Informal finance and rural finance policy in India: historical and contemporary perspectives

From the 1950s up to the early 1990s the All-India data show an ever-declining share of informal credit in the total outstanding debt of rural households. Contemporaneous micro-level studies, using more qualitative research methodologies, provide evidence that questions the strength of this trend, and more recent All-India credit surveys show, first, a levelling, and then a rise, in the share of rural informal credit in 1990/91 and 2000/01, respectively. By reference to findings of a study of village moneylenders in Rajasthan, the paper notes lessons to be drawn. First, informal financial agents have not disappeared from the rural financial landscape in India. Second, formal-sector financial institutions can learn much about rural financial service needs from the financial products and processes of their informal counterparts. Third, a national survey of informal agents, similar to that of the 1921 Census survey of indigenous bankers and moneylenders, would provide valuable pointers towards policy options for the sector. A recent Reserve Bank of India Report on Moneylender Legislation not only explores incentive mechanisms to better ensure fair practice, but also proposes provision for a new category of loan providers that would explicitly link the rural informal and formal financial sectors.

Risk pricing practices in finance, insurance and construction

A review of current risk pricing practices in the financial, insurance and construction sectors is conducted through a comprehensive literature review. The purpose was to inform a study on risk and price in the tendering processes of contractors: specifically, how contractors take account of risk when they are calculating their bids for construction work. The reference to mainstream literature was in view of construction management research as a field of application rather than a fundamental academic discipline. Analytical models are used for risk pricing in the financial sector. Certain mathematical laws and principles of insurance are used to price risk in the insurance sector. construction contractors and practitioners are described to traditionally price allowances for project risk using mechanisms such as intuition and experience. Project risk analysis models have proliferated in recent years. However, they are rarely used because of problems practitioners face when confronted with them. A discussion of practices across the three sectors shows that the construction industry does not approach risk according to the sophisticated mechanisms of the two other sectors. This is not a poor situation in itself. However, knowledge transfer from finance and insurance can help construction practitioners. But also, formal risk models for contractors should be informed by the commercial exigencies and unique characteristics of the construction sector.

Entropy application to improve construction finance decisions

In financial decision-making processes, the adopted weights of the objective functions have significant impacts on the final decision outcome. However, conventional rating and weighting methods exhibit difficulty in deriving appropriate weights for complex decision-making problems with imprecise information. Entropy is a quantitative measure of uncertainty and has been useful in exploring weights of attributes in decision making. A fuzzy and entropy-based mathematical approach is employed to solve the weighting problem of the objective functions in an overall cash-flow model. The multiproject being undertaken by a medium-size construction firm in Hong Kong was used as a real case study to demonstrate the application of entropy. Its application in multiproject cash flow situations is demonstrated. The results indicate that the overall before-tax profit was HK$ 0.11 millions lower after the introduction of appropriate weights. In addition, the best time to invest in new projects arising from positive cash flow was identified to be two working months earlier than the nonweight system.