Exposure Management Challenges Today
Key results
Reduced exposure analysis time, enabling swift responses during peak periods.
Delivered real-time analytics to validate assumptions and align exposures with risk appetite.
Improved ability to analyze year-on-year changes and assess profitability with actionable insights.
As reinsurance companies grapple with increasingly complex risks, Exposure Management (EM) is becoming a similarly important tool in the underwriting armoury. At the recent Allphins roundtable, exposure management professionals and underwriters from leading firms gathered to share candid reflections on where EM stands today—and where it needs to go.
Naturally, one of the first things we asked our contributors was: where are the big challenges they face today? There was some concern for talent, with one of our guests noting: “We have a lot of problems losing people to other areas of insurance. It’s good for the market - you're sending people out with knowledge- but it’s hard internally. We’ve got to keep people interested and give them a career path.” But the vast majority of issues faced by our panel concerned data: either there is too much of it, too little of it, or not enough of quality to truly aid decision-making...
Drowning in Data
One urgent theme was the sheer volume and complexity of data flooding across desks – and a healthy skepticism as to whether it’s all useful. “There’s been an explosion of tech, an explosion of different model options from different vendors,” says Vanessa Jones, Head of Exposure Management at Dale Underwriting Partners. “The challenge is filtering through it and avoiding decision paralysis. I always try to pull the focus back onto what the underwriting need is: what nuggets of that huge amount of information do we really need to drive our pricing and portfolio management decisions?”
This was echoed by Blenheim Syndicate’s Head of Exposure Management, James Simpson, who adds that while product choice has multiplied, making a meaningful comparison and evaluation of those software products and their underlying models has become commensurately harder. “Choosing what’s best, reviewing it all—keeping on top of it is almost impossible,” he says.
Rather than clarity, the proliferation of models and data feeds is, paradoxically, creating confusion for many insurance professionals. The core question is: how do you extract the insights that matter for underwriting and steering a portfolio, without being overwhelmed?
Beyond the Big Perils
Concerns were also raised about the blind spots in models, especially for lesser perils that are increasingly driving losses but don’t get the analytic attention they perhaps deserve. One of our guests noted, “There’s plenty of comfort around the main perils like wind, storm and earthquakes, but we’re seeing losses come through from other perils where we still need better ways of tracking them. ”Getting enough data – or data with enough granularity - for effective modelling at this secondary level remains an ongoing issue, especially in the retro space.
The Data Quality Conundrum
The issue isn’t just the volume of data, it’s consistency. One of our contributors added, “There’s so much untapped NatCat data in whole new classes—credit risk, casualty, financial lines… How do you harness all of that meaningfully?”
Mathias Borjesson, SVP of Underwriting at RenaissanceRe, agrees, and says that data complexity represents an everyday operational challenge: “There's a lot of tools and tech that we've been building on the last five years or so, in an attempt to overcome the data deficiencies in the market, which is just something we’d rather not have to do. A lot of effort and spend goes into matching up different submissions from different providers around the world.”
A common refrain across our discussion was the fact that the timeliness and quality of binder materials are as much of a problem as their consistency. That’s not specifically a data quality issue; it means that even with perfect data, applying it in context to the cadence of policy renewals is hamstrung. “Consistency and timeliness of binder data are a real bugbear for me”, said one guest.
More with more…
As exposure management stretches to cover more risks, more regions, and more classes of business, the pressures on its practitioners are growing too. There’s pressure to stay abreast of new tools, navigate noisy data, and retain skilled teams—all while maintaining meaningful underwriting discipline under the watchful eye of investors, the capital markets, Lloyds, regulators and boards. The tools and data at our disposal are more powerful than ever, but their complexity is a double-edged sword. EM professionals aren’t being asked to do more with less – more challengingly, they’re being expected to do more with more.
Exposure Management Challenges Today
As reinsurance companies grapple with increasingly complex risks, Exposure Management (EM) is becoming a similarly important tool in the underwriting armoury. At the recent Allphins roundtable, exposure management professionals and underwriters from leading firms gathered to share candid reflections on where EM stands today—and where it needs to go.
Naturally, one of the first things we asked our contributors was: where are the big challenges they face today? There was some concern for talent, with one of our guests noting: “We have a lot of problems losing people to other areas of insurance. It’s good for the market - you're sending people out with knowledge- but it’s hard internally. We’ve got to keep people interested and give them a career path.” But the vast majority of issues faced by our panel concerned data: either there is too much of it, too little of it, or not enough of quality to truly aid decision-making...
Drowning in Data
One urgent theme was the sheer volume and complexity of data flooding across desks – and a healthy skepticism as to whether it’s all useful. “There’s been an explosion of tech, an explosion of different model options from different vendors,” says Vanessa Jones, Head of Exposure Management at Dale Underwriting Partners. “The challenge is filtering through it and avoiding decision paralysis. I always try to pull the focus back onto what the underwriting need is: what nuggets of that huge amount of information do we really need to drive our pricing and portfolio management decisions?”
This was echoed by Blenheim Syndicate’s Head of Exposure Management, James Simpson, who adds that while product choice has multiplied, making a meaningful comparison and evaluation of those software products and their underlying models has become commensurately harder. “Choosing what’s best, reviewing it all—keeping on top of it is almost impossible,” he says.
Rather than clarity, the proliferation of models and data feeds is, paradoxically, creating confusion for many insurance professionals. The core question is: how do you extract the insights that matter for underwriting and steering a portfolio, without being overwhelmed?
Beyond the Big Perils
Concerns were also raised about the blind spots in models, especially for lesser perils that are increasingly driving losses but don’t get the analytic attention they perhaps deserve. One of our guests noted, “There’s plenty of comfort around the main perils like wind, storm and earthquakes, but we’re seeing losses come through from other perils where we still need better ways of tracking them. ”Getting enough data – or data with enough granularity - for effective modelling at this secondary level remains an ongoing issue, especially in the retro space.
The Data Quality Conundrum
The issue isn’t just the volume of data, it’s consistency. One of our contributors added, “There’s so much untapped NatCat data in whole new classes—credit risk, casualty, financial lines… How do you harness all of that meaningfully?”
Mathias Borjesson, SVP of Underwriting at RenaissanceRe, agrees, and says that data complexity represents an everyday operational challenge: “There's a lot of tools and tech that we've been building on the last five years or so, in an attempt to overcome the data deficiencies in the market, which is just something we’d rather not have to do. A lot of effort and spend goes into matching up different submissions from different providers around the world.”
A common refrain across our discussion was the fact that the timeliness and quality of binder materials are as much of a problem as their consistency. That’s not specifically a data quality issue; it means that even with perfect data, applying it in context to the cadence of policy renewals is hamstrung. “Consistency and timeliness of binder data are a real bugbear for me”, said one guest.
More with more…
As exposure management stretches to cover more risks, more regions, and more classes of business, the pressures on its practitioners are growing too. There’s pressure to stay abreast of new tools, navigate noisy data, and retain skilled teams—all while maintaining meaningful underwriting discipline under the watchful eye of investors, the capital markets, Lloyds, regulators and boards. The tools and data at our disposal are more powerful than ever, but their complexity is a double-edged sword. EM professionals aren’t being asked to do more with less – more challengingly, they’re being expected to do more with more.