left it in place. The reason is that GAILABO members have a lot of financial knowledge and cutting-edge AI technology, and they are not just an AI scoring vendor or AI tool provider. We are very satisfied with the service. Although we initially felt that the fee was a little high, haha, the improvement in the approval and collection rates has paid for itself in a big way.
We will continue to exceed your paid price! Thank you very much. Finally, what do you expect from GAILABO in the future?
We have been able to identify risk segments, but, they are volume zones. So further categorization is necessary. We continue to work together to refine the score model and optimize the screening criteria for this risk customer segment.
Of course. We will continue to do our best to solve your issues through our services, so please feel free to contact us if you have any question or concern. Thank you very much for taking time out of your busy schedule to talk with us today.
Thank you very much.
Left: Mr. Yasunori Narabayashi, President Director, PT.
