Insights

New Exposure Management Tools Needed for Emerging Risk

Key results

Reduced exposure analysis time from days to hours.

Enabled real-time, comprehensive exposure insights and reporting.

Enhanced analysis of complex Terrorism data for profitability.

New Exposure Management Tools Needed for Emerging Risk

When it comes to exposure management in the Property & Casualty (P&C) classes of risks, the (re)insurance industry has focused mostly on natural perils. Natural catastrophic models predict an estimated loss associated with a hurricane or an earthquake in a specific geographical zone.

Those tools are essential because natural perils are prevalent. However, we argue that the risk drivers are getting more and more multidimensional and interconnected. As a result, the core nature of the risks is changing and will continue to change, and exposure management models need to grow too.

New emerging risks

In a world of hyper-connectivity, the (re)insurance industry faces new emerging risks. As documented in its Risk Barometer 2020 report, Allianz ranked cybersecurity and business interruption risks as the two most important business risks for the last four consecutive years (Note 1), relegating natural catastrophes to the third and fourth places over the same period.

Risk drivers such as supply chain disruptions, cyber-attacks, pandemic risks, or political violence are interconnected, having the potential to affect a wide range of business lines.

For example, in the energy sector, there are dependencies between offshore energy installations, such as pipelines and bridges. This presents significant property damage and supply-chain disruptions risk leading to potential risks of a business interruption. A cyberattack or an earthquake affecting an unmanned oil production platform could trigger such an event.

In the Aviation industry, the COVD-19 pandemic has affected the entire supply chain. The grounding of over 70% of the aircraft's fleets has created significant aggregate exposure in specific airports.  

Generally, supply chain and industry practices tend towards more centralisation, hubs, and clusters. Industrial and logistical centres are few but more significant at individual levels, exacerbating the dependencies between risks at the global level.

We believe emerging risks and their connected aspects, in particular, require the industry to rethink exposure management, and design alternative models based on relevant sources of data and fit-for-purpose technologies.

Current tools are not appropriate for undercovering emerging risks

Outside the natural catastrophes models, which have consumed a lot of resources, current model approaches are not appropriate to help underwriters quantify and qualify new emerging risks.

For example, although widely used in P&C (re)insurance, Microsoft Excel is not designed to perform complex exposure calculations or to apply machine learning methodologies, as well as having limited collaborative features.

Using inappropriate tools and data not only undermines the productivity of the underwriting process but also amplifies the uncertainty of the output and erodes the quality of the decision-making.

A better way forward

At Allphins we advocate for a live risk exposure management approach, focusing on interconnected risk, covering both man-made and non-man-made events.

We base models on the following building blocks:

  1. Fit-for-purpose technologies: To foster digital transformation and empower underwriters to transform internal and external unstructured data into insights.
  2. Risk-relevant data: To recognise risks and enhance the information provided by brokers and clients.
  3. Deep sector expertise: To define the realm of potential events.
  4. A cross-class and cross-functional approach connected to other systems

It requires drifting away from relying exclusively on the underwriter's intuition and moving towards blending underwriters' judgment with data and technology. Making such an approach a priority requires organisations to collaborate further, and integrate the output of different teams, including underwriters, risk engineers, exposure managers, and claims managers.

The road is long, but the benefits are real, enabling (re)insurers to identify value and make better risk decisions, improve capital allocation and portfolio segmentation, opening the industry for new growth opportunities.

Antonin & the Allphins team

New Exposure Management Tools Needed for Emerging Risk

When it comes to exposure management in the Property & Casualty (P&C) classes of risks, the (re)insurance industry has focused mostly on natural perils. Natural catastrophic models predict an estimated loss associated with a hurricane or an earthquake in a specific geographical zone.

Those tools are essential because natural perils are prevalent. However, we argue that the risk drivers are getting more and more multidimensional and interconnected. As a result, the core nature of the risks is changing and will continue to change, and exposure management models need to grow too.

New emerging risks

In a world of hyper-connectivity, the (re)insurance industry faces new emerging risks. As documented in its Risk Barometer 2020 report, Allianz ranked cybersecurity and business interruption risks as the two most important business risks for the last four consecutive years (Note 1), relegating natural catastrophes to the third and fourth places over the same period.

Risk drivers such as supply chain disruptions, cyber-attacks, pandemic risks, or political violence are interconnected, having the potential to affect a wide range of business lines.

For example, in the energy sector, there are dependencies between offshore energy installations, such as pipelines and bridges. This presents significant property damage and supply-chain disruptions risk leading to potential risks of a business interruption. A cyberattack or an earthquake affecting an unmanned oil production platform could trigger such an event.

In the Aviation industry, the COVD-19 pandemic has affected the entire supply chain. The grounding of over 70% of the aircraft's fleets has created significant aggregate exposure in specific airports.  

Generally, supply chain and industry practices tend towards more centralisation, hubs, and clusters. Industrial and logistical centres are few but more significant at individual levels, exacerbating the dependencies between risks at the global level.

We believe emerging risks and their connected aspects, in particular, require the industry to rethink exposure management, and design alternative models based on relevant sources of data and fit-for-purpose technologies.

Current tools are not appropriate for undercovering emerging risks

Outside the natural catastrophes models, which have consumed a lot of resources, current model approaches are not appropriate to help underwriters quantify and qualify new emerging risks.

For example, although widely used in P&C (re)insurance, Microsoft Excel is not designed to perform complex exposure calculations or to apply machine learning methodologies, as well as having limited collaborative features.

Using inappropriate tools and data not only undermines the productivity of the underwriting process but also amplifies the uncertainty of the output and erodes the quality of the decision-making.

A better way forward

At Allphins we advocate for a live risk exposure management approach, focusing on interconnected risk, covering both man-made and non-man-made events.

We base models on the following building blocks:

  1. Fit-for-purpose technologies: To foster digital transformation and empower underwriters to transform internal and external unstructured data into insights.
  2. Risk-relevant data: To recognise risks and enhance the information provided by brokers and clients.
  3. Deep sector expertise: To define the realm of potential events.
  4. A cross-class and cross-functional approach connected to other systems

It requires drifting away from relying exclusively on the underwriter's intuition and moving towards blending underwriters' judgment with data and technology. Making such an approach a priority requires organisations to collaborate further, and integrate the output of different teams, including underwriters, risk engineers, exposure managers, and claims managers.

The road is long, but the benefits are real, enabling (re)insurers to identify value and make better risk decisions, improve capital allocation and portfolio segmentation, opening the industry for new growth opportunities.

Antonin & the Allphins team

New Exposure Management Tools Needed for Emerging Risk

When it comes to exposure management in the Property & Casualty (P&C) classes of risks, the (re)insurance industry has focused mostly on natural perils. Natural catastrophic models predict an estimated loss associated with a hurricane or an earthquake in a specific geographical zone.

Those tools are essential because natural perils are prevalent. However, we argue that the risk drivers are getting more and more multidimensional and interconnected. As a result, the core nature of the risks is changing and will continue to change, and exposure management models need to grow too.

New emerging risks

In a world of hyper-connectivity, the (re)insurance industry faces new emerging risks. As documented in its Risk Barometer 2020 report, Allianz ranked cybersecurity and business interruption risks as the two most important business risks for the last four consecutive years (Note 1), relegating natural catastrophes to the third and fourth places over the same period.

Risk drivers such as supply chain disruptions, cyber-attacks, pandemic risks, or political violence are interconnected, having the potential to affect a wide range of business lines.

For example, in the energy sector, there are dependencies between offshore energy installations, such as pipelines and bridges. This presents significant property damage and supply-chain disruptions risk leading to potential risks of a business interruption. A cyberattack or an earthquake affecting an unmanned oil production platform could trigger such an event.

In the Aviation industry, the COVD-19 pandemic has affected the entire supply chain. The grounding of over 70% of the aircraft's fleets has created significant aggregate exposure in specific airports.  

Generally, supply chain and industry practices tend towards more centralisation, hubs, and clusters. Industrial and logistical centres are few but more significant at individual levels, exacerbating the dependencies between risks at the global level.

We believe emerging risks and their connected aspects, in particular, require the industry to rethink exposure management, and design alternative models based on relevant sources of data and fit-for-purpose technologies.

Current tools are not appropriate for undercovering emerging risks

Outside the natural catastrophes models, which have consumed a lot of resources, current model approaches are not appropriate to help underwriters quantify and qualify new emerging risks.

For example, although widely used in P&C (re)insurance, Microsoft Excel is not designed to perform complex exposure calculations or to apply machine learning methodologies, as well as having limited collaborative features.

Using inappropriate tools and data not only undermines the productivity of the underwriting process but also amplifies the uncertainty of the output and erodes the quality of the decision-making.

A better way forward

At Allphins we advocate for a live risk exposure management approach, focusing on interconnected risk, covering both man-made and non-man-made events.

We base models on the following building blocks:

  1. Fit-for-purpose technologies: To foster digital transformation and empower underwriters to transform internal and external unstructured data into insights.
  2. Risk-relevant data: To recognise risks and enhance the information provided by brokers and clients.
  3. Deep sector expertise: To define the realm of potential events.
  4. A cross-class and cross-functional approach connected to other systems

It requires drifting away from relying exclusively on the underwriter's intuition and moving towards blending underwriters' judgment with data and technology. Making such an approach a priority requires organisations to collaborate further, and integrate the output of different teams, including underwriters, risk engineers, exposure managers, and claims managers.

The road is long, but the benefits are real, enabling (re)insurers to identify value and make better risk decisions, improve capital allocation and portfolio segmentation, opening the industry for new growth opportunities.

Antonin & the Allphins team

Share via:
Insights

New Exposure Management Tools Needed for Emerging Risk

New Exposure Management Tools Needed for Emerging Risk

When it comes to exposure management in the Property & Casualty (P&C) classes of risks, the (re)insurance industry has focused mostly on natural perils. Natural catastrophic models predict an estimated loss associated with a hurricane or an earthquake in a specific geographical zone.

Those tools are essential because natural perils are prevalent. However, we argue that the risk drivers are getting more and more multidimensional and interconnected. As a result, the core nature of the risks is changing and will continue to change, and exposure management models need to grow too.

New emerging risks

In a world of hyper-connectivity, the (re)insurance industry faces new emerging risks. As documented in its Risk Barometer 2020 report, Allianz ranked cybersecurity and business interruption risks as the two most important business risks for the last four consecutive years (Note 1), relegating natural catastrophes to the third and fourth places over the same period.

Risk drivers such as supply chain disruptions, cyber-attacks, pandemic risks, or political violence are interconnected, having the potential to affect a wide range of business lines.

For example, in the energy sector, there are dependencies between offshore energy installations, such as pipelines and bridges. This presents significant property damage and supply-chain disruptions risk leading to potential risks of a business interruption. A cyberattack or an earthquake affecting an unmanned oil production platform could trigger such an event.

In the Aviation industry, the COVD-19 pandemic has affected the entire supply chain. The grounding of over 70% of the aircraft's fleets has created significant aggregate exposure in specific airports.  

Generally, supply chain and industry practices tend towards more centralisation, hubs, and clusters. Industrial and logistical centres are few but more significant at individual levels, exacerbating the dependencies between risks at the global level.

We believe emerging risks and their connected aspects, in particular, require the industry to rethink exposure management, and design alternative models based on relevant sources of data and fit-for-purpose technologies.

Current tools are not appropriate for undercovering emerging risks

Outside the natural catastrophes models, which have consumed a lot of resources, current model approaches are not appropriate to help underwriters quantify and qualify new emerging risks.

For example, although widely used in P&C (re)insurance, Microsoft Excel is not designed to perform complex exposure calculations or to apply machine learning methodologies, as well as having limited collaborative features.

Using inappropriate tools and data not only undermines the productivity of the underwriting process but also amplifies the uncertainty of the output and erodes the quality of the decision-making.

A better way forward

At Allphins we advocate for a live risk exposure management approach, focusing on interconnected risk, covering both man-made and non-man-made events.

We base models on the following building blocks:

  1. Fit-for-purpose technologies: To foster digital transformation and empower underwriters to transform internal and external unstructured data into insights.
  2. Risk-relevant data: To recognise risks and enhance the information provided by brokers and clients.
  3. Deep sector expertise: To define the realm of potential events.
  4. A cross-class and cross-functional approach connected to other systems

It requires drifting away from relying exclusively on the underwriter's intuition and moving towards blending underwriters' judgment with data and technology. Making such an approach a priority requires organisations to collaborate further, and integrate the output of different teams, including underwriters, risk engineers, exposure managers, and claims managers.

The road is long, but the benefits are real, enabling (re)insurers to identify value and make better risk decisions, improve capital allocation and portfolio segmentation, opening the industry for new growth opportunities.

Antonin & the Allphins team

New Exposure Management Tools Needed for Emerging Risk

When it comes to exposure management in the Property & Casualty (P&C) classes of risks, the (re)insurance industry has focused mostly on natural perils. Natural catastrophic models predict an estimated loss associated with a hurricane or an earthquake in a specific geographical zone.

Those tools are essential because natural perils are prevalent. However, we argue that the risk drivers are getting more and more multidimensional and interconnected. As a result, the core nature of the risks is changing and will continue to change, and exposure management models need to grow too.

New emerging risks

In a world of hyper-connectivity, the (re)insurance industry faces new emerging risks. As documented in its Risk Barometer 2020 report, Allianz ranked cybersecurity and business interruption risks as the two most important business risks for the last four consecutive years (Note 1), relegating natural catastrophes to the third and fourth places over the same period.

Risk drivers such as supply chain disruptions, cyber-attacks, pandemic risks, or political violence are interconnected, having the potential to affect a wide range of business lines.

For example, in the energy sector, there are dependencies between offshore energy installations, such as pipelines and bridges. This presents significant property damage and supply-chain disruptions risk leading to potential risks of a business interruption. A cyberattack or an earthquake affecting an unmanned oil production platform could trigger such an event.

In the Aviation industry, the COVD-19 pandemic has affected the entire supply chain. The grounding of over 70% of the aircraft's fleets has created significant aggregate exposure in specific airports.  

Generally, supply chain and industry practices tend towards more centralisation, hubs, and clusters. Industrial and logistical centres are few but more significant at individual levels, exacerbating the dependencies between risks at the global level.

We believe emerging risks and their connected aspects, in particular, require the industry to rethink exposure management, and design alternative models based on relevant sources of data and fit-for-purpose technologies.

Current tools are not appropriate for undercovering emerging risks

Outside the natural catastrophes models, which have consumed a lot of resources, current model approaches are not appropriate to help underwriters quantify and qualify new emerging risks.

For example, although widely used in P&C (re)insurance, Microsoft Excel is not designed to perform complex exposure calculations or to apply machine learning methodologies, as well as having limited collaborative features.

Using inappropriate tools and data not only undermines the productivity of the underwriting process but also amplifies the uncertainty of the output and erodes the quality of the decision-making.

A better way forward

At Allphins we advocate for a live risk exposure management approach, focusing on interconnected risk, covering both man-made and non-man-made events.

We base models on the following building blocks:

  1. Fit-for-purpose technologies: To foster digital transformation and empower underwriters to transform internal and external unstructured data into insights.
  2. Risk-relevant data: To recognise risks and enhance the information provided by brokers and clients.
  3. Deep sector expertise: To define the realm of potential events.
  4. A cross-class and cross-functional approach connected to other systems

It requires drifting away from relying exclusively on the underwriter's intuition and moving towards blending underwriters' judgment with data and technology. Making such an approach a priority requires organisations to collaborate further, and integrate the output of different teams, including underwriters, risk engineers, exposure managers, and claims managers.

The road is long, but the benefits are real, enabling (re)insurers to identify value and make better risk decisions, improve capital allocation and portfolio segmentation, opening the industry for new growth opportunities.

Antonin & the Allphins team

New Exposure Management Tools Needed for Emerging Risk

When it comes to exposure management in the Property & Casualty (P&C) classes of risks, the (re)insurance industry has focused mostly on natural perils. Natural catastrophic models predict an estimated loss associated with a hurricane or an earthquake in a specific geographical zone.

Those tools are essential because natural perils are prevalent. However, we argue that the risk drivers are getting more and more multidimensional and interconnected. As a result, the core nature of the risks is changing and will continue to change, and exposure management models need to grow too.

New emerging risks

In a world of hyper-connectivity, the (re)insurance industry faces new emerging risks. As documented in its Risk Barometer 2020 report, Allianz ranked cybersecurity and business interruption risks as the two most important business risks for the last four consecutive years (Note 1), relegating natural catastrophes to the third and fourth places over the same period.

Risk drivers such as supply chain disruptions, cyber-attacks, pandemic risks, or political violence are interconnected, having the potential to affect a wide range of business lines.

For example, in the energy sector, there are dependencies between offshore energy installations, such as pipelines and bridges. This presents significant property damage and supply-chain disruptions risk leading to potential risks of a business interruption. A cyberattack or an earthquake affecting an unmanned oil production platform could trigger such an event.

In the Aviation industry, the COVD-19 pandemic has affected the entire supply chain. The grounding of over 70% of the aircraft's fleets has created significant aggregate exposure in specific airports.  

Generally, supply chain and industry practices tend towards more centralisation, hubs, and clusters. Industrial and logistical centres are few but more significant at individual levels, exacerbating the dependencies between risks at the global level.

We believe emerging risks and their connected aspects, in particular, require the industry to rethink exposure management, and design alternative models based on relevant sources of data and fit-for-purpose technologies.

Current tools are not appropriate for undercovering emerging risks

Outside the natural catastrophes models, which have consumed a lot of resources, current model approaches are not appropriate to help underwriters quantify and qualify new emerging risks.

For example, although widely used in P&C (re)insurance, Microsoft Excel is not designed to perform complex exposure calculations or to apply machine learning methodologies, as well as having limited collaborative features.

Using inappropriate tools and data not only undermines the productivity of the underwriting process but also amplifies the uncertainty of the output and erodes the quality of the decision-making.

A better way forward

At Allphins we advocate for a live risk exposure management approach, focusing on interconnected risk, covering both man-made and non-man-made events.

We base models on the following building blocks:

  1. Fit-for-purpose technologies: To foster digital transformation and empower underwriters to transform internal and external unstructured data into insights.
  2. Risk-relevant data: To recognise risks and enhance the information provided by brokers and clients.
  3. Deep sector expertise: To define the realm of potential events.
  4. A cross-class and cross-functional approach connected to other systems

It requires drifting away from relying exclusively on the underwriter's intuition and moving towards blending underwriters' judgment with data and technology. Making such an approach a priority requires organisations to collaborate further, and integrate the output of different teams, including underwriters, risk engineers, exposure managers, and claims managers.

The road is long, but the benefits are real, enabling (re)insurers to identify value and make better risk decisions, improve capital allocation and portfolio segmentation, opening the industry for new growth opportunities.

Antonin & the Allphins team