This article is shared with the kind permission of Insurance Edge.
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According to Statista, the amount of data created, captured, copied, and consumed globally is projected to reach 180 zettabytes by 2025. This is an increase of about 50% from 2023. For those that don’t know off the top of their heads, a zettabyte is equal to one sextillion bytes, or 1,000,000,000,000,000,000,000 bytes.
Statistia’s staggering figure underscores the importance of data management across industries, particularly in re/insurance. In the re/insurance sector, data is not just a byproduct of business processes – it is the foundation upon which risk assessments, underwriting decisions, and compliance are built.
So it follows that for our sector, the rapidly evolving global insurance market, the sheer volume of data generated and processed is also increasing almost exponentially. Yet, with such a massive influx of information, the quality of data often becomes compromised. Inaccurate, non-standardised or incomplete data can set off a chain reaction of errors, undermining risk models, misguiding exposure management, and leading to compliance breaches.
As we approach 2025, re/insurers are increasingly investing in robust data cleansing processes to mitigate these risks. In this editorial, we will explore the latest trends in data cleansing, the impact of poor data on exposure management, and the tools and techniques reshaping the insurance landscape.
The Impact of Poor Data on Exposure Management and Risk Models
At the core of re/insurance operations is exposure management—the process of evaluating and pricing risk across portfolios. This process relies on accurate data, such as property valuations, geographical information, and historical loss data. Exposure models, such as catastrophe models for natural disasters, are fueled by this data, and the quality of the input directly impacts the accuracy of the output.
However, exposure schedules or Statements of Value (SOVs) often come riddled with errors—outdated property valuations, missing fields, or inconsistencies across datasets. These data discrepancies not only skew the models but can also lead to mispricing of risk, which may result in significant financial loss or, worse, inability to pay claims accurately in the event of a disaster.
Inaccurate data also hampers decision-making. For instance, a re/insurer may overestimate their exposure in a particular region, leading to unnecessary capital allocations or reinsurance purchases. Conversely, underestimating exposure may leave the company vulnerable to catastrophic losses. The cascading effect of poor data is clear, as it touches every part of the insurance value chain—from underwriting to claims handling.
Compliance Risks Tied to Data Quality
Beyond the financial implications, incorrect or unverified data also brings a host of compliance issues. The insurance industry is one of the most heavily regulated sectors, and regulatory bodies are scrutinising data quality and governance more closely than ever. Regulators demand that insurers have robust systems in place for managing and verifying their data, particularly in light of increased transparency requirements and evolving risk landscapes.
Data sharing within the insurance chain also poses risks. Re/insurers often work with multiple partners – brokers, agents, and reinsurers – and need to share exposure data to ensure that all parties are aligned on risk levels. If one party is operating on incomplete or incorrect data, the entire insurance chain can become compromised, leading to disputes, delays in claim settlements, or breaches in service-level agreements (SLAs). Insurers must, therefore, ensure that their data is clean, accurate, and compliant before sharing it with partners.
Garbage in = garbage out
Though nearly 20 years old, Hurricane Katrina is the storm that really focused the market’s attention on loss modelling, data quality and the impact of bad or incomplete data. In the exposure management world this event was a game changer.
After the event, it became clear that a number of locations were coded as concrete ‘on land’ Casino’s whereas actually they were floating Casino’s built on barges, which were far more susceptible to storm damage. Incorrect location data translated to a poor understanding of where exactly levees were located and an underestimation of the ultimate flood risks.
Incorrect location data can put risks into or outside of hazard zones leading to an incorrect assessment of the risk. To increase efficiency around geocoding some Insurers opt to model locations based on ZIP codes over street addresses, however this has proven to increase the amount of inaccurate loss estimations.
Trends in Data Cleansing
The process of data cleansing involves cleaning, validating, and standardising data, particularly exposure schedules, to ensure that models run on reliable information. In recent years, technological advancements have transformed how this cleansing process is performed.
One of the biggest trends is the adoption of augmented data platforms that automate much of the data cleansing workload. These platforms use machine learning and AI to scan vast datasets, flag inconsistencies, and apply fixes at scale. The advantages are clear: speed, accuracy, and consistency. Augmented tools can cleanse large volumes of data more efficiently than it would take human analysts while reducing the risk of manual errors.
Techniques such as anomaly detection and pattern recognition are also becoming commonplace. These allow insurers to identify outliers in datasets – whether it’s an abnormally low property valuation or a misclassified exposure – and correct them before they cause issues downstream. Data enrichment, another technique gaining traction, involves enhancing raw data with third-party information (such as location intelligence) to fill in gaps and improve overall data quality.
Despite these advancements in the automation of data cleansing functions, human oversight remains vital. While AI-driven tools are excellent at automating routine tasks, they still require human input to set parameters, validate results, and make judgement calls on more complex data issues. Additionally, insurers must balance the need for rapid data cleansing with the risk of over-relying on automation. There’s always the risk that in an effort to streamline processes, insurers may inadvertently bypass critical validation steps, leaving errors undetected.
The Future of Data Cleansing in Re/Insurance
Looking ahead, the role of data cleansing in the re/insurance sector is only set to grow. As insurers continue to face pressure to innovate and reduce operational costs, we can expect to see even greater reliance on automated data platforms. Advanced AI systems are likely to evolve, allowing for real-time data cleansing that seamlessly integrates into exposure models. This will dramatically reduce the time it takes to underwrite policies, giving companies a competitive edge in the fast-paced market.
Moreover, data governance and compliance will continue to be a key driver. Regulatory bodies are unlikely to ease their demands on data quality; in fact, with the ever-expanding scope of environmental, social, and governance (ESG) considerations, insurers will need to ensure that their data is not only clean but also aligned with broader compliance and reporting standards.
In 2025, the re/insurance sector will likely see a convergence of data cleansing, compliance, and exposure management. Clean, validated, and standardised data will become the linchpin of the re/insurance industry, and those who fall behind risk not only financial loss but also regulatory and reputational consequences.
Insurers must ensure they have strong robust data validation, data cleansing and data enhancement, which are key to accurate risk assessment. Technology works best when monitored and controlled by a team with subject matter expertise and processes established by experience.
For those insured, providing as much data as possible around locations, occupancies, constructions and additional modifiers is also key. The more current and accurate the data, the more accurate the loss estimate and the premium.
Name: James Hunt
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The Legacy Burden for Brokers
Legacy business is often seen as an inconvenient burden, impacting the value and profitability of broking operations. The challenges range from the ongoing cost of managing accounts in run-off to resolving aged funding, unallocated cash, and retaining knowledgeable staff. Legacy systems, often outdated and incompatible, add to the complexity, requiring costly maintenance or intricate transfers.
For brokers, a passive approach to legacy management might yield satisfactory results, but a proactive strategy can unlock significant benefits. Pro Global’s proven track record in descaling over US$3 billion in liabilities across various business classes positions us as a key ally for brokers seeking a strategic shift in effective and efficient legacy management.
A proactive legacy management strategy involves identifying, segregating, and de-scaling entire legacy portfolios, allowing brokers to focus on growth and core business activities.The key lies in a dedicated, multi-functional team, including claims handling, technical processing, IBA resolution, and credit control expertise.
This can be achieved by diverting experienced resources to establish an in-house legacy team or outsourcing to a specialist provider like Pro Global. From premium and claims technical accounting to legacy broker acquisition, our expertise is renowned for ensuring a comprehensive and strategic approach to legacy management.
An opportunity for Transformation
As the market plans for highly competitive market conditions across many classes of business in 2024, brokers can view legacy business not as a burden but as an opportunity for transformation. Pro Global’s Broker Services division stands ready to assist brokers in navigating the challenges of legacy administration. By adopting a proactive approach, brokers can unlock value, protect market reputation and optimise processes to minimise the legacy burden going forward.
Broker Transfer: A Path to Finality and Certainty
For brokers seeking finality and certainty in legacy management, the Broker Transfer solution provided by Pro Global is a game-changer. This solution allows Pro to assume entire legacy portfolios and accounts, becoming the formal Broker of Record.
The process usually involves an interim period where Pro works with Brokers to ring-fence the business to be transferred and ensure a smooth transition. Following regulatory approvals, Pro takes on all obligations and liabilities for ongoing administration, providing brokers with the freedom to concentrate on their core business priorities.
The call to action is clear: By collaborating with specialists like Pro Global, brokers can concentrate on strategic growth opportunities while we handle the complexities of legacy management. This allows them to reduce the unwanted distraction of legacy liabilities, optimise operational processes, and resolve long-standing issues. The future of brokerage lies in transforming challenges into growth potential. While our clients lead the way in their respective fields, Pro Global is here to provide our expert support.
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Traditionally, German insurers have been cautious when it comes to outsourcing to TPAs, as many see claims handling as their core competence. However, a shortage of experts and increase in complex claims has led to an increase in demand for trusted claims outsourcing partners.
This, in turn, has led to questions surrounding data protection, particularly sensitive personal data in the case of life insurance and disability claims handling. The complexities around data protection and outsourcing of claims cannot be an afterthought, but if proactively addressed by experienced teams, can be properly accounted for and – crucially – audited and proven.
With these evolving dynamics in the market, we are beginning to see early indications of a shift in mindset. The TPA model is gaining acceptance as a strategic tool for insurers, and a growing number of insurers are opening up dialogues around the possibilities of TPA support in the year ahead, with a focus on scrutinising the expertise and experience of potential TPA support teams.
The Changing Face of TPA in Germany
The global insurance TPA market has been on a steady upward trajectory, with a size valued at $324.9 billion in 2022, projected to reach an impressive $795.1 billion by 2032, growing at a remarkable CAGR of 9.6% from 2023 to 2032. TPAs have emerged as licensed third-party entities that offer administrative solutions to the market, particularly in the complex areas of disability claims handling and life insurance, as well as employment insurance. They act as intermediaries between insurance companies and policyholders, streamlining processes such as cashless claims and reimbursement claims, ensuring effective settlements, among other functions.
A surge in claims can lead to a surge in work for insurers, sometimes at the expense of service quality. TPAs have risen to address this issue by assisting insurers in providing seamless claim settlements and scrutinising complex claims for accuracy. They play a vital role in processing claims, providing a more efficient and customer-friendly experience.
So, what is driving this shift in Germany’s TPA landscape, and why are insurers now considering the outsourcing model more seriously?
The main reason for outsourcing is the shortage of experts, and this is particularly true in the disability claims handling market where cases can be very complex, and experts are few. The challenges are different for the various insurers; large insurers naturally have technical support and experts in-house, however when complex claims volumes rise, the number of experts is often simply not sufficient and external help is needed.
For large insurers, TPA support during work peaks as well as maternity and holiday cover also plays a major role. Small insurers, on the other hand, often require less technical support. Here, the loss of one expert (if the business only has four on-house complex claims specialists, for example) can already mean a 25% loss of productivity.
Many very small insurers can no longer sustainably maintain their expertise and need external support. In addition, demographic change is exacerbating the situation, with a loss of experienced talent in the market through retirement over the coming five years, and a lack of incoming claims experts to replace them.
Data Protection and Expertise
At the same time, German insurers – as with entities across Europe and the UK – have long been concerned about data protection and the expertise available with outsourcing to TPAs. Data privacy regulations, most notably the General Data Protection Regulation (GDPR), have added complexity to data handling and sharing. The sensitivity surrounding personal data – particularly health and disability data – has understandably made insurers cautious about sharing such information with external parties.
However, market-leading TPA providers have recognised these concerns and have invested heavily in robust data security measures and compliance protocols. They understand the importance of maintaining data confidentiality, and many have obtained certifications and expertise to handle data in full compliance with regulatory standards.
Furthermore, the availability of experts with a proven track record in insurance, who thoroughly comprehend the challenges around data privacy, confidentiality, and trust, has improved. This has instilled confidence in insurers, as they can now partner with TPAs who have the requisite knowledge and experience to handle their unique demands.
Partnership Approach
A partnership approach is critical to the evolving TPA market in Germany. Best practice sees TPAs and insurers collaborate closely to ensure that the TPA solutions align with the insurer’s specific needs and goals. Flexibility is inherent in the model – insurers seeking outsourcing support like this can decide the scope of the cooperation.
Complete outsourcing of claims management is possible, for instance, but so is outsourcing that leaves the decision-making power with the insurer. In this way, the insurer receives the support it needs, but does not lose its core expertise.
This flexible partnership mentality is gaining traction as both parties recognise the mutual benefits and efficiencies of working together harmoniously.
With TPAs acting as an extension of insurers, the shared responsibility for customer satisfaction and efficient claims processing leads to better outcomes for all stakeholders. This collaborative mindset fosters innovation and allows for more tailored solutions that can drive growth, agility, and efficiency, and also ensure momentum with claims handling does not wane at peak times.
A Look at Other Markets
To understand the full potential of the TPA model, it’s instructive to examine more mature TPA outsourcing markets, such as the United Kingdom and the Netherlands. In these regions, the TPA model has already proven its worth – helping insurers grow faster, become more agile, and operate with greater efficiency.
The adoption of TPAs in these markets has been instrumental in streamlining claims processing, reducing costs, and improving overall service quality. Insurers in the UK and the Netherlands have benefited from the expertise and capabilities that TPAs bring to the table, allowing them to focus on core functions and strategic growth.
TPAs: Empowering Growth in 2024
During 2024, the TPA market in Germany is poised for growth. In a market where in-house resources are often stretched, the maturing TPA model, with a focus on data protection, expertise, and partnership, is set to drive efficiencies and enhance the customer experience for insurers and policyholders alike, particularly at peak times for claims.
The lessons learned from more established markets can also ensure that Germany’s insurers adopt best practice with TPA outsourcing from the get-go. It is a transformation that promises to empower a new era of growth and efficiency for the industry in Germany,and the Pro Global team is on standby to support.
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