隨著金融科技的發展，傳統銀行面臨著外界金融科技公司和大型科技公司所帶來的前所未有的壓力，傳統銀行必須要把握住金融科技所帶來的利好才能順應市場的發展，獲得發展先機。隨著信息化時代的到來，作爲金融科技手段之一的大數據分析對傳統銀行顯得十分重要。傳統銀行可以通過大數據分析來提高利潤、降低風險，甚至可以借此來增加客戶粘性。
本研究通過個案研究法，結合整理出的國内外參考文獻，對大數據分析在傳統銀行中的應用情況進行分析。通過半結構式訪談法與個案中國信託商業銀行資料經營部的副總經理進行深度訪談，訪談主要包括動機與背景、發展與應用、挑戰與限制、預期效益和未來規劃五個部分。
本研究結果發現大數據分析在傳統銀行的各個面向皆有應用，但大數據分析在給傳統銀行帶來巨大改變的同時，傳統銀行也面臨著很多挑戰。在未來，大數據分析在傳統銀行業會有更多的應用。希望通過本研究結果，能提供個案銀行發展大數據分析一些建議，也能作爲提供台灣銀行業在大數據分析發展計劃的一項參考。

With the development of financial technology, traditional banks are facing unprecedented pressure from external financial technology companies and large technology companies. Traditional banks must grasp the advantages brought by financial technology in order to adapt to the development of the market and seize the opportunity for development. With the advent of the information age, big data analysis, as one of the Fintech means, becomes very important for traditional banks. Traditional banks can use big data analysis to increase profits, reduce risks and even increase customer stickiness.
In this study, the application of big data analysis in traditional banks was analyzed through case study method and combined with domestic and foreign references. The semi-structured interview method was used to conduct an in-depth interview with the deputy general manager of the data management department of China Trust Commercial Bank. The interview mainly included five parts: motivation and background, development and application, challenges and limitations, expected benefits and future planning.
The results of this study found that big data analysis has been applied in all aspects of traditional banks, but traditional banks are also facing a lot of challenges while big data analysis has brought great changes to traditional banks. In the future, big data analysis will have more applications in the traditional banking industry. It is expected that the results of this study can provide some suggestions on the development of big data analysis in case banks, as well as a reference for the development plan of big data analysis in Taiwan banking industry.

參考文獻
一、 中文文獻
1. 台灣金融監督管理委員會（2016），金融科技發展策略白皮書
2. 沈中華、孫一仕、謝邦昌、盧陽正、王儷容、陳世訓、林士傑、賴威仁、盧淑惠、戴郁文、吳佩珊（2015），巨量資料（Big Data）於銀行業之應用與其成效，臺灣金融研訊院
3. 俞勇（2018），一文讀懂金融科技在金融行業的應用，銀行家雜誌
二、 英文文獻
1. Abadi, Joseph, and Markus Brunnermeier. Blockchain economics. No. w25407. National Bureau of Economic Research, 2018.
2. Anagnostopoulos, Ioannis, Sherali Zeadally, and Ernesto Exposito. "Handling big data: research challenges and future directions." The Journal of Supercomputing 72.4 (2016): 1494-1516.
3. Arner, Douglas W., Janos Barberis, and Ross P. Buckley. "The evolution of Fintech: A new post-crisis paradigm." Geo. J. Int'l L. 47 (2015): 1271.
4. ASIC (2016), Fintech: ASIC’s Approach and Regulatory Issues, July 2016.
5. BCBS (Basel Committee on Banking Supervision). "Sound Practices: Implications of Fintech Developments for Banks and Bank Supervisors." (2018).
6. Cearley, David W. "Cloud computing: key initiative overview." Gartner Report (2010).
7. Commission E. The EU Data Protection Reform and Big Data: Factsheet 2016
8. De Mauro, Andrea, Marco Greco, and Michele Grimaldi. "A formal definition of Big Data based on its essential features." Library Review (2016).
9. Drever, Eric. Using Semi-Structured Interviews in Small-Scale Research. A Teacher's Guide. 1995.
10. El Naqa, Issam, and Martin J. Murphy. "What is machine learning?." machine learning in radiation oncology. Springer, Cham, 2015. 3-11.
11. Fang, Bin, and Peng Zhang. "Big data in finance." Big data concepts, theories, and applications. Springer, Cham, 2016. 391-412.
12. Fast, Ethan, and Eric Horvitz. "Long-term trends in the public perception of artificial intelligence." Proceedings of the AAAI Conference on Artificial Intelligence. Vol. 31. No. 1. 2017.
13. Fenwick, Mark, Joseph A. McCahery, and Erik PM Vermeulen. "Fintech and the financing of entrepreneurs: From crowdfunding to marketplace lending." (2017).
14. Fidel, Raya. "The case study method: a case study." Library and Information Science Research 6.3 (1984): 273-288.
15. FSB (2016), FinTech: Describing the Landscape and a Framework for Analysis, 16 March 2016.
16. Giorgio Barba, et al. "Fintech and Banking. Friends or Foes?." Friends or Foes (2018).
17. Gomber, Peter, et al. "On the fintech revolution: Interpreting the forces of innovation, disruption, and transformation in financial services." Journal of Management Information Systems 35.1 (2018): 220-265.
18. He, Mr Dong, et al. Fintech and financial services: initial considerations. International Monetary Fund, 2017.
19. IOSCO. (2017). IOSCO Research Report on Financial Technologies (Fintech). February 2017.
20. Jagtiani, Julapa, and Catharine Lemieux. "Fintech lending: Financial inclusion, risk pricing, and alternative information." (2017).
21. Jain, Anil K., Arun Ross, and Salil Prabhakar. "An introduction to biometric recognition." IEEE Transactions on circuits and systems for video technology 14.1 (2004): 4-20.
22. Jeyakumar Rajeev (2017), The State of Fintech in 2017, 18 May 2017.
23. Jordan, Michael I., and Tom M. Mitchell. "Machine learning: Trends, perspectives, and prospects." Science 349.6245 (2015): 255-260.
24. Kakavand, Hossein, Nicolette Kost De Sevres, and Bart Chilton. "The blockchain revolution: An analysis of regulation and technology related to distributed ledger technologies." Available at SSRN 2849251 (2017).
25. Kambatla, Karthik, et al. "Trends in big data analytics." Journal of parallel and distributed computing 74.7 (2014): 2561-2573.
26. Kang, Jungho. "Mobile payment in Fintech environment: trends, security challenges, and services." Human-centric Computing and Information sciences 8.1 (2018): 1-16.
27. KPMG（2021）, Pulse of Fintech H2’20, February 2021.
28. Kutler, Jeffrey. "Citibank is shedding individualistic image." American Banker, August 13 (1993).
29. Le, Chien, and R. Jain. "A survey of biometrics security systems." EEUU. Washington University in St. Louis (2009).
30. Lee, In, and Yong Jae Shin. "Fintech: Ecosystem, business models, investment decisions, and challenges." Business Horizons 61.1 (2018): 35-46.
31. Lee, P. "The fintech entrepreneurs aiming to reinvent finance." Euromoney (UK) 46.552 (2015): 42-48.
32. Li, Xiaoqi, et al. "A survey on the security of blockchain systems." Future Generation Computer Systems 107 (2020): 841-853.
33. Marcus, Gary. "Deep learning: A critical appraisal." arXiv preprint arXiv:1801.00631 (2018).
34. Ma, Yue, and De Liu. "Introduction to the special issue on Crowdfunding and FinTech." (2017): 1-4.
35. Mell, Peter, and Tim Grance. "The NIST definition of cloud computing." (2011).
36. Milena, Zaharia Rodica, Grundey Dainora, and Stancu Alin. "Qualitative research methods: A comparison between focus-group and in-depth interview." Annals of the University of Oradea, Economic Science Series 17.4 (2008): 1279-1283.
37. Mills, David C., et al. "Distributed ledger technology in payments, clearing, and settlement." (2016).
38. NDRC (2014), So what is FinTech?. National Digital Research Centre. March 2014 [26 November 2014].
39. Nicoletti, Bernardo, Weis Nicoletti, and Weis. Future of FinTech. Basingstoke, UK: Palgrave Macmillan, 2017.
40. Nilsson, Nils J., and Nils Johan Nilsson. Artificial intelligence: a new synthesis. Morgan Kaufmann, 1998.
41. NIST. (2015). NIST Big Data Interoperability Framework: Volume 1, Definitions
42. Prabhakar, Salil, Sharath Pankanti, and Anil K. Jain. "Biometric recognition: Security and privacy concerns." IEEE security & privacy 1.2 (2003): 33-42.
43. Pranoto, Pranoto, Munawar Kholil, and Kukuh Tejomurti. "Fintech Lending: Challenge And Opportunities Of The Indonesia’s Loan Unbanked To Develop The Inclusive Financial Industry." Hang Tuah Law Journal 3.2 (2019): 105-119.
44. Puschmann, Thomas. "Fintech." Business & Information Systems Engineering 59.1 (2017): 69-76.
45. Rajaraman, V. "Big data analytics." Resonance 21.8 (2016): 695-716.
46. Ravi, Vadlamani, and Sk Kamaruddin. "Big data analytics enabled smart financial services: opportunities and challenges." International Conference on Big Data Analytics. Springer, Cham, 2017.
47. Rusk, Nicole. "Deep learning." Nature Methods 13.1 (2016): 35-35.
48. Sabhanayagam, T., V. Prasanna Venkatesan, and K. Senthamaraikannan. "A comprehensive survey on various biometric systems." International Journal of Applied Engineering Research 13.5 (2018): 2276-2297.
49. Schmidhuber, Jürgen. "Deep learning." Scholarpedia 10.11 (2015): 32832.
50. Slaughter, McKenzie M., and Telly V. Onu. "Internationalizing InsurTech–A Global Phenomenon in Different Markets." The InsurTech Book: The Insurance Technology Handbook for Investors, Entrepreneurs and FinTech Visionaries (2018): 88-90.
51. Silverman, David, ed. Qualitative research. Sage Publications Limited, 2020.
52. Stone, Peter, et al. "Artificial intelligence and life in 2030: the one hundred year study on artificial intelligence." (2016).
53. Truong, Thi. "How FinTech Industry is changing the world." (2016).
54. Tsai, Chun-Wei, et al. "Big data analytics: a survey." Journal of Big data 2.1 (2015): 1-32.
55. Urban, M. "Big data analytics in the fight against financial crime." (2014).
56. Wüst, Karl, and Arthur Gervais. "Do you need a blockchain?." 2018 Crypto Valley Conference on Blockchain Technology (CVCBT). IEEE, 2018.
57. Yaga, Dylan, et al. "Blockchain technology overview." arXiv preprint arXiv:1906.11078 (2019).
58. Zakir, Jasmine, Tom Seymour, and Kristi Berg. "Big Data Analytics." Issues in Information Systems 16.2 (2015).
59. Zhou, Kaile, Chao Fu, and Shanlin Yang. "Big data driven smart energy management: From big data to big insights." Renewable and Sustainable Energy Reviews 56 (2016): 215-225.