ARTIFICIAL INTELLIGENCE SERVICE AGENTS IN FISCAL EXPANSION

PurposeThe study aims to examine the impact of an artificial intelligent service agent (AISA) on customer services to the rural population provided by KAYA, Kotak Life's AI-enabled insurance chatbot avatar that offers quality insurance services.Design/methodology/approachMulti-stage cluster sampling method was adopted to collect the responses from the 707 customers across the rural population of southern states of India. SPSS V.2 and Smart PLS 4 were used to apply simple percentage analysis, multiple linear regression analysis, and structural equation modeling (SEM) to validate the hypothesis. The dependent variables are economic performance and market performance based on the independent variables: efficiency, security, availability, enjoyment and contact.FindingsThe study revealed that efficiency and security are the highest predictors and the most influencing variables in predicting the economic and market performance of the insurance companies in determining the quality of service when rendered through AISA among the customers. Efficiency, security, availability, contact and enjoyment are the critical dimensions of AISA. It has a more significant impact on quality service (claim processing) to the rural population. It improves the economic and market performance among the insurance companies and the rural population.Originality/valueCustomers need convenience when making claims. Even little challenges might lead to stress and unhappiness, depending on the situation. Restrictions on where customers can file claims may not be the most outstanding service insurance firms can offer, given rising travel and commuting costs and widening geographical borders. Customers value proactive communication from service providers about the status of their insurance claims.

PurposeThe current work aims to analyze the complementary effects of relationship and service‐quality orientations on market and economic performance and their mediating role in the relationship between market orientation and performance.Design/methodology/approachIn order to test the hypotheses proposed, an empirical analysis for financial and insurance companies was conducted.FindingsThe study reveals that market performance relates highly to relationship orientation and service quality as two alternative but complementary strategies, whereas the effect on economic performance is basically indirect through the market performance.Practical implicationsResults suggest that applying relational policies such as preferential treatment, communication and adaptation to customers' needs is critical for customer retention, reducing complaints and conflicts or improving the positioning. Moreover, the firms need to focus on quality service, as a consequence of relationship orientation and another requisite for market performance and, subsequently, economic performance.Originality/valueThis work integrates market orientation philosophy with relationship marketing and service quality as related drivers of the firm's performance. Few empirical works had related these concepts until now in this way.

The purpose of conducting this research was to explore how the customers of the private sector banks perceive the various dimensions of service quality.This research was mainly based on primary data which had been collected through a well-structured questionnaire (adapted from the PZB model of service quality).The questionnaire had been distributed to 300 respondents.This paper makes a useful contribution as there are very low number of studies that have been conducted in India on such dimensions like tangibility, reliability, responsiveness assurance and empathy.This research showed that perception of service quality varies from person to person and, bank managers need to conduct more researches in order to evaluate perceived service quality more strongly.

The Market Performance of Diversified and Non-Diversified Organizations within the P-L Insurance Industry

The paper presents a methodology for assessing the quality of service (QoS) provision for a campus network. The author utilizes the Staffordshire University's network communications infrastructure (SUNCI) as a testing platform and discusses a new approach and QoS provision, by adding a component of measurement to the existing model presented by J.L. Walker (see J. Services Marketing, vol.9, no.1, p.5-14, 1995). The QoS provision is assessed in light of users' perception compared with the network traffic measurements and online monitoring reports. The users' perception of the QoS provision of a telecommunications network infrastructure is critical to the successful business management operation of any organization. The computing environment in modern campus networks is complex, employing multiple heterogeneous hardware and software technologies. In support of highly interactive user applications, QoS provision is essential to the users' ever increasing level of expectations. The paper offers a cost effective approach to assessing the QoS provision within a campus network.

The scope of development and research in the field of wireless mesh networks (WMN) is wide open and the focus has also been widened from simple channel assignment to multicast routing further moving towards providing quality of service (QoS) to the end users. The nodes in the network are of multi radio multi channel (MRMC) model. The efficiency of the network is termed as quality of service. For providing the QoS to the end users different techniques have been evolved which caters situations as QoS provisioning in the channel assignment phase, QoS provisioning in the multicast routing phase, and QoS provisioning in the channel assignment and multicast routing phase. This chapter presents a detailed study of QoS provisioning in WMN. It also classifies the techniques as: QoS provision in channel assignment, QoS provision in multicast routing and QoS provision in channel assignment as well as multicast routing.

PurposeWhile a vast number of studies have pointed out the keys of relationship marketing practices in consumer markets, little attention has been paid to the value the organization can get from such strategies. The literature provides relatively little support for the effectiveness of relationship marketing programs. The purpose of this research is to produce some evidence of the association between customer relationship marketing strategies and the market and economic performance of the firm.Design/methodology/approachThe proposed hypotheses are tested in the case of car repair and maintenance services, as a case where long‐term relationships are frequent. The hypotheses were evaluated using a path analysis, which associates relationship marketing activities with market performance (customers' perceptions, market position and loyalty) and market performance with economic performance.FindingsThe findings suggest that the effect of attraction and loyalty programs is greater on market performance than on economic performance. Furthermore, the results show that attracting customers through a good service quality and reaching a good position in the market have greater impact on economic results than loyalty.Practical implicationsAs a managerial implication, the authors suggest that service providers should put their efforts on improving quality rather than on promotion, advertising or economic bonus to customers.Originality/valueThis article realizes the importance of product and service quality rather than promotions, advertising or economic bonuses in retaining customer loyalty.

This paper deals with quality of service (QoS) provision in wireless IP networks. QoS provision is particularly challenging in wireless networks, where network resources are generally limited, variable over time and shared. In the design of possible measures to assure QoS one should consider that standardization is well established for the network layer Internet Protocol and for many underlying technologies of frequent use (e.g. IEEE 802.11, BLUETOOTH or HIPERLAN II). Therefore, as far as research on QoS is concerned, there is little room in both the IP and the link-layers for improved IP over wireless interfaces. In this paper we illustrate a solution in which an intermediate Wireless Adaptation Layer (WAL) is transparently interposed between the IP layer and specific link-layer technologies as a solution to provide QoS. The WAL addresses two main issues: (i) compensation for channel impairments in different platforms in order to enhance wireless channel reliability and (ii) implementation of traffic control and packet scheduling mechanisms to satisfy bandwidth and delay requirements, as well as to enforce a general principle of fairness among the IP associations contending for network resources and achieve optimal exploitation of transmission capacity. The WAL consists of a set of modules, each one in charge of a specific task, which can be enabled or disabled depending on the specific network environment. The novelty of the WAL approach is its capability of adapting itself to different wireless interfaces selecting performance enhancing modules for specific networks. This requires to modify the standard TCP/IP protocol stack by introducing an intermediate layer between the IP layer and the Data Link layer, with performance enhancement purposes. This paper focuses on two modules in particular, namely a traffic control module, which is in charge of performing congestion control and channel state dependent scheduling (CSD) packet scheduling, and a forward error correction (FEC) module, which compensates for channel impairments. This paper presents the proposed architecture provided with these modules and reports some measurements and simulations highlighting benefits resulting from the use of such modules.

This study had the following aims: (1) to describe the variable of service quality, brand image, loyalty and satisfaction of Prudential customers; (2) to analyze the influence of variable service quality and brand image on customer satisfaction; (3) to analyze the influence of variable service quality and brand image on customer loyalty; (4) analyze the influence of satisfaction on customer loyalty, and (5) to analyze the influence of service quality and brand image on customer loyalty through satisfaction strategy. There were 86 respondents that were used as a sample in this study. This research employed the structural equations (Structural Equation Modeling) as its analysis technique. The results showed that service quality and brand image had an influence on satisfaction, which meant that the provision of quality services and supported by companies that had good images could increase customer satisfaction. Furthermore, the service quality and brand image influenced Prudential Malang's consumer loyalty. This meant that customer loyalty could be developed through the provision of quality services since customers chose a company that had a good image/perception. Satisfaction affected loyalty. Customer satisfaction was subjective and it oriented towards individuals. Furthermore, it could relate to various aspects including the quality of services provided by the company. Customer satisfaction could be utilized to say positive things and reference for a company. Satisfaction mediated the influence of service quality and brand image on loyalty. This meant that customer loyalty could be developed if the customers were satisfied with the service quality provided by the company and also if the company had a good brand image.

The objective of this paper is to test empirically the performance of Indonesian capital market following the interest rate change. This study also tests the relationship between the interest rate changes and the subsequence performance in various industries, which are financial and manufacture sector. We used market level analysis as well as industry level analysis. We examine the 1996-2001 period. The sample consists of 64 interest rate change, 34 increase and 30 decrease. We used one market index and two industry index, which are Indonesian Capital Market Composite Index, Financial Sector Index and Manufacture Sector Index. In order to examine the market and industry performance following interest rate change, we test the mean-adjusted return (MAR) and cumulative mean-adjusted return (CMAR) during 21 event windows with t-test statistics. The results indicate that market and industrial performance react negatively to the increase of interest rate, while react positively to the decrease of interest rate. Besides, there is also an indication that financial sector performance tends to be more sensitive than manufacture sector performance. Keywords: Interest rate change, market performance, financial and manufacture performance, market-level analysis, industry-level analysis.

AIM: To analyze the impact of Technology-Driven Claims Automation, with a focus on real-time fraud detection and enhancing accuracy in claims intake and validation. This study explores how advanced technologies such as AI, machine learning, and automation streamline claims workflows, reduce processing time, and enhance decision-making accuracy while mitigating fraudulent activities in real-time. Study Design: A quasi-experimental design was employed to assess the effectiveness of Technology-Driven Claims Automation. The study analyzed pre- and post-implementation performance metrics, such as Claim Cycle Time, Claims Straight-Through Processing (STP) Rate, and Fraud Detection Rate. Place and Duration of Study: This study was conducted at Global Insurance Systems over a 16-week period from April to September 2024, involving all applications, tools and software used in Claims. Methodology: The methodology for enhancing claims processing leverages technology advancements in AI, automation, and predictive analytics to improve efficiency, accuracy, and fraud detection in Property & Casualty (P&C) insurance. It involves automated claims intake and processing, claims document verification, claims triaging and claim adjudication. Automated claims intake and processing eliminates manual data entry by using AI-powered chatbots, RPA, and cloud-based integrations, enabling policyholders to submit claims via self-service portals while AI validates and processes the information. Claims document verification applies OCR, NLP, and blockchain-based authentication to instantly extract, validate, and cross-check information from policyholder documents, invoices, and reports, improving accuracy and preventing fraud. Claims triaging utilizes OCR, machine learning, and computer vision to classify claims based on severity, risk, and potential fraud, ensuring legitimate claims are fast-tracked while suspicious cases are flagged for review. Multi-step workflow automation in claims adjudication integrates rule-based decision engines and predictive analytics to verify policy coverage, assess fraud risks, and automate approvals or payouts, reducing human intervention and processing time. Conclusion: The introduction of AI, automation, and predictive analytics in claims processing has significantly improved efficiency, fraud detection, and accuracy in the P&C insurance industry. In our study, it reduced Claim Cycle Time by 50%, increased Fraud Detection Accuracy by 25%, reduced operational costs by 40%, and increased Customer Satisfaction by 35%. By leveraging automated claims intake, triaging, adjudication workflows, and document verification, insurers can streamline operations, reduce manual intervention, and enhance customer experience. These advancements enable faster settlements, better risk assessment, and improved compliance with regulatory standards. As technology continues to evolve, embracing AI-driven solutions will be essential for insurers to stay competitive, minimize fraud, and deliver seamless, real-time claims processing.

Multi-tenant software-defined networks have emerged as a promising service platform to manage and share virtual network services between tenants and end-users. However, when using a service level agreement (SLA) in a multi-tenant circumstance, the resource competition among tenants incurred in many challenges on the quality of services (QoS) provisioning. First, as the existing QoS provisioning was to translate the high-level SLA contact into a group of corresponding low-level QoS rules, this traditional top-down translation mechanism was too ossified to support the dynamic SLA negotiation. Second, since an end-user usually requested multiple services and different services had different QoS requirements, the QoS provisioning required tenants to monitor and control the network status though OpenFlow protocol in a fine-grained way. To address these issues, we propose an SLA-aware fine-grained QoS provisioning (SFQP) scheme for MTSDN. The SFQP scheme extracts the eigen characteristics of each packet by application-aware technology automatically. Considering tenants are more willing to serve for users which have popular SLA contact to earn more revenues, we predict the SLA popularity by K-nearest neighbor. Moreover, we present an SLA-aware dynamic bandwidth allocation algorithm to implement the proposed SFQP scheme. The feasibility of the proposed scheme is verified by simulations of the SLA taxonomy, bandwidth utilization, and bandwidth fluctuation.

With the convergence of advanced technologies such as robotic process automation (RPA), artificial intelligence (AI), and data analytics, financial institutions and insurance companies are experiencing a paradigm shift in their operational models. The chapter explores how intelligent automation is revolutionizing traditional financial processes, including risk assessment, fraud detection, and compliance management. It analyzes the integration of automation tools in insurance underwriting, claims processing, and customer service, shedding light on the enhanced efficiency, accuracy, and customer satisfaction achieved through these innovations. Additionally, the chapter scrutinizes the challenges and ethical considerations associated with deploying intelligent automation in the financial sector, offering insights into best practices for achieving a harmonious synergy between technology and regulatory frameworks.

Handover management with Quality of Service (QoS) provision is the major challenge for the seamless mobility across heterogeneous wireless networks. In this paper, we propose the context-aware vertical handoff (VHO) management architecture with QoS provision, based on the extension of IEEE 802.21. In this proposed architecture, context information is collection from all layers of the protocol stack both mobile node side and network side as most as possible. Context-aware Adaptive Analytic Hierarchy Process Method (CAAHP) method is chosen to identify the most suitable network for the optimization of handover decision mechanism. For QoS provision, QoS Management Module is carefully designed to provide the various functionalities, especially, Dynamic QoS negotiation mechanism and Dynamic QoS Mapping mechanism to provide the QoS service continuity and adaptation. Finally, the Mobile-initiated Handover scheme integrating with our proposed architecture is detailedly illustrated through the messages and procedures.

This study examines the impact of company-specific and macro-economic factors on insurance companies' financial and market performance in Sri Lanka. The analysis was conducted using a panel regression. The sample consisted of nine listed insurance companies from 2010 to 2019, inclusive of both years. Capital structure, capital adequacy, liquidity position, and company size were considered as company-specific factors, whereas inflation and GDP growth were considered as market-specific factors. Net profit margin, return on assets, return on equity, and earnings per share were considered to measure the financial performance. In contrast, market value-added (MVA) was used to measure the market performance. Capital adequacy and capital structure have a significant negative association with financial performance, whereas the size is positively related to financial and market performance. The GDP growth rate is negatively associated with financial performance. Moreover, the liquidity position of the company is positively related to the MVA. The study provides evidence that the capital structure, capital adequacy, GDP growth rate, size of the company and liquidity position are essential factors that affect the insurance sector's financial and market performance in Sri Lanka. The study recommends that Sri Lankan insurance companies pay due attention to these factors to address financial and market performance matters. There is a dearth of studies in Sri Lanka on this phenomenon. We contribute as the direct study that analyzes the financial and market performance of the insurance sector in Sri Lanka in a single study. 
 Keywords: Company-specific factors, Financial performance, Market performance, Insurance sector, Macroeconomic factors, Sri Lanka.