How insurers can better leverage data to maximise underwriting profitability and efficiency

Despite P&C insurance being transformed by the adoption of digitalisation and automation, insurers are struggling to be ‘scientific’ on risk, impacting the profitability of underwriting, according to AdvantageGo senior director of business development Rupert Bidwell. 

Risk and underwriting decisions are made by leveraging expertise, data and science to make accurate decisions. However, a recent report from AdvantageGo stated that only 16% of insurers have access to up-to-date external data sources needed to make scientific decisions on risk.

Data-driven decision making can improve underwriting, but only if its being used properly.  Speaking with FinTech Global ahead of the Global InsurTech Summit, Bidwell discussed how insurers can improve underwriting profitability and efficiency through improved data insights.

How can insurers drive underwriting profitability and efficiency through smart underwriting using multiple sources of data to maximise data insights?

Integrating the wealth of data available into the underwriting decision-making process can seem like a daunting task, but it doesn’t have to be. Through industrialising the generation of data-driven insights with in-house data (risk, claims etc), and external data from different sources, Underwriters can accurately assess the marginal impact of new quotes on their portfolio to make the best underwriting decisions. Analytics-driven insights have been shown to help Underwriters spot new and emerging markets and opportunities to cross-sell and engage with clients, including the historic role of informing underwriting and pricing rules.

Smart underwriting is about embedding multiple data sources in processes and maximising data insights to unlock growth to become a trusted partner to clients.

How are insurers failing to leverage all the necessary data for underwriting damaging the industry?

There has always been a history of leveraging data in the insurance industry from the perspective of identifying new rating factors and changes that need to be made to track the evolution of risk in underwriting portfolios, and the industry has these skills and the expertise. The challenge today is fourfold:

  • Seeing the wood from the trees. There is now so much internal (risk, location, claims) and external data that can be analysed for potential use in underwriting.
  • Operationalising the analysis so that “the wood from the trees” can be seen is the next challenge, especially as computing power is no longer an issue. A slick industrial process to identify the next material insight is everything.
  • Operationalising the insight in the underwriting organisation whereby the underwriter’s systems and tools are updated to deploy the insight.
  • Operationalising the insight in the value chain whereby all the stakeholders in the value chain make the data available to underwriters to use in a low-cost, machine readable form, or finding an alternative way to source the data with each risk underwritten.

How can insurers ensure their risk assessments are being more “scientific” and leveraging all the data that is available?

Quite simply, it breaks down into three areas: organisational change, skills availability, and the right technology along the breadth of the value chain. Firstly, there needs to be a clear understanding of an organisation’s actual use of data and science, which means clear communication between senior executives and the frontline. Secondly, those using the technology need to have the skills to use science, data, and the right tools in their decision-making processes. The second area of focus is on skills availability and making sure Insurers attract the right talent. Lastly, the right people, with the appropriate levels of understanding across the business can only do so much if they do not have the best tools and systems at their disposal, whereby the insights can be operationalised within the underwriting process and the original data can be provided by upstream parties.

Why is a data centric strategy in the pre-bind phase key to driving efficiencies and growth?

Having a data-centric strategy in the pre-bind phase that connects all the dots in underwriting processes driving underwriting profitability. The pre-bind phase requires ingesting vast amounts of data. The systems in place need to handle that data quickly and allow underwriters to shift, make changes, and respond to the market changes that are constantly happening in the digital age. If you look at the sheer amount of data coming into underwriters’ desks every day, without a best of breed pre-bind solution there is a risk of being overwhelmed by the data.

Are there data sources that many firms are not utilising, which would massively improve how they underwrite?

Of course there are; the challenge is the operationalisation of the process of identifying which data is material and needs to be used in the go forward underwriting.  This is not a static process as risk has never been less static, be it from climate change, socio economic change, rapid urbanisation or technology change, which creates hazard in its own right and enables other risk factors like social inflation.

Does the insurance industry have confidence in the technology that underpins its underwriting decision making – now and in the future?

Not yet, but it is better than before; the pandemic has accelerated digitisation projects at many Insurers. The wholesale migration of the (re)insurance market to remote working nearly a year ago is a well-regarded achievement, and its relatively smooth transition was largely down to technology. The most significant issue remade though is securing the data into the value chain in a machine-readable form; there is no point in underwriters deploying new rules and rates if they can not cost effectively secure the data to operationalise.

Pre-COVID-19, when companies identified software or technology gaps, their first thought was to build their own solution. Nowadays, companies don’t have the luxury of time to build up a solution, so they adopt the technologies in the market that allow them to fix that gap in months rather than years. Underwriters who previously dealt with a multitude of disparate systems have now seen the light when it comes to being able to unite those disparate solutions into a single source of the truth. They see data-driven decisions and analytics that give them insights into those risks and the underwriting process and allow them to process business more effectively. You are seeing InsurTech investment increases year over year.

What can be done to encourage firms to be more adoptive of technology for underwriting?

I think the industry is already doing a great job embracing underwriting tools and incorporating analytics within the decision-making process. Insurers are keen to be part of the digitisation revolution, but their legacy systems are holding them back and thwarting efforts to allow them to make the best of the new opportunities.

Integration of new technology into old technology is a problem as many legacy systems lack APIs, and poor governance has created data quality issues. Most of these systems are highly customised, so changing them can be costly and disruptive.

Adopting new technology doesn’t need to come from radical and disruptive changes. Processes and systems can be updated in small chunks that don’t disrupt the whole ecosystem. Our guidance is that it’s crucial to be selective when it comes to deploying new technology. If your legacy technology is still fulfilling your needs, there’s no need to replace it. The key is to fully understand your options and how new technology can integrate with what you already have. Don’t trust anyone that says this can’t happen.

Are companies still investing enough to make a genuinely forceful change?

It depends on who you ask. In a survey of 200 (re)insurers we conducted at the end of 2020, only one-third of respondents felt that the technology in use was highly effective at adapting quickly to customers’ changing underwriting requirements. However, the survey revealed a disconnect, with 38% of senior respondents likely to think the technology at their disposal was highly effective for adapting to customer needs, compared to just 23% of frontline employees.

The pandemic has forced insurers to scrutinise their entire technological ecosystem and pinpoint where they need to invest to provide the right solutions for their day-to-day operations to be more efficient and profitable and keep up with their competitors.

In today’s volatile environment where Insurers must embrace data-driven decision-making, it is not a “nice to have” anymore, it is a must. We don’t know what is coming tomorrow – the pandemic has clearly shown that. The tumultuous economic and political atmosphere means carriers not to rely on all the resources at their fingertips and allow their Underwriters to provide feedback to the C-suite, making rapid changes and responding to market needs.

How can Artificial Intelligence enhance and support an Underwriter’s tacit knowledge and augment the underwriting process for Underwriters?

Intelligent automation and intelligence-based assistance do not mean codifying an Underwriter’s tacit knowledge as in its very nature, tacit knowledge is difficult to write down and share as it’s based on experiences, insights, and intuition. However, there is still a sentiment in the market that AI and machine learning will eventually replace an Underwriter – this couldn’t be further from the truth. AI and intelligent automation are about providing contextual and relevant information from the varied data sources and providers at the right time in the underwriting process to validate tacit knowledge.

For example, if a new risk is location-based such as with property and marine, having access to hazard information, peril scores, and cat risks in real-time can help decide the risk factors that could be used in pricing models, probabilistic models, and contractual inclusions and exclusions. Intelligence-based assistance processes can automate the homogeneous process and present the underwriter with a holistic view of the risk factors and peril scores. Non-location-based risks, such as casualty insurance would provide risk assessments from a global view, with some assessments being relevant at country level, such as political, terrorist, and incidental risks. Automating menial and low-value tasks through intelligent automation and intelligence-based assistance liberates Underwriters to focus on high-value tasks and connects disparate information to bring sense and insights to the underwriting process. Where once this would have been a manual activity to source, digest, analyse and report, this activity can now operate in the background of the underwriting process allowing the underwriters to concentrate fully on the foreground thought, assessment and decision-making process.

To what extent will the success of an insurer be tied to their ability to leverage all the available data for their underwriting?

Absolutely critical; risk has never been less static, the process of identifying change and actioning that change into underwriting has never been more important.

 How does AdvantageGo revolutionise how insurers are underwriting?

We have over 25 years’ experience as an InsurTech, and our philosophy is to work closely with the market to ensure that our software is fit for purpose. Our ‘Underwriting’ platform, specifically designed for and in partnership with underwriters, streamlines and automates low-value tasks, systemises processes, and improves operational excellence. Powered by an ecosystem of data providers supporting data-led decisions, ‘Underwriting’ proactively delivers new business insights and risk-specific knowledge. When combined with an underwriter’s own intellectual property and existing data assets, underwriters can begin to create new products, understand risk at new levels of granularity and differentiate beyond their peers. We combine our other core solutions with revolutionary microservices, enabling (re)insurers to rapidly and effortlessly scale with new business models and products.

To hear more from Bidwell and the AdvantageGo team, you can join the Global InsurTech Summit to get their insights, and those of other leaders in the sector, through a range of panels and demos. 

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