“Knowledge is power”. It is a famous quote by Francis Bacon that states knowledge allows us to anticipate undesirable events and find ways to mitigate them. Although this phrase is more than 400 years old, business experts have yet to put it into practice.
Firms obtain business (commercial) insurance policies to protect themselves from financial loss or hazards. Insurance companies, on the other hand, prefer to charge high premiums rather than provide loss prevention consultancy to their customers. Thus, there are more claims, greater premiums, and more risk for both parties. This article introduces scientific loss prevention and its best practices to help insurers operate a less risky business and contribute to society’s well-being.
What is scientific loss prevention?
Scientific loss prevention is a risk management strategy for insurance firms that aims to reduce claims and insurance company obligations as much as possible. To do so, insurers evaluate the risk aspects of the companies they financially protect and work with the insured to limit potential damages.
What are the 6 principles of scientific loss prevention?
Scientific loss prevention is built on following main principles:
- Determining of risk elements: Insurance companies should cooperate with risk engineers that specialize in risk management for certain industries. Risk engineers gather data on the risk elements that may influence insureds and examine the safeguards taken to reduce loss through on-site or remote assessment. Risk engineers present their results to the insurance company at the conclusion of the investigation.
- Determining possible scenarios: Risk refers to ambiguity. Thus, coming up with a single scenario can be misleading. A large earthquake, for example, that ruins factory buildings could result in a fire if the natural gas pipeline is also damaged. However, this may also not be the case. To protect against insolvency, insurers should analyze all probable circumstances. The three main scenarios insurers should consider are maximum possible loss, maximum probable loss, and normal loss expectancy.
- Calculating risk score: Risk scoring has been performed manually for a long time which is error prone. Since different experts evaluate different sites it was not standardized. Advanced analytics on the other hand use standard calculations. For a case of factory fire risks advanced analytics can use information such as:
- Flammable material stored per square matter
- Frequency of transportation of such materials
- Humidity of factory
- existence of firewalls
and predict future incidents. Thus, risk of factory fire is scored by AI algorithms in a standardized and data driven way (See Figure 1 for a fire risk scoring example of a factory).
- Consulting insured for reducing risk elements: After the risk score is calculated, insurance companies should inform their customers about the details of it and suggest short and long term plans for mitigating risks.
- Monitoring insured performance: Insurance companies periodically monitor the performance of reinsured to understand whether or not the client mitigates its risk.
Reevaluating insured premium considering its success: When an insured makes a step ahead in terms of loss prevention, the likelihood of a claim decreases. As a result, insurance premiums should be adjusted correspondingly. It is also vital for customer retention, because business insurance consumers prioritize getting the best price the most.
Figure 1: Fire risk scoring example
Virtual i Technologies help insurers to provide better scientific loss prevention thanks to their cloud-based platform [VRS]™ Virtual Risk Space. Platform assists insurers with advanced analytics to measure risk scores of their clients. Traditional risk engineering services are also transformed into tech-based processes by Virtual i Technologies. For example, using the remote risk engineering capabilities of [VRS]™ Virtual Risk Space, Virtual I Technologies assisted a broker in examining 13 textile plants in remote locations within 3 months.
Virtual i Technologies help insurers to provide better scientific loss prevention thanks to their cloud-based platform [VRS]™ Virtual Risk Space. Platform assists insurers with advanced analytics to measure risk scores of their clients. Traditional risk engineering services are also transformed into tech-based processes by Virtual i Technologies. For example, using the remote risk engineering capabilities of [VRS]™ Virtual Risk Space, Virtual I Technologies assisted a broker in examining 13 textile plants in remote locations within 3 months.
Why is scientific loss prevention important now?
By establishing strategies and precautions against hazardous situations, scientific loss prevention benefits both insurers and insureds. It safeguards capital rather than its monetary value, promotes resource efficiency, and improves society’s long-term well-being:
- Reduces risk of bankruptcy of insurance firms: Providing effective risk management for the customers implies less claims for the insurance companies. Thus, insurance companies minimize their liabilities and reduce the probability of bankruptcy.
- Reduces business insurance premium: The best way of reducing insurance premium is showing that you are a responsible customer. For instance, your clean driving records results in a lower auto insurance premium. Similarly, a business that takes precautions against possible risk scenarios will be rewarded by the insurance companies.
- Protects goodwill of the insured: An insurance policy protects the insured from the financial consequences of an unfavorable incident. Corporate reputation, on the other hand, cannot be insured. When a tragic event occurs at your organization (for example, a data breach), it erodes the trust of your stakeholders and customers (even if your firm has cybersecurity insurance policy)
- Promotes sustainability: Executives hear terms like environmental, social, and governance (ESG) reports, circular economy, and corporate carbon footprint frequently recently. There is a reason behind this. We consumed natural resources equal to 1.7 Earth’s annual production. After a commercial building fire, taking financial recourse through an insurance policy might help to mitigate short-term financial concerns. Renovation of the plant, on the other hand, has a negative impact on your ESG score and, as a result, your business.
5 best practices of scientific loss prevention for insurers
- Ensure the consistency of risk scoring: To make loss prevention scientific, the same data should yield the same findings. As a result, employing algorithms and standardized data collection are required to perform it.
- Provide holistic reports: As we mentioned in our Top 6 Risk Management Best Practices article, firms cope with lots of risk elements today such as:
- Traditional risk elements ( work accidents, fires, natural disasters, economic cycle related risks etc.)
- Cyber risks.
- Climate related risks.
- Covid related risks.
- Supply chain disruption related risks.
An effective scientific loss prevention service provides assessments and consultancy services for each of them.
- Collaborate with insurtechs: Remote risk assessment tools and risk scoring algorithms deliver scientific loss prevention services a competitive advantage. Not every insurer or insurance company, however, is a technology company. As a result, using insurance as a service mentality cloud-based platforms of insurtech firms is beneficial to them. Insurers can take advantage of AI capabilities by paying insurtechs a subscription fee.
- Widen your risk engineers network: We live in a global world where businesses have multiple facilities, some of which are located in different parts of the globe. Therefore, insurers need connections from many locations who can execute risk engineering in order to provide risk scoring and loss prevention services.
- Guide clients effectively: Insurers can provide value by staying in touch with clients throughout the year rather than just at procedural times like the first registration, periodic invoicing, or when losses are reported. Guiding insureds with:
- Risk management e-newsletters.
- Messages offering safety recommendations.
- Messages notifying with risks such as (storm alerts).
- Sharing case studies of effective loss-prevention activities.
can help policyholders and does not cost much for the insurers.
The article was originally published in the AI Multiple website and written by Görkem Gençer on April 14,2022.
