• Title/Summary/Keyword: Financial Big Data

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Big Data Strategies for Government, Society and Policy-Making

  • LEE, Jung Wan
    • The Journal of Asian Finance, Economics and Business
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    • v.7 no.7
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    • pp.475-487
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    • 2020
  • The paper aims to facilitate a discussion around how big data technologies and data from citizens can be used to help public administration, society, and policy-making to improve community's lives. This paper discusses opportunities and challenges of big data strategies for government, society, and policy-making. It employs the presentation of numerous practical examples from different parts of the world, where public-service delivery has seen transformation and where initiatives have been taken forward that have revolutionized the way governments at different levels engage with the citizens, and how governments and civil society have adopted evidence-driven policy-making through innovative and efficient use of big data analytics. The examples include the governments of the United States, China, the United Kingdom, and India, and different levels of government agencies in the public services of fraud detection, financial market analysis, healthcare and public health, government oversight, education, crime fighting, environmental protection, energy exploration, agriculture, weather forecasting, and ecosystem management. The examples also include smart cities in Korea, China, Japan, India, Canada, Singapore, the United Kingdom, and the European Union. This paper makes some recommendations about how big data strategies transform the government and public services to become more citizen-centric, responsive, accountable and transparent.

A Study on the Calculation and Provision of Accruals-Quality by Big Data Real-Time Predictive Analysis Program

  • Shin, YeounOuk
    • International journal of advanced smart convergence
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    • v.8 no.3
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    • pp.193-200
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    • 2019
  • Accruals-Quality(AQ) is an important proxy for evaluating the quality of accounting information disclosures. High-quality accounting information will provide high predictability and precision in the disclosure of earnings and will increase the response to stock prices. And high Accruals-Quality, such as mitigating heterogeneity in accounting information interpretation, provides information usefulness in capital markets. The purpose of this study is to suggest how AQ, which represents the quality of accounting information disclosure, is transformed into digitized data in real-time in combination with IT information technology and provided to financial analyst's information environment in real-time. And AQ is a framework for predictive analysis through big data log analysis system. This real-time information from AQ will help financial analysts to increase their activity and reduce information asymmetry. In addition, AQ, which is provided in real time through IT information technology, can be used as an important basis for decision-making by users of capital market information, and is expected to contribute in providing companies with incentives to voluntarily improve the quality of accounting information disclosure.

Real-time CRM Strategy of Big Data and Smart Offering System: KB Kookmin Card Case (KB국민카드의 빅데이터를 활용한 실시간 CRM 전략: 스마트 오퍼링 시스템)

  • Choi, Jaewon;Sohn, Bongjin;Lim, Hyuna
    • Journal of Intelligence and Information Systems
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    • v.25 no.2
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    • pp.1-23
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    • 2019
  • Big data refers to data that is difficult to store, manage, and analyze by existing software. As the lifestyle changes of consumers increase the size and types of needs that consumers desire, they are investing a lot of time and money to understand the needs of consumers. Companies in various industries utilize Big Data to improve their products and services to meet their needs, analyze unstructured data, and respond to real-time responses to products and services. The financial industry operates a decision support system that uses financial data to develop financial products and manage customer risks. The use of big data by financial institutions can effectively create added value of the value chain, and it is possible to develop a more advanced customer relationship management strategy. Financial institutions can utilize the purchase data and unstructured data generated by the credit card, and it becomes possible to confirm and satisfy the customer's desire. CRM has a granular process that can be measured in real time as it grows with information knowledge systems. With the development of information service and CRM, the platform has change and it has become possible to meet consumer needs in various environments. Recently, as the needs of consumers have diversified, more companies are providing systematic marketing services using data mining and advanced CRM (Customer Relationship Management) techniques. KB Kookmin Card, which started as a credit card business in 1980, introduced early stabilization of processes and computer systems, and actively participated in introducing new technologies and systems. In 2011, the bank and credit card companies separated, leading the 'Hye-dam Card' and 'One Card' markets, which were deviated from the existing concept. In 2017, the total use of domestic credit cards and check cards grew by 5.6% year-on-year to 886 trillion won. In 2018, we received a long-term rating of AA + as a result of our credit card evaluation. We confirmed that our credit rating was at the top of the list through effective marketing strategies and services. At present, Kookmin Card emphasizes strategies to meet the individual needs of customers and to maximize the lifetime value of consumers by utilizing payment data of customers. KB Kookmin Card combines internal and external big data and conducts marketing in real time or builds a system for monitoring. KB Kookmin Card has built a marketing system that detects realtime behavior using big data such as visiting the homepage and purchasing history by using the customer card information. It is designed to enable customers to capture action events in real time and execute marketing by utilizing the stores, locations, amounts, usage pattern, etc. of the card transactions. We have created more than 280 different scenarios based on the customer's life cycle and are conducting marketing plans to accommodate various customer groups in real time. We operate a smart offering system, which is a highly efficient marketing management system that detects customers' card usage, customer behavior, and location information in real time, and provides further refinement services by combining with various apps. This study aims to identify the traditional CRM to the current CRM strategy through the process of changing the CRM strategy. Finally, I will confirm the current CRM strategy through KB Kookmin card's big data utilization strategy and marketing activities and propose a marketing plan for KB Kookmin card's future CRM strategy. KB Kookmin Card should invest in securing ICT technology and human resources, which are becoming more sophisticated for the success and continuous growth of smart offering system. It is necessary to establish a strategy for securing profit from a long-term perspective and systematically proceed. Especially, in the current situation where privacy violation and personal information leakage issues are being addressed, efforts should be made to induce customers' recognition of marketing using customer information and to form corporate image emphasizing security.

Determinants of The Level of Information Distribution on Financial Statement

  • Van Thi Hong NGUYEN;Anh Phuong PHAM
    • Journal of Distribution Science
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    • v.21 no.6
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    • pp.91-97
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    • 2023
  • Purpose: Interim financial statements provide timely and qualified financial information for users. Hence, the importance of the interim financial statement is increasingly noticeable among information users. This research studies determinants of interim financial statements disclosure in Vietnamese-listed enterprises. Research design, data and methodology: The sample is 55 enterprises listed in VNIndex and is in the list of Forbes top 100 largest companies in 2020. Data was collected from interim financial statements for four years, from 2018 to 2021. GMM is used in this study. Results: The regression analysis results show that reporting lag has a positive impact on the level of information distribution of interim financial reporting; companies audited by BIG4 tend to have a higher level of information disclosure. The higher the return on assets, the more disclosure is made; the larger the company size, the greater the disclosure level. Owner equity structure and Leverage do not affect the disclosure level of interim financial reporting. Conclusions: The information disclosure level on the interim financial statement should be improved to increase transparency. In addition to continuing to encourage these companies to provide more information voluntarily, government authorities should have effective regulations to require sufficient information disclosure from other listed companies.

A study on the MD&A Disclosure Quality in real-time calculated and provided By Programming Technology

  • Shin, YeounOuk
    • International Journal of Internet, Broadcasting and Communication
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    • v.11 no.3
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    • pp.41-48
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    • 2019
  • The Management Discussion and Analysis(MD&A) provides investors with an opportunity to gain insight into the company from a manager's perspective and enables short-term and long-term analysis of the business. And MD&A is an important channel through which companies and investors can communicate, providing a useful source of information for analyzing financialstatements. MD&A is measured by the quality of disclosure and there are many previous studies on the usefulness of disclosure information. Therefore, it is very important for the financial analyst who is the representative information user group in the capital market that MD&A Disclosure Quality is measured in real-time in combination with IT information technology and provided timely to financial analyst. In this study, we propose a method that real-time data is converted to digitalized data by combining MD&A disclosure with IT information technology and provided to financial analyst's information environment in real-time. The real-time information provided by MD&A can help the financial analysts' activities and reduce information asymmetry.

An Analysis of Stock Return Behavior using Financial Big Data (금융 빅 데이터를 이용한 주식수익률 행태 분석)

  • Jung, Heon-Yong;Kim, Sang-Sik
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2014.10a
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    • pp.708-710
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    • 2014
  • 최근 금융 분야에서는 빅 데이터를 이용하여 주가예측 모형을 만들어내고 있으며, 특히 금융 시계열 자료의 변동성 집중 현상을 금융 빅 데이터를 이용하여 분석함으로써 세계 주식시장의 동조화 현상을 분석하고 있다. 본 논문에서는 한국과 중국의 일별 주가지수수익률과 일중 주가지수수익률을 이용하여 이들 2개 국가의 대표적인 주가지수 시계열 데이터에 변동성 집중 현상이 존재하는지를 보다 세밀하게 추적하여 양국 주식시장의 동조화 현상을 분석한다. 분석 결과, 한국의 KOSPI와 중국의 Shanghai 종합주가지수의 지수수익률 시계열 자료는 단위근이 존재하지 않으며, 변동성 집중 현상을 보이는 것으로 나타났다. 또한 한국보다는 중국 주식시장의 변동성 집중현상이 보다 강하게 나타나며, 이러한 현상은 일중 주가지수수익률 시계열 자료에서 보다 두드러지게 나타났다.

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A Study on Improvement of Accounting Curriculum in Big Data Age (빅데이터시대의 회계교육과정 개선방안 연구)

  • Jeong, Eun-Han;Kim, Kyung-Ihl
    • Journal of Convergence for Information Technology
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    • v.8 no.5
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    • pp.145-152
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    • 2018
  • The paper aims to present the direction in which accounting education should proceed to enhance the expertise of accounting works in the new era in which big data is the center. This paper examines the definition and analysis of big data, and reviews the effectiveness through big data development in accounting expertise with specific references. Also, this paper presents some of the plans selected by professional accounting bodies and universities to address the topic of big data in the accounting curriculum. According to the plan, big data could provide a blueprint for the future role of accounting and financial experts. Therefore, what this study suggests is to improve educational content by adding big data topics to current accounting curricula in order to help accounting professionals of future generations prepare for technologies related to big data analysis in advance.

Cases of Stock Analysis through Artificial Intelligence Using Big Data (빅데이터를 활용한 인공지능을 통한 주식 예측 분석 사례)

  • Choi, Min-gi;Jo, Kwang-ik;Jeon, Min-gi;Choi, hun
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2021.05a
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    • pp.303-304
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    • 2021
  • In the 21st century, as we enter the Fourth Industrial Revolution, research in various fields utilizing big data is being conducted, and innovative and useful technologies are constantly emerging in the world. Among several technologies recently in the big data era, among various fields utilizing some algorithms of artificial intelligence, it shines in the field of finance and is used for pin tech, financial fraud detection and risk management, etc., and recently Even in the booming stock market, it is used for investment prediction and investment factor analysis using artificial intelligence algorithm models. In this paper, we plan to investigate various research cases and investigate trends in how they are used in the stock market through artificial intelligence that utilizes big data.

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A Customer Segmentation Scheme Base on Big Data in a Bank (빅데이터를 활용한 은행권 고객 세분화 기법 연구)

  • Chang, Min-Suk;Kim, Hyoung Joong
    • Journal of Digital Contents Society
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    • v.19 no.1
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    • pp.85-91
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    • 2018
  • Most banks use only demographic information such as gender, age, occupation and address to segment customers, but they do not reflect financial behavior patterns of customers. In this study, we aim to solve the problems by using various big data in a bank and to develop customer segmentation method which can be widely used in many banks in the future. In this paper, we propose an approach of segmenting clustering blocks with bottom-up method. This method has an advantage that it can accurately reflect various financial needs of customers based on various transaction patterns, channel contact patterns, and existing demographic information. Based on this, we will develop various marketing models such as product recommendation, financial need rating calculation, and customer churn-out prediction based on this, and we will adapt this models for the marketing strategy of NH Bank.

Topic Analysis Using Big Data Related to 'Blockchain usage': Focused on Newspaper Articles ('블록체인 활용' 관련 빅데이터를 활용한 토픽 분석: 신문기사를 중심으로)

  • Kim, Sungae;Jun, Soojin
    • Journal of Industrial Convergence
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    • v.18 no.1
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    • pp.73-78
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    • 2020
  • To analyze the main topics related to the use of blockchain technology, the Topic Modeling Technique was applied to the 'Blockchain Technology Utilization' big data shown in newspaper articles. To this end, from 2013 to 2019, when newspaper articles on the use of blockchain technology first appeared, the topics were extracted from 21 newspapers and analyzed by time to 15,537 articles. As a result of the analysis, articles related to the utilization of blockchain technology have increased exponentially since 2015 and focused on IT_science and economics. Key words related to cryptocurrency, bitcoin and virtual currency were weighted high, although they differed depending on time. Blockchain technology, which had focused on financial transactions, gradually expanded to big data, Internet of Things and artificial intelligence. As a result, changes in corporate topics were also made together to expand into various fields at banks for financial transactions, focusing on large and global companies. The study showed how these topics were changing, along with the main topics in newspaper articles related to the use of blockchain technology.