Evaluating Contractors for Bonding: DEA Decision Making Model for Surety Underwriters

Abstract

In several countries, it is a common practice for construction owners to require contractors to submit several types of surety bonds shifting the risk of contractors default to sureties. The process of evaluating contractors’ applications for bonding is complicated and time-consuming. Surety underwriters are faced with the challenge of considering tens of objective and subjective criteria to make the bonding recommendation. These criteria include a contractor’s financial strength, past performance, and other related aspects. Literature review revealed that there is little guidance to surety underwriters in this regard. As a result, the purpose of this paper is to equip surety underwriters with a decision making model for evaluating contractors’ applications for bonding. The proposed model is based on data envelopment analysis (DEA). The DEA is a robust nonparametric linear programming approach that is widely used for benchmarking, performance measurement, and decision making. The proposed DEA model guides surety underwriters throughout the decision making process. The model offers surety underwriters the flexibility to accommodate any number of variables in the evaluation process. The proposed model is deployed based on a database that includes 49 contractors. The validity and applicability of the proposed model are scored positively by industry practitioners in terms of methodology used, evaluation criteria, ease of use, performance results, and overall usefulness compared to existing methods.