• Journal of Internet Computing and Services
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• v.22 no.5
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• pp.69-77
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• 2021

The main channels of the financial industry are rapidly changing to mobile. In this environment, banks are focusing on information and communication technology to secure their competitiveness, and rapid innovation is being pursued especially in the payment settlement sector. In October 2019, Korea also introduced open banking services to accelerate the financial innovation, such as the open conversion of financial settlement networks and the expansion of the use of simple payments. In this paper, an empirical study was conducted on the effect of domestic open banking quality factors on usage intention. The service quality factors for open banking were classified into interface design, innovation, security, and data sharing, and the technology acceptance model (TAM) was used to verify whether it has a significant effect on perceived convenience, usefulness and intention to use. According to the analysis results, while innovation and security did not have a significant effect on convenience and usefulness, interface design and data sharing were found to have an effect on perceived convenience. The results would provide implications for some quality issues for companies seeking to introduce open banking services as well as for the related academic arena.

• KIPS Transactions on Computer and Communication Systems
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• v.7 no.2
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• pp.49-58
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• 2018

A certificate is a means to certify users by conducting the identification of the users, the prevention of forgery and alteration, and non-repudiation. Most people use an accredited certificate when they perform a task using online banking, and it is often used for the purpose of proving one's identity in issuing various certificates and making electronic payments in addition to online banking. At this time, the issued certificate exists in a file form on the disk, and it is possible to use the certificate issued in an existing device in a new device only if one copies it from the existing device. However, most certificate duplication methods are a method of duplication, entering an 8-16 digit verification code. This is inconvenient because one should enter the verification code and has a weakness that it is vulnerable to security issues. To solve this weakness, this study proposes a method for enhancing security certificate duplication in a multi-channel using TCP and BLE. The proposed method: 1) shares data can be mutually authenticated, using BLE Advertising data; and 2) encrypts the certificate with a symmetric key algorithm and delivers it after the certification of the device through an ECC-based electronic signature algorithm. As a result of the implementation of the proposed method in a mobile environment, it could defend against sniffing attacks, the area of security vulnerabilities in the existing methods and it was proven that it could increase security strength about $10^{41}$ times in an attempt of decoding through the method of substitution of brute force attack existing method.

• Agribusiness and Information Management
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• v.11 no.1
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• pp.27-39
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• 2019

Agricultural risks are exacerbated by a variety of factors ranging from climatevariability and change, frequent natural disasters, uncertainties in yields and prices, weakrural infrastructure, imperfect markets and lack of financial services including limited spanand design of risk mitigation instruments such as credit and insurance. Indian agriculture has little more than half (53%) of its area still rainfed and this makes it highly sensitive to vagaries of climate causing unstable output. Besides adverse climatic factors, there are man-made disasters such as fire, sale of spurious seeds, adulteration of pesticides and fertilizers etc., and all these severely affect farmers through loss in production and farm income, and are beyond the control of farmers. Hence, crop insurance' is considered to be the promising tool to insulate the farmers from risks faced by them and to sustain them in the agri-business. This paper critically evaluates the performance of recent crop insurance scheme viz., Pradhan Mantri Fasal Bhima Yojana (PMFBY) and its comparative performance with earlier agricultural insurance schemes implemented in the country. It is heartening that, the comparative performance of PMFBY with earlier schemes revealed that, the Government has definitely taken a leap forward in covering more number of farmers and bringing more area under crop insurance with the execution of this new scheme and on this front, it deserves the appreciation in fulfilling the objective for bringing more number of farmers under insurance cover. The use of mobile based technology, reduced number of Crop Cutting Experiments (CCEs) and smart CCEs, digitization of land record and linking them to farmers' account for faster assessment/settlement of claims are some of the steps that contributed for effective implementation of this new crop insurance scheme. However, inadequate claim payments, errors in loss/yield assessment, delayed claim payment, no direct linkage between insurance companies and farmers are the major shortcomings of this scheme. This calls for revamping the crop insurance program in India from time to time in tune with the dynamic changes in climatic factors on one hand and to provide a safety-net for farmers to mitigate losses arising from climatic shocks on the other. The future research avenues include: insuring the revenue of the farmer (Price × Yield) as in USA and more and more tenant farmers should be brought under insurance by doling out discounts for group coverage of farmers like in Philippines where 20 per cent discount in premium is given for a group of 5-10 farmers, 30 per cent for a group of 10-20 and 40 per cent for a group of >20 farmers.

• Journal of Digital Contents Society
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• v.19 no.1
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• pp.11-18
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• 2018

The Dutch treat culture, which pays for the cost of having meetings with a large number of people, is located in the daily life of many modern people. In particular, the execution of Kim Young-ran is a more active Dutch treat. However, when going dutch, there is a case where the amount of money to be paid per person is not divided equitably and there is an ambiguous situation about who should pay more. Also if one person have to pay all of the payments because of the different payment method such as a cash or card, there is inconvenience to keep a record of the financial relationship each time. In this paper, we introduce an application that allows several people to easily calculate the amount of money to pay per person when eating together or calculating something. From our service, you can easily access with web-based service, manage the user's debts more conveniently through forming the group. In addition, we focused on convenient calculation of cost by setting remaining unit and reserve function which is a function to overcome the disadvantages of existing application. Also, we maintain fairness through games in situations where the users need to make a choice.

• Journal of the Korea Society of Computer and Information
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• v.28 no.8
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• pp.21-30
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• 2023

The study proposes a model that utilizes Python-based deep learning text classification techniques to detect the legality of illegal financial advertising posts on the internet. These posts aim to promote unlawful financial activities, including the trading of bank accounts, credit card fraud, cashing out through mobile payments, and the sale of personal credit information. Despite the efforts of financial regulatory authorities, the prevalence of illegal financial activities persists. By applying this proposed model, the intention is to aid in identifying and detecting illicit content in internet-based illegal financial advertisining, thus contributing to the ongoing efforts to combat such activities. The study utilizes convolutional neural networks(CNN) and recurrent neural networks(RNN, LSTM, GRU), which are commonly used text classification techniques. The raw data for the model is based on manually confirmed regulatory judgments. By adjusting the hyperparameters of the Korean natural language processing and deep learning models, the study has achieved an optimized model with the best performance. This research holds significant meaning as it presents a deep learning model for discerning internet illegal financial advertising, which has not been previously explored. Additionally, with an accuracy range of 91.3% to 93.4% in a deep learning model, there is a hopeful anticipation for the practical application of this model in the task of detecting illicit financial advertisements, ultimately contributing to the eradication of such unlawful financial advertisements.