Park Dae-young and Noh Yoo-bin (YU) and Kim Deok-hyeon (Kyungpook National University) Alliance, ‘CUCCI’ Team takes first place

Analyzed big data to develop ‘gentrification index’... Predicting gentrification regions

Provide preemptive systems and can use for business marketing

[November 23, 2020]   

<CUCCI, the YU and Kyungpook National Univ. alliance team that won the grand prize at the ‘2020 Financial Big Data Challenge’ contest>

(From left to right: Noh Yoo-bin, Kim Deok-hyeon, Park Dae-young)

 

  

  This regional college team comprised of students from YU and Kyungpook National University won the grand prize at the ‘2020 Financial Big Data Challenge’ held for the general public.

  They are the CUCCI Team comprised of YU’s Park Dae-young (25, Business Administration, senior) and Noh Yoo-bin (24, International Economics and Business, graduated) and Kyungpook National University’s Kim Deok-hyeon (24, Statistics, senior).

  This contest that was co-hosted by the Ministry of Science and ICT, National Information Society Agency, and BC Card was ‘Industrial and Commercial Growth Prediction Ideas Using Consumption Data.’ The participants used financial big data to submit analysis results on ▲manufacturer investment appeal (stock prices) through consumption data and manufacturer revenue analysis per item ▲real estate market prices through local consumption data and corporate revenue analysis, and ▲gentrification predictions using local consumption data and real estate prices.

  A total of 275 teams and individuals took part in this contest and after first document reviews on the excellence, commercialization, and social effects of ideas, seven teams that entered the finals on October 29 gave presentations that were reviewed, and a total of five teams were awarded. The CUCCI Team took first place to win the grand prize.

  The CUCCI Team predicted the commercial gentrification region based on ‘rising commercial districts, gentrification predictions.’ They collected BC Card financial big data platform data, number of foreigners living in Seoul, portal site search frequency, etc. to come up with main keywords that affect gentrification through social media network analyses. They were used as collected data to develop a gentrification index, and after conducting local status surveys for the predicted areas using the index, they verified the appropriateness of the index, thus receiving good evaluations.

  They said, “By using the ‘gentrification index’ developed based on analysis of big data, it will be possible to come up with countermeasures against gentrification that had negative impact,” and added, “After identifying the gentrification prediction region, it will be possible for the government to preemptively apply lease ceilings, or in the case of credit card companies, utilize it in a variety of fields such as in marketing strategies to promote credit card transactions.”

  YU Department of Business Administration senior Park Dae-young said, “It was quite difficult to study big data as I did not major in it. I sat in for special lectures on big data analysis provided by the school and I was able to learn the fundamentals through the big data utilization center of the Daegu Digital Industry Promotion Agency. Whenever I hit a wall while preparing for this contest, I spoke with Professor Kim Byung-soo to seek advice and it was very helpful. It has not been very long since I started studying big data, but I think this contest served as an opportunity to gain more insight on the utilization potentials of big data.”