In light of the recent exodus of foreign insurers from Taiwan and the local insurers' outcries against the International Financial Reporting Standard (IFRS) 4 Insurance Contracts, we examine the value relevance of financial statements for life insurance firms, with particular interests to the embedded value (EV) disclosure. We find that the EV of equity has an incremental information role for book value of equity, which indicates that the accounting mismatching problem in the insurance industry creates a demand for fair value accounting. The fair value of liabilities under IFRS 4 Phase 2 has been disputed globally by accountants, actuaries, academia and regulators. The EV model is a concept approaching the fair value model. The research findings provide important empirical evidences supporting the fair value concept of IFRS 4.

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Investigates the possibility of applying artificial intelligence to solve practical auditing problems faced by the public sector, namely the tax auditor of the Internal Revenue Services, when targeting firms for further investigation. Suggests that organizations which incorporate an operational artificial neural network system will raise their performance greatly. Proposes that the neural network will overcome problems faced by a direct knowledge acquisition method in building an expert system to preserve the expertise of senior auditors by the IRS in Taiwan. Provides an explanation of the neural network theory with regard to multi‐ and single‐layered neural networks. Statistics reveal the neural network performs favourably, and that three‐layer networks perform better than two‐layer neural networks. The results strongly suggest that neural networks can be used to identify firms requiring further auditing investigation, and also suggest future implications for intelligent auditing machines.

In this paper, we employ a unique dataset from Taiwan to investigate the order type choices made by individual and institutional investors over periods of high market uncertainty. Our studies show that individuals change their behavior during periods of high market uncertainty by submitting more market orders and sell orders. In contrast, institutions are less influenced by market uncertainty. Institutional trades can alleviate, but not reverse, this increase in individuals' market orders during periods of high market uncertainty. These findings suggest that the composition of investor clientele plays an important role in understanding asset returns and volatility in emerging markets.