Open API Research Articles

New Sustainable Fintech Business Models Created by Open Application Programming Interface Technology: A Case Study of Korea’s Open Banking Application Programming Interface Platform

Fintech facilitates financial inclusion by introducing new sustainable and accessible business models in developing countries. Open banking API technology is used by various fintech businesses in both developing and developed countries, with varying effects on financial markets. It changes the financial market distribution structure by separating financial product manufacturing and distribution and intensifying competition between traditional financial institutions and fintech companies. Fintech companies innovate by using this tool to create new business models. In December 2019, Korea established a standardized “open banking API platform”, sharing an interbank payment network with fintech companies. It has since shown explosive growth, surpassing the trading volume of the UK, the country that introduced open banking APIs for the first time. This study analyzes new business models fintech companies created using this API technology. Based on existing literature, statistics from the platform operator (the Korea Financial Telecommunications and Clearings Institute), and investigations of 30 Korean fintech mobile applications, this study analyzes new fintech business models that provide financial services using this platform. These companies create sustainable business models by combining multiple APIs. Four representative business models (simple funds transfer, simple payment, cross-border remittance, and asset management) are analyzed to reveal how fintech companies create business models with open APIs.

The Innovation of Digital Payment System with QRIS in National Open API and Maqasid al-Sharia Standards

QRIS is a digital payment system innovation standardized as a national QR code in Indonesia. This paper analyzes the National Open API and Maqasid al-Sharia standards within the QRIS digital payment system. Employing a qualitative descriptive methodology, the study determined that Bank Indonesia formulated three National Open API standards: governance guidelines, data standards with technical specifications, and technical and safety standards. Aligned with Maqasid al-Sharia, the analysis reveals a significant correlation between QRIS and its core tenets, specifically Hifz ad-Din (safeguarding religion) and Hifz al-Mal (preserving wealth). Moreover, viewing maqasid as a methodological framework, QRIS is deemed a legal and halal system conforming to maqasid. This topic can be examined from five dimensions: the payment system's alignment with Sharia law, its widespread use among traders (urf tujjar), the contractual adherence (ijab qabul) to Islamic sharia and user benefits, the reflection of service value in QRIS service fees, and mutual advantages for both parties. Regarding maslahah, QRIS falls under dzanni maslahah, necessitating its implementation to be entrusted to contemporary mujtahids for the continued benefit of users

Spatial accessibility and equity of community healthcare: unraveling the impact of varying time and transport mode.

Achieving a higher level of accessibility and equity to community healthcare services has become a major concern for health service delivery from the perspectives of health planners and policy makers in China. In this study, we introduced a comprehensive door-to-door (D2D) model, integrating it with the open OD API results for precise computation of accessibility to community hospitals over different transport modes. For the D2D public transit mode, we computed the temporal variation and standard deviation of accessibility at different times of the day. Additionally, accessibility values for D2D riding mode, D2D driving mode, and simple driving mode were also computed for comparison. Moreover, we introduced Lorenz curve and Gini index to assess the differences in equity of community healthcare across different times and transport modes. The D2D public transit mode exhibits noticeable fluctuations in accessibility and equity based on the time of day. Accessibility and equity were notably influenced by traffic flow between 8 AM and 11 AM, while during the period from 12 PM to 10 PM, the open hours of community hospitals became a more significant determinant in Nanjing. The moments with the most equitable and inequitable overall spatial layouts were 10 AM and 10 PM, respectively. Among the four transport modes, the traditional simple driving mode exhibited the smallest equity index, with a Gini value of only 0.243. In contrast, the D2D riding mode, while widely preferred for accessing community healthcare services, had the highest Gini value, reaching 0.472. The proposed method combined the D2D model with the open OD API results is effective for accessibility computation of real transport modes. Spatial accessibility and equity of community healthcare experience significant fluctuations influenced by time variations. The transportation mode is also a significant factor affecting accessibility and equity level. These results are helpful to both planners and scholars that aim to build comprehensive spatial accessibility and equity models and optimize the location of public service facilities from the perspective of different temporal scales and a multi-mode transport system.

An IoT system based on open APIs and geolocation for the prevention of human health disorders

The article presents a study devoted to improving the developed Internet of Things system based on open APIs and geolocation, which is aimed at analyzing data about the state of the environment using an expert approach and data visualization for possible prevention of human health disorders. Based on the developed Internet of Things system, open APIs, geolocation using intelligent gadgets, and the Meteorological Geographic Information System, the study generates a message about the danger to human health associated with meteorological factors. Accordingly, a person is informed promptly about potential risks and threats, particularly about the presence of pollen in the air, indicating the level of its concentration in the air, and about problems with air quality. What is the “anthropo-geo-sensory-digital” prerequisite for making effective real-time decisions to prevent human health disorders? New features were added to the developed system to analyze data about potential risks and threats that could lead to human health disorders, in particular, about the presence of temperature problems, under the condition that this indicator goes beyond the normative and optimal zone; the presence of relative humidity problems, under the condition that this indicator go beyond the normative and optimal zone; the presence of wind speed problems, if the air wind speed exceeds the permissible standards. Effective decision-making based on providing timely information about potential risks and threats to human health, in addition to preventive, has significant methodological and technological potential that can be used to improve the effectiveness of health care, both in extreme conditions and in conditions of sustainable existence. The system developed and improved by us can also be considered as one of the ways of introducing innovations in health care, the IT field, the educational process in institutions of higher education and conducting further research in this field, in particular, in the direction of data processing in health care systems based on machine learning.

Interplay between Platform Providers and Complementors via Affordance, Autonomy, and Super-Modularity: The Empirical Investigation of the Korean Digital Industry

This study examines the dynamic interplay between platform providers and complementors in the context of digital ecosystems, focusing on the complementary factors of affordance, autonomy, and super-modularity. Using national survey data from the Korean digital industry, the study applied multivariate ordered probit and k-mode clustering models to analyze what determines these factors and how these factors are interrelated from the perspective of platform providers and complementors, respectively. The results indicate that platform providers with open APIs promote affordance, but providing an SDK inhibits affordance. In terms of complementors, choosing a platform providing APIs increases super-modularity. And affordance increases when using the platform for logistics and new product development. In addition, we found that affordance and autonomy have a trade-off relationship from the perspective of both platform providers and complementors. Finally, we classified platforms and complementors into subgroups with respect to affordance, autonomy, and super-modularity using cluster analysis and found that the size of a complementor’s firm, such as revenue and number of employees, influences which platform it chooses. Conversely, the size of a platform provider also influences how much autonomy and collaboration it offers. This study contributes to the understanding of digital platform ecosystems and provides insights for practitioners on how to leverage platform dynamics to enhance competitive advantage.

Designing a Weather Forecasting Application using API

A web-based tool called Weather Forecasting App gives users precise weather information according to their location. Numerous characteristics are employed in the proposed online application, including temperature, humidity, wind pressure, wind speed, dawn, and sunset times for the area. The precise locations of a forested and hilly environment can be found in this. All of the weather's parameter data was retrieved for this web application using a JavaScript API. To retrieve weather information specific to the user's location, the open weather map API is utilized in the suggested app.This web-based project is also a very responsive app that can provide a very interactive easy-to-use interface to the user on all their devices. Mean this app is a dynamic site that can change its orientation and size depending upon the user's devices. The purpose of weather forecasting is to provide individuals and organizations with information they can use to reduce climate-related losses and grow the community benefits, which include health and property protection, public health and safety, and support economic prosperity and a standard of living

An Open API Architecture to Discover the Trustworthy Explanation of Cloud AI Services

An Open API Architecture to Discover the Trustworthy Explanation of Cloud AI Services

NeuronBridge: an intuitive web application for neuronal morphology search across large data sets

BackgroundNeuroscience research in Drosophila is benefiting from large-scale connectomics efforts using electron microscopy (EM) to reveal all the neurons in a brain and their connections. To exploit this knowledge base, researchers relate a connectome’s structure to neuronal function, often by studying individual neuron cell types. Vast libraries of fly driver lines expressing fluorescent reporter genes in sets of neurons have been created and imaged using confocal light microscopy (LM), enabling the targeting of neurons for experimentation. However, creating a fly line for driving gene expression within a single neuron found in an EM connectome remains a challenge, as it typically requires identifying a pair of driver lines where only the neuron of interest is expressed in both. This task and other emerging scientific workflows require finding similar neurons across large data sets imaged using different modalities.ResultsHere, we present NeuronBridge, a web application for easily and rapidly finding putative morphological matches between large data sets of neurons imaged using different modalities. We describe the functionality and construction of the NeuronBridge service, including its user-friendly graphical user interface (GUI), extensible data model, serverless cloud architecture, and massively parallel image search engine.ConclusionsNeuronBridge fills a critical gap in the Drosophila research workflow and is used by hundreds of neuroscience researchers around the world. We offer our software code, open APIs, and processed data sets for integration and reuse, and provide the application as a service at http://neuronbridge.janelia.org.

GraphQL response data volume prediction based on Code2Vec and AutoML

PurposeGraphQL is a new Open API specification that allows clients to send queries and obtain data flexibly according to their needs. However, a high-complexity GraphQL query may lead to an excessive data volume of the query result, which causes problems such as resource overload of the API server. Therefore, this paper aims to address this issue by predicting the response data volume of a GraphQL query statement.Design/methodology/approachThis paper proposes a GraphQL response data volume prediction approach based on Code2Vec and AutoML. First, a GraphQL query statement is transformed into a path collection of an abstract syntax tree based on the idea of Code2Vec, and then the query is aggregated into a vector with the fixed length. Finally, the response result data volume is predicted by a fully connected neural network. To further improve the prediction accuracy, the prediction results of embedded features are combined with the field features and summary features of the query statement to predict the final response data volume by the AutoML model.FindingsExperiments on two public GraphQL API data sets, GitHub and Yelp, show that the accuracy of the proposed approach is 15.85% and 50.31% higher than existing GraphQL response volume prediction approaches based on machine learning techniques, respectively.Originality/valueThis paper proposes an approach that combines Code2Vec and AutoML for GraphQL query response data volume prediction with higher accuracy.

Smart Billing Software

The set of solutions offered by the Business Operation Support System revolves around Smart Billing Software. Because billing is the nerve centre of the company, it oversees all the important data, including product catalogues, customers, rates, taxes, financial accounting, invoices, payments, debit and credit notes, dual ledgers, support for multiple currencies, and more. You can manage any business operation involving metered charges, recurring charges, event-based charges, and ad-hoc charges with the help of Smart Billing Software's engine, which offers unparalleled flexibility in setting up any kind of product, product packages, user-defined rating structures, tax rules, and more. With Smart Billing Software, any service model and offering can be easily integrated into a single platform. It is compatible with both pre-paid and post-paid payment systems. Due to its open API foundation, Smart Billing Software is highly compatible with other BOSS products, allowing for the construction of comprehensive solutions. Smart Billing is a pre-integrated component of Xsinfosol Solutions and is one of the BOSS solutions offered by Xsinfosol.

THE URGENCY OF STANDARDIZING THE OPEN APPLICATION PROGRAMMING INTERFACE IN IMPLEMENTATION OF OPEN BANKING FOR CUSTOMER PROTECTION

Open banking with Open Application Programming Interface (open API) technology is an initiative aimed at streamlining the payment system in Indonesia. The open API allows banks to integrate their systems with digital financial service providers (fintech) and bold trade (e-commerce) providers by disclosing customer transaction data. This study investigates the urgency of open API standardization in implementing open banking in Indonesia. This study uses a normative juridical approach to secondary data. The data includes primary, secondary, and tertiary legal materials. In addition, it also uses qualitative normative data analysis methods. It was concluded that before the National Open API Payment Standard (SNAP) stipulation, the process of sharing data between banks and fintech and/or e-commerce still needed to be standardized but was only based on an agreement between the parties. Banking in Indonesia has various open API standards that can affect the protection of customer data. According to the Financial Services Authority Regulation Number 12/POJK.03/2018, the relationship between banks, fintech, and/or e-commerce in providing digital banking services based on agreements between parties needs to be stronger. OJK is indeed present as a supervisory agency. However, the parties will eventually come back to a deal between themselves. Unlike the Regulations of the Financial Services Authority, the Regulations of the Members of the Board of Governors, which form the legal basis for SNAP, provide standards that must be complied with by both service providers and service users. However, implementing SNAP-based open APIs still requires personal data protection regulations.

An agricultural digital twin for mandarins demonstrates the potential for individualized agriculture

A digital twin is a digital representation that closely resembles or replicates a real world object by combining interdisciplinary knowledge and advanced technologies. Digital twins have been applied to various fields, including to the agricultural field. Given big data and systematic data management, digital twins can be used for predicting future outcomes. In this study, we endeavor to create an agricultural digital twin using mandarins as a model crop. We employ an Open API to aggregate data from various sources across Jeju Island, covering an area of approximately 185,000 hectares. The collected data are visualized and analyzed at regional, inter-orchard, and intra-orchard scales. We observe that the intra-orchard analysis explains the variation of fruit quality substantially more than the inter-orchard analysis. Our data visualization and analysis, incorporating statistical models and machine learning algorithms, demonstrate the potential use of agricultural digital twins in the future, particularly in the context of micro-precision and individualized agriculture. This concept extends the current management practices based on data-driven decisions, and it offers a glimpse into the future of individualized agriculture by enabling customized treatment for plants, akin to personalized medicine for humans.

OPACA: Toward an Open, Language- and Platform-Independent API for Containerized Agents

OPACA: Toward an Open, Language- and Platform-Independent API for Containerized Agents

A Study on Influencing Factors on Users’ Intention to Accept Open Banking: Moderating Effect of Financial Literacy

Purpose - This study aims to explore the factors affecting users’ intentions regarding open banking. It extends the Unified theory of Acceptance and Use of Technology (UTAUT) by integrating perceived risk, initial trust, and financial literacy into the conceptual models. Since the government allowed open API access to the accounts of fintech firms and commercial banks, open banking has expanded rapidly in Korea from 2019. Understanding the factors influencing users’ intention to use this new system is important, given that open baking is still in the development stage.
 Design/methodology - Conceptual models were adopted from relevant literature and a string of hypotheses were developed. This study analyzed a data set of 439 Korean survey respondents and applied the initial trust model and the united theory of acceptance and use of technology(UTAUT) model.
 Findings - The results of the study show that performance expectancy, effort expectancy, and initial trust are the three major factors stimulating the use of open banking, whereas risks negatively affect its adoption. Financial literacy played a moderating role between these factors and the intention to use open banking. There was a difference in the impact of social influence on open banking users due to the degree of financial understanding. In addition, the moderating effect was verified according to the age group, the frequency of open banking use, and the number of accounts owned to check whether there are differences according to the characteristics of each group.
 Originality/value - This study is significant because it uses the level of financial knowledge as a moderating variable in users’ adoption of open banks, and is the first to investigate whether differences in users’ levels of financial knowledge affect their intention to use financial innovation.

Research on the Influencing Factors of Consumers' Purchase Intention of Commuter Pants Based on UGC Case Study of Little Red Book App

The Little Red Book App is a typical representative of User-Generated Content (UGC) platform in China, being well-known to the public for its unique sharing function. In this app, numerous users sharing content related to commuting clothing. However, there are very few research on the consumption intention of commuter pants consumers on the UGC platform. This study examines how UGC on the Little Red Book APP influences users' consumption willingness, using the 100 top commuter pants notes about popular commuter pants content as experimental subjects from the Little Red Book platform. Text analysis and network research are conducted based on data collected from Little Red Book open API Dandelion platform. information quality, visual experience and KOL influence significantly influence consumers' purchase intention. This study summarizes the common denominator of the most popular notes for relevant search terms from multiple perspectives and provides insights into how to utilize UGC and KOLs marketing to stimulate consumption desire and promote product sales. Based on the research results, corresponding feasible suggestions have been proposed for UGC e-commerce platforms, brands, and KOLs.

Fintech adoption, the regulatory environment and bank stability: An empirical investigation from GCC economies

The study analyzes the impact of fintech adoption on the banking sector's stability in GCC countries from 2010 to 2022. The study also considers the role of fintech regulations in this framework. We construct an index of fintech adoption by banks by considering several factors such as banks' digital presence, mobile banking capabilities, support for open APIs, fintech partnerships, digital payment solutions, automation and artificial intelligence integration, innovation initiatives, user experience focus and embracing new technologies. The regulatory environment is measured through the existence or introduction of fintech-related regulations such as the regulatory sandbox. The findings imply that fintech adoption has reduced banks' stability in GCC. The fintech-stability relationship varies over various bank-specific and country-specific variables. For instance, large and well-capitalized banks are less likely to experience adverse effects of fintech adoption. Moreover, the negative impact of fintech on financial stability is lower for Islamic, foreign and government banks. In addition, banks operating in well-developed and more competitive banking sectors experience lower financial instability when adopting fintech innovation. We confirm these findings with an alternative indicator of fintech adoption. The study also discusses essential policy implications for the sample countries.

Federated Secure Computing

Privacy-preserving computation (PPC) enables encrypted computation of private data. While advantageous in theory, the complex technology has steep barriers to entry in practice. Here, we derive design goals and principles for a middleware that encapsulates the demanding cryptography server side and provides a simple-to-use interface to client-side application developers. The resulting architecture, “Federated Secure Computing”, offloads computing-intensive tasks to the server and separates concerns of cryptography and business logic. It provides microservices through an Open API 3.0 definition and hosts multiple protocols through self-discovered plugins. It requires only minimal DevSecOps capabilities and is straightforward and secure. Finally, it is small enough to work in the internet of things (IoT) and in propaedeutic settings on consumer hardware. We provide benchmarks for calculations with a secure multiparty computation (SMPC) protocol, both for vertically and horizontally partitioned data. Runtimes are in the range of seconds on both dedicated workstations and IoT devices such as Raspberry Pi or smartphones. A reference implementation is available as free and open source software under the MIT license.

Investigating “organizational maturity” in order to provide “blockchain banking service” based on “FinTech” (through “the CMMI” in “Parsian Bank”)

PurposeThe description of “blockchain banking”, the determination of “the sub-processes” of “blockchain banking” as a “business process”, and the assessment of “maturity level” in Parsian Bank.Design/methodology/approachTheoretical sources on “blockchain banking” were initially investigated. Then the “sub-processes” of “blockchain banking” as a “business process” were extracted by Parsian Bank's experts through the “Delphi method”. Next, the “sequence” of the “sub-processes” was determined by means of the “AHP”. Eventually, Parsian Bank's maturity levels for all the sub-processes as well as the overall maturity level were specified on the basis of the “CMMI” V1.3 in order for Business Process Management (BPM).FindingsBlockchain banking’ combines traditional banking with cryptocurrencies, which can be provided by merging “hybrid e-wallet” with “bank account” and “bank card” – all together as “crypto bank account”. Plus, “hybrid e-wallet” is a form of mobile e-wallet on blockchain that supports both cryptocurrencies and traditional currencies in the same platform by which the purchase and sale of cryptocurrencies are possible. Besides, “Blockchain banking service” can also be offered within the framework of “open banking” aligned with “open innovation” through a FinTech (or a beta bank) in collaboration with a licensed bank via “open API”, which is called “blockchain banking based on FinTech”. At last, the eight sub-processes of “blockchain banking” were determined and Parsian Bank's “maturity level” was specified.Originality/valueThis is the very first practical guide to “blockchain banking service”.

Bridge Frost Prediction Using K-nearest Neighbor Classifier

Background: Considering the frequent occurrence of accidents on icy bridges during winter nights, it would be advantageous to notify both road managers and drivers regarding the most perilous areas. This notification would allow road managers to address the icy conditions by applying de-icing substances, while drivers could be more adequately prepared for potential hazards. Methods: In this study, the focus was on investigating k-nearest neighbor algorithms to predict nighttime icing caused by frost on three distinct bridges located on the National Highways in Korea. The algorithms utilized atmospheric data as input, which was obtained from the weather agency's website through an open API. The input data included relative humidity, air temperature, and dew point temperature, as well as the disparities in air temperature and humidity between two consecutive days. Results: In order to assess the effectiveness of the prediction models, reference data were created using the fundamental principle that ice is formed when the temperature of the pavement is below freezing and lower than the dew point temperature. Consequently, the developed algorithm demonstrated favorable performance, achieving an accuracy of 95% when evaluated using a test dataset that occupies 30% of the entire data. Conclusion: Considering the increasing focus on preventive maintenance, these newly developed forecasting models can be employed proactively as a preventive measure against icing. This proactive approach will ultimately contribute to improving traffic safety on winter roads.

Performance Comparison between Signature Cryptography: A Case Study on SNAP Indonesia

SNAP (Standar Nasional OPEN API Pembayaran) was submitted by several sub-working groups formed jointly by ASPI and the Bank of Indonesia for encouraging digital transformation in the banking industry. In the document Pedoman Tata Kelola (Bank of Indonesia, n.d.), there is the use cryptographic algorithms that are used as validation for third parties to use the Open API. The algorithms used in the document are HMAC and RSA. The third party will send the signature in the API header along with the sent API payload. The signature describes the body payload, the endpoint URL that was called by the third party, and the time when the API call was made, so the signature will change all the time. However, there are other algorithms that can be used as a form of validation, such as ECC and ZK-SNARK. In this journal, the performance of the four cryptographic algorithms is compared. The performance we compare is overall speed when creating the signature and verifying it. The result is that HMAC is the most efficient algorithm, but for financial data, it is better to use ECC which uses asymmetric keys and is faster than RSA contained in the SNAP document, especially when 256 bits security level that ECC could be 10 times faster then RSA.