Strategy & Insurance | Cognitive bias lead to over estimating short term risks and underestimating long term risks
Those who we love the #insurance #industry with its pros and cons, I believe we have lived through those kind of situations for quite some time:
?? Senior #Management who needs to take an #investment decision about what kind of #technology might be the right one to mitigate a described pain the organization is suffering, acts with #bias due to prior experience.
?? If a #CLevel Executive has had prior experiences that shape his/her #beliefs and #opinions, they may be biased in their #decision-making, particularly in situations where their prior experiences are similar to the current situation. (in the positive or negative way)
For example, if a person has had prior experience with a particular type of technology or business model and it did not work out well, they may be biased against similar technologies or business models in the future, even if there is evidence to suggest that they could be successful.
This prior experience usually impacts the individual's judgment and decision-making, leading to a mismanagement of risks – even over estimating short term risks and underestimating long term risks.
Over estimating short term risks and underestimating long term risks
Over-estimating short-term #risks and underestimating long-term risks is a common issue in risk management. This phenomenon is often referred to as "risk #myopia." It is caused by several factors, including a focus on immediate, visible risks, and a tendency to prioritize short-term goals and objectives over long-term planning. This can result in the allocation of resources and attention towards mitigating short-term risks, while ignoring or downplaying the potential consequences of long-term risks. This can lead to a false sense of #security and can have serious consequences, as long-term risks may have a much greater impact than initially estimated. It is important for organizations to adopt a holistic approach to risk management that takes into account both short-term and long-term risks and incorporates strategies to manage both.
What is an example of bias error?
An example of a bias error is the Confirmation Bias. Confirmation bias is a type of cognitive bias that involves interpreting new information in a way that confirms one's existing beliefs and opinions, while ignoring or downplaying information that contradicts those beliefs. For example, a person may have a belief that a certain investment is low risk, and they may only seek out information that supports this belief, while ignoring or dismissing information that suggests otherwise. As a result, the person may make a decision that is not based on a comprehensive understanding of the risks involved, leading to a mismanagement of risks and potential negative consequences. Confirmation bias is just one example of a bias error that can impact decision-making in risk management.
Impact of human bias on risk management
Human bias can significantly impact risk management, leading to decisions that are based on subjective opinions and incorrect assumptions rather than objective data and analysis. To mitigate the impact of human bias in risk management, organizations can adopt the following strategies:
1.??????#Diversify decision-making teams: Including individuals from diverse backgrounds and with different perspectives can help to reduce the impact of bias in decision-making.
2.??????Use #data and #analytics: Objective data and analysis can help to reduce the impact of bias by providing a basis for informed decision-making.
3.??????Implement structured decision-making #processes: Establishing a clear, structured process for risk management can help to ensure that decisions are based on objective criteria and data, rather than subjective opinions.
4.??????Provide #training and #education: Providing training and education to risk management teams can help to raise awareness of the impact of bias and provide tools and techniques to mitigate it.
5.??????Regularly review and assess processes: Regularly reviewing and assessing risk management processes can help to identify areas where bias may be impacting decision-making and provide opportunities to implement corrective measures.
By implementing these strategies, organizations can reduce the impact of human bias in risk management and improve the accuracy and effectiveness of their risk management processes.
Examples of mismanagement of risks due to human bias
Examples of mismanagement of risks due to human bias include:
1.??????#Confirmation bias: Ignoring or downplaying information that contradicts existing beliefs and only considering information that supports those beliefs.
2.??????#Overconfidence bias: Underestimating risks and overestimating abilities, leading to a false sense of security and poor risk management decisions.
3.??????#Anchoring bias: Underestimating risks because they have not been experienced or observed in the past.
4.??????#Availability bias: Underestimating risks because they are not readily available or easily remembered.
5.??????#Groupthink: Conforming to the opinions and decisions of a group, even if they are incorrect, due to a desire for social harmony.
6.??????#Herding behavior: Following the decisions of others, even if they are not based on objective analysis, due to a desire to avoid personal responsibility.
7.??????#Hindsight bias: Believing that events were predictable after they have happened, leading to poor risk management decisions in the future.
These are just a few examples of how human bias can impact risk management. To mitigate the impact of these biases, organizations must be aware of their potential influence and implement strategies to reduce their impact.
Impact of technology in business models insurance carriers
Technology has had a significant impact on business models for insurance carriers. Some of the key ways technology has influenced insurance include:
?? #Digitization of the customer experience
Technology has made it possible for insurance companies to offer customers more convenient and user-friendly experiences, such as online quotes and policy management.
???Increased data analytics
Technology has made it possible for insurance carriers to collect and analyze vast amounts of data to better understand customer needs, identify risks, and develop more accurate pricing models.
???Telematics and #IoT devices
The rise of connected devices and telematics has enabled insurance carriers to gather real-time data about customers, leading to more accurate risk assessments and pricing.
?? #Automated underwriting and #claims processing
Technology has enabled insurance companies to automate many manual processes, such as underwriting and claims processing, leading to more efficiency and lower costs.
Technology has enabled insurance carriers to reach customers directly, bypassing traditional intermediaries, and allowing for new, more cost-effective business models.
Technology has enabled insurance carriers to be more #agile, #efficient, and #customer-focused, leading to new opportunities for #growth and increased #competitiveness in the market.
Being aware about #cognitive bias can lead to better decisions on what kind of technology to use in response to challenges the organization might face.
If you want to continue debating on this or any other issue related to the insurance market, please meet me at the #InsurtechInsights Europe #Conference in London on March 01st and 2nd, where I plan to speak.
?? https://www.insurtechinsights.com/europe/speakers/