Loss prevention technologies' effect on property damage cost and financial savings

Investments in loss prevention technologies are made with the intention of preventing financial loss and reducing the cost of damage; however, uncertainty and lack of knowledge regarding what effect loss prevention technologies have challenges risk managers’ ability to efficiently prioritise investments.

Based on a new PhD study, this article conveys the main results of the question what quantitative effects do the most frequently used loss prevention technologies have on property damage cost? and explore what financial returns can be achieved through loss prevention investments when risk transfer is excluded.

Main results

First, the probability of a damage event is empirically estimated as a function of building characteristics, building types and the loss prevention technology in use. This analysis shows that damage probability tends to be higher when property loss prevention is used. It is noted that this is not a causal relationship as it was not possible to control for underlying factors like policyholder prioritisation of where to install the technology. Hence, it is expected that the higher probability of damage in buildings with loss prevention is a likely result of policyholders’ prioritisation of lowering risk in buildings where risk is highest.

Second, the difference in damage reduction for properties with and without loss prevention technologies is quantified by regressing damage cost per square metre on building characteristics, building types, and loss prevention technology in use. The analysis also shows that loss prevention technologies’ effect on damage reduction is dependent on the building type, and thus the usage of the building.

Crime loss prevention technologies are the only loss prevention technologies that show a significant influence on damage at the .99 confidence interval, and crime related damages are the most frequent damage expected to be influenced by the loss prevention technology in use. The only non-crime related loss prevention technology that shows significant influence on damage cost is building management systems combined with water leakage detection with stop valves for non-schools at the .9 confidence interval. The effect of using fire loss prevention technologies shows insignificant results as do the results for non-school buildings regarding crime loss prevention technologies.

Third, the quantified relationships are used to calculate potential financial savings from loss prevention technologies by using the regression coefficients to estimate the probabilities and damage costs for the properties without loss prevention technologies should they be adopted. For example, damage costs related to crime were found to be DKK 3.36 lower per square metre yearly if the building is a school and there is a burglar alarm combined with access control in use. This equates to financial savings for a mean size school of DKK 16,778.44 per year. This is one of the higher savings calculated, as one might expect, given that several of the technologies do not have demonstrable impacts on damage costs. 

Conclusion

While property loss prevention technologies reduce damage cost, the reductions are likely insufficient to finance investments or operation costs regarding these technologies. It should be noted that non-physical damages such as business interruption are not included in the calculation; thus, more positive results are likely to be found if these costs are included. Organisations should carefully consider why they are investing in loss prevention technologies as positive financial net benefits are likely unachievable.