Pricing insurance for risks associated with information technology systems presents a complex modelling challenge, combining the disciplines of operations management, security, and economics. This work proposes a socioeconomic modelling framework for cyber-insurance decisions compromised of entity relationship diagrams, security maturity models, and economic models, addressing a long-standing research challenge of capturing organizational structure in the design and pricing of cyber-insurance policies. Insurance pricing is usually informed by the long experience insurance companies have of the magnitude and frequency of losses that arise in organizations based on their size, industry sector, and location. Consequently, their calculations of premia will start from a baseline determined by these considerations. A unique challenge of cyber-insurance is that data history is limited and not necessarily informative of future loss risk meaning that established actuarial methodology for other lines of insurance may not be the optimal pricing strategy. The modelling framework proposed in this paper provides a vehicle for agreement between practitioners in the cyber-insurance ecosystem on cyber-security risks and allows for the users to choose their desired level of abstraction in the description of a system.