That's the good news- the bad news is that only 8% achieve that trailblazing underwriting performance and 92% languish with adverse impacts on combined ratios.

Cap Gemini's report;  WORLD PROPERTY AND CASUALTY INSURANCE REPORT 2024   measures the yarning gap between underwriting trailblazers and lower-performing mainstream insurers. This deserves your attention- read the differences below. 

This primary research shows that only 8% of insurers achieve that trailblazing performance so 92% must bridge that gap.  Some reports lack credibility but this one is rigorous with a large representative sample of respondents. 

  • 3,323 insurance customers
  •  294 senior P&C insurer executives
  • 201 leading P&C underwriters
  • from across the globe.

Some key findings: -

  • 83% of insurance executives believe predictive analytic models are critical to success but only 27% say they have them.
  • 70% of trailblazers integrate third-party data effectively with traditional data compared with 12% of typical insurers.
  • 65% of trailblazers deploy mature, optimised underwriter’s workbenches compared with 19% of typical carriers.
  • 78% of trailblazers deploy underwriters as sales enablers compared to 36% of mainstream insurers.

Fortunately, Cap Gemini offers a practical and actionable underwriter’s playbook to bridge the gap to which I have added my insights in this article. ‘Connecting the data dots’ is the key first step. I fully agree but it is a sad truth that after all these years most insurers still find data and analytics a barrier to success.  The report states that a serious lack of data mastery harms most insurer’s core business.  73% grapple with insufficient pricing precision and 70% say inconsistent underwriting decisions are a prevailing headache. 

8% of insurers surveyed are described as underwriting trailblazers i.e. actively providing automated, data-driven decisions or recommendations utilising advanced technology to integrate third-party and traditional data sources. Critical to this superior underwriting performance is underwriters being actively at the heart of internal collaboration, customer transparency, and selling cover. Being a trailblazer means underwriters can deploy the playbook. 

  • Connecting the data dots
  • Unlocking actionable insights
  • Evolving the underwriting role.
  • Delivering business results

Connecting the data dots

You would think this was a fundamental priority achieved by most insurers investing heavily in big data management, data lakes, and AI-driven projects. 

Data silos still prevail, and these grand projects continue to go over budget, over time, and invariably under-achieve. Not just carriers, but also brokers and MGAS including the trend to  global conglomerates that have acquired diverse businesses covering every kind of risk from aviation to zoos. So many applications, platforms, and core record systems are still based wholly or partly on legacy technology, hindering data connectivity. 

Too many core platforms are policy-focused rather than customer-centric hindering personalising solutions and optimising lifetime premium potential. 

Cap Gemini urges insurers to master the intersection between underwriting-specific technologies, CoreTech platforms, and data lakes to turn brilliant dynamic underwriting into the products customers want now, and in the future, plus world-beating customer experiences.

Digital workbenches can help evolve the underwriting role and boost productivity, customer experience, and discipline. ( page 20 in the report). 

It is no good jumping in the deep end without a sound plan, strategy, and the resources to execute transformation projects. Lack of data mastery is just one business challenge and, unless insurers know all of the enterprise’s predictive analytics gaps, transformation advance will be limited. We must first know our customers’ challenges and opportunities before looking at our own. That's an essential first step before you start planning underwriting transformation so that the right customers, markets, and risk cover can be optimised for lifetime customer revenue/premiums and profitability. That requires relevant, actionable, and accurate insights.

Unlocking actionable insights

Modern  MACH-architected core systems, data insight engines, and predictive analytics are key to unlocking the insights identified as vital to meet an insurer’s goals, strategy, and business plans. They can enable insurers to ingest diverse data and power AI from extractive and conversational to full-blown generative AI. 

Combining Cap Gemini’s examples with those described in InsurtechWorld.org you can see examples of good practice.

  • Munich-based Allianz with UK Insurtech Cytora to drive AI-powered risk processing and management (page 19 of the report) 
  • Cytora and hyperexponential partnering to “provide commercial insurers with a more streamlined and informed understanding of risk. The move improves underwriting decisions by basing pricing on real-time data and driving profitable growth.”
  • CGI’s Elements 360 underwriter’s workbench plus Ratabase360 rating technologies power major insurers- over 200 worldwide 
  • Quantee partnering with Zurich Insurance to “provide state of the art, flexible platform that blends traditional and next generation AI-driven techniques for Pricing”
  • MGA The Demex Group analysing and transferring climate-related risk with innovative re-insurance solutions for US carriers and self-insured
  • Predictive insurance analytics-as-a-service provider Giroux.ai found a niche providing data mastery and predictive underwriting insights for MGAs large and small. . 
  • Aiimi Limited with its Insight Data Platform delivering enterprise knowledge into the hands of customer-facing employees at the FCA, blue chip companies, and insurers. Ensuring data mastery vital for effective AI deployment including LLMs, teams of LLMs; an essential first step for underwriting
  • Modern MACH-architectured core platforms (see description in further reading) at the intersection of PAS Systems, Data Lakes, and underwriting technology e.g. Genasys, Instanda, EIS, Novidea, and ICE
  • UK carrier Esure had the vision, courage, and leadership buy-in to re-platform to the MACH architected EIS CoreTech combined with AWS, Amazon Connect, RightIndem Claims platforms, and GenAI with implementation partner EY

The report highlights that actionable insights should focus on efficiency, accuracy, and customer experience.

Evolving the underwriting role

Administration takes up 41% to 43% of an underwriter’s working day!  A further 32% to 33% of the day is spent on core activities leaving just 25% to 26% for growth and sales enablement. No wonder so much time is wasted on admin as they describe how this contributes to their main challenges.

  • Data collection (28% to 33%)
  • Pricing decisions (19% to 32%)
  • Quote generation and policy issuance (45%)

With the right insights and practical technology underwriters can reduce the 55% spent on data collection and pricing to increase the time spent on achieving profitable growth. One major impediment is a lack of trust in the technologies currently deployed. The report highlights that only 43% of underwriters trust automation tools and regularly accept decision recommendations. 67% of underwriters say support analytics tools are too complex and 59% voice data integrity concerns.

Cap Gemini believes that underwriters are not involved early enough in transformation projects. Instead of engaging early with data scientists and engineers, the report recommends a change management cycle.

Early involvement means that underwriters will more readily trust the technologies chosen to enhance their roles and free up more of their time for: -

  • Sales enablement
  • Broker relationship building
  • Book building
  • New product development
  • Achieving trailblazer standards of performance.

To achieve that, of course, the technology partners must themselves collaborate to understand the business, the strategy and spend more time on the insurer’s numbers than their own.

Delivering business results

Trailblazing underwriting means optimising the tasks above to help achieve the superior underwriting and business performance described in the report. That depends upon collaborative technology partners to put ‘skin-in-the-game’ to understand your business goals, deliver minimal viable products faster, at a better value, and apply continuous improvement for competitive advantage. Technology is a means to an end and not the goal itself.

Better value cannot be understated. For too long many technology providers have lived off big-ticket licensing to which add the three to five-year massive upgrade costs of inflexible core platforms with their hidden legacy technology even in cloud -based newer releases. 

The report describes the measurable results expected plan across three key areas.

  1. Productivity
  2. Customer Experience
  3. Discipline

Productivity

Applying the playbook will reduce the data entry workload, generate quotes faster and leverage access to real-time data to anticipate and predict outcomes better.

Customer Experience

Predictive models leveraging AI and ML help price risks better, offer actionable recommendations, and reduce policy-holder’s risk exposure. A better understanding of risk improved personalised recommendations and earns the trust of the customer.

Discipline

A lack of mature and predictive models to augment underwriting skills hinders an underwriter’s ability to evaluate risks methodically via rich data and unique insights. Those combining mature technology capabilities to achieve strategic goals reap the measurable benefits detailed in the report. Reducing operational risk, boosting customer service and improving pricing accuracy. 

Reliable, relevant, complete, and current empirical evidence is superior to subjective judgment and will support innovation.

Collaborating with the right technology partners

Insurers are notorious for running pilots with effective technology partners only to try and then build out underwriting (and other parts of the value-chain) systems only to take too long, spend too much, delay deployment, and under-deliver. It is usually better to choose the right, collaborative technology partners working with internal teams deliver the transformation required. I know many such technology providers have suffered the same problems, but a new breed leverages MACH-architected systems (see further reading)  and viable cost structures to deliver value, adaptability, and the outcomes described above.

Data mastery requires not just sufficient data scientists but deep data engineering resources. Look for partners with those capabilities and the desire and ability to help you decide the right strategies, plans and resourcing to achieve success. To deliver the advanced underwriting they must help you source relevant data, connect the data dots, and extract the actionable insights across the policy lifecycle through interconnected systems. 

The report describes just 8% of insurers scaling the heights to be trailblazers which means that 92% need to adopt the playbook detailed in this report.  That must surely be a priority! Doing so will deliver the well-documented and measurable results you’ll find reading the original report. 

 

Further Reading

MACH- architected systems and platforms

What is a MACH-architected system?

  • Microservices 
  • API first
  • Cloud native
  • Headless

Microservices architected means that you can build a software product as a set of independent components — microservices — where each component operates on its own and interacts with others through APIs. As a result, teams can deploy, change, and improve separate software components without disrupting the rest of the system.

API-first architectures are more flexible allowing teams to choose the most appropriate frontend technology to solve priority business problems. Developers can unify logic across touchpoints and avoid duplication of development work, as well as eliminate channel silos.

APIs allow for fast communication between components, meaning that businesses can reduce the time to implement new touchpoints and accelerate speed-to-market processes.

Cloud-native platforms use the public, private, and hybrid cloud as part of a cloud migration strategy to develop scalable and dynamic data solutions. Insurers will be more resilient to performance issues that often bug on-premises systems.

Headless - far from being clueless!  Insurers that employ headless architecture don’t have a default frontend system that defines how content is presented to end users. You will be able to deliver personalised products and services to your target audience using any channels, devices, and platforms.

When is AI easy and hard to apply?

Scrapping the spreadsheet: take aim at an old insurance addiction