The Insurance Data Revolution
What the Founding Fathers Would Do in 2025
TL;DR:
Insurance companies in 2025 face a defining choice: cling to legacy systems and siloed data - or declare full independence and embrace revolutionary data governance.
Just as the American colonies overthrew distant control to build a bold new system, insurers must unite around AI-powered, automated, and federated data strategies to survive and thrive.
The time for incremental change is over. Data independence isn’t just a technical upgrade - it’s a strategic imperative.
Those who lead will define the future of the industry. Those who delay will be left behind.
What can insurance companies learn from America's quest for independence & Britain's experience of "Dependence Day" about maximising their data assets in 2025?
The Revolutionary Parallel: Then and Now
On July 4, 1776, thirteen American colonies declared independence from British rule, fundamentally transforming the balance of power in the New World.
As comedian John Cleese wryly observed, this date might be better called "Dependence Day" for Great Britain, marking the beginning of the end of its colonial empire and forcing a complete reimagining of its global strategy.
Today, insurance companies face their own revolutionary moment.
The industry is experiencing unprecedented transformation driven by new technologies, changing customer expectations, and the urgent need to extract maximum value from vast data reserves.
Like the American colonies in 1776, insurers must declare independence from legacy systems, siloed data, and manual processes that constrain their growth potential.
The question is not whether this transformation will happen, but how quickly and effectively companies can navigate it.
Source : Today in American History.
The Taxation Without Representation of Poor Data Governance
The American colonists' rallying cry of "no taxation without representation" resonates powerfully with modern insurance companies struggling under the burden of poor data governance.
Just as the colonists felt oppressed by taxes levied without their input into policy decisions, insurance companies today are paying a steep price for data they cannot effectively control, understand, or utilise.
The insurance industry faces challenges with poor data quality and inconsistency, stemming from unstructured data, siloed systems and data complexity across different business lines.
This creates a form of "taxation without representation" where companies invest heavily in data collection and storage but lack meaningful voice or control over how that data can be leveraged for business value.
Consider the parallel struggles:
1776 Challenge: Distant Governance The British Parliament, sitting 3,000 miles away, made decisions affecting colonial commerce without understanding local conditions or needs.
2025 Challenge: Data Silos Data silos can inflate operational costs by up to 30%, creating distant governance of information where different departments make decisions about data without understanding its broader organisational value or interconnections.
1776 Solution: Local Self-Governance The colonies established representative assemblies and local control over their affairs.
2025 Solution: Automated Data Curation AI-powered data curation platforms automate the discovery, understanding, classification and validation of unstructured insurance data, unlocking immediate business value.
The Continental Congress of Data: Building Unified Systems
The First Continental Congress brought together representatives from disparate colonies to coordinate a unified response to British policies.
Similarly, insurance companies need their own "Continental Congress of Data" – unified platforms that bring together information from various business lines, departments, and systems.
Almost all growth in commercial P&C insurance was driven by higher premiums, and insurers must now focus on how they capture consistent, profitable growth amid the shifting market landscape.
This growth challenge parallels the colonies' need to coordinate resources and strategies across different regions with varying economic interests.
The historical lesson is clear: fragmented approaches fail under pressure.
The colonies that remained divided fell to British control, while those that united thrived.
Modern insurance companies face a similar imperative.
Connecting and integrating appropriate products and services requires deep insights into targeted segments, something product-centric organisations like insurers often don't have.
The Praxi Perspective: Federating Data Like Founding Fathers
Praxi's approach to automated data curation mirrors the constitutional principles that emerged from the American Revolution.
Praxi's AI-powered data curation solution creates order where there is chaos by applying smart metadata to define what matters, automate data discovery, streamline decision-making, and stay compliant.
Just as the U.S. Constitution established a federal system balancing state autonomy with national coordination, Praxi's platform enables insurance companies to maintain departmental data ownership while ensuring enterprise-wide discoverability and governance.
Praxi offers a unique approach to data curation by using pre-built industry specific libraries, allowing businesses to easily search and analyse their data without the extensive AI training required by other platforms.
The Boston Tea Party Moment: Rejecting Legacy System Dependence
The Boston Tea Party represented a decisive rejection of economic dependence on British trade policies that no longer served colonial interests.
Insurance companies today face their own "tea party moment" with legacy systems that have become more burden than benefit.
50% of the current insurance workforce will retire in the next 15 years, leaving more than 400,000 open positions unfilled, while only 4% of millennials are interested in insurance careers.
This demographic shift creates an urgent need to move beyond systems and processes that require extensive institutional knowledge to operate effectively.
The historical parallel is instructive: the colonists didn't gradually reform the tea tax system – they rejected it entirely and built new commercial relationships.
Similarly, to fully leverage their data, insurers need to modernise systems, eliminate silos and improve data management through a unified approach to modernisation, automation and data management.
Source : Boston Tea Party, Library of Congress
Revolutionary vs. Evolutionary Change
The American Revolution succeeded because it was bold and comprehensive, not incremental.
The colonists didn't petition for slightly lower taxes – they declared complete independence and built new institutions.
Insurance companies need similar revolutionary thinking about their data strategies.
Many insurance companies find claims processing remains a manual and time-consuming task, riddled with inefficiencies and delays.
The need for a streamlined, automated system is critical.
Incremental improvements to broken processes won't suffice; companies need revolutionary approaches that reimagine how data flows through their organizations.
The Declaration of Data Independence: Core Principles
Drawing from the philosophical foundations of the Declaration of Independence, insurance companies should establish their own core principles for data sovereignty:
1. Self-Evident Truths About Data Value
Just as the Declaration proclaimed certain truths to be "self-evident," insurance companies must recognise fundamental truths about data:
Data scattered across silos loses exponential value
Manual data processes cannot scale with modern business demands
The average cost of a single data breach in 2023 was about $4.5 million, making data security a business imperative, not just an IT concern
2. Inalienable Rights to Data Access
Every department and stakeholder should have inalienable rights to:
Timely access to relevant, high-quality data
Transparency about data lineage and quality metrics
Protection from data governance processes that impede legitimate business needs
3. Consent of the Governed Data Users
Data should be accessible to various stakeholders, enhancing collaboration across departments and ensuring that data is used to its full potential.
Data governance systems derive their just powers from the consent of the business users they serve, not from IT mandates that ignore operational realities.
The Federalist Papers of Data Architecture
Alexander Hamilton, James Madison, and John Jay wrote the Federalist Papers to explain how the new constitutional system would work in practice.
Insurance companies need their own "Federalist Papers" – clear explanations of how modern data architecture serves business objectives.
Organisations are drowning in data but starving for insights.
Praxi CaaS is the solution they need to turn fragmented, unstructured, and unreliable data into a strategic asset for the whole business analytics stack.
Federalist Paper #10: The Problem of Data Factions
Madison's Federalist #10 addressed how to prevent factional interests from overwhelming the common good.
In insurance companies, different departments often become "data factions," hoarding information or implementing incompatible systems that serve narrow interests at the expense of organisational effectiveness.
The solution, like Madison's, involves structured systems that channel competing interests toward productive outcomes.
Praxi's platform automatically surfaces deep insights from structured, semi-structured, un-structured and API-based systems, providing a single interface or API access to search and understand data relationships.
Federalist Paper #51: Checks and Balances in Data Governance
Madison wrote that "ambition must be made to counter ambition" in governmental systems.
In data governance, this translates to automated checks and balances that prevent any single system or department from compromising data quality or accessibility.
Compliance monitoring tools keep insurers ahead of evolving data privacy regulations, simplifying audits and cutting costs.
These automated systems create the checks and balances necessary for sustainable data governance.
The Economic Warfare: Data as Strategic Asset
The Revolutionary War wasn't just about political independence – it was fundamentally about economic control.
The British sought to maintain economic dependence through trade restrictions and preferential treatment for British merchants.
American victory required not just military success but the establishment of independent economic systems.
The life insurance market is being reshaped by the aging global "silver" population and concentration of wealth among Generation X and retirees, while changing social norms present opportunities for more flexible policies catering to nontraditional family structures.
Companies that maintain independence from legacy data constraints can rapidly adapt to these market changes, while those dependent on manual processes and siloed systems lag behind competitors.
The Praxi Arsenal: Pre-Built Industry Intelligence
Praxi's pre-trained insurance-specific models accelerate data curation, classification, and enrichment - so insurers get results in days, not years.
This represents a strategic advantage comparable to the Continental Army's knowledge of local terrain – intimate understanding of industry-specific data challenges enables faster, more effective responses to market opportunities.
The platform's approach recognises that insurance requires precision-built solutions, rejecting generic data tools that force companies to start from scratch.
This mirrors how the colonists leveraged their specific knowledge of American conditions rather than trying to replicate European military strategies.
Valley Forge: Surviving the Data Winter
Every revolution faces its Valley Forge moment – a period of extreme hardship that tests commitment to the cause.
For insurance companies, this often comes during major data transformation initiatives when short-term disruptions threaten to overwhelm long-term benefits.
Carriers will likely be challenged to grow current levels of profitability, especially during periods of disruption and fluctuating demand.
Like Washington's troops at Valley Forge, companies must maintain discipline and vision during difficult transitions.
The historical lesson is crucial: Valley Forge wasn't just about survival – it was where the Continental Army transformed from a collection of regional militias into a professional fighting force.
Similarly, data transformation initiatives shouldn't just solve immediate problems but fundamentally enhance organizational capabilities.
Learning from British Mistakes
Great Britain's experience offers equally valuable lessons.
The empire's decline wasn't sudden but resulted from accumulated strategic mistakes:
Over-reliance on distant control mechanisms – like insurance companies trying to manage modern data needs with legacy centralised systems
Failure to adapt to local conditions – like generic data solutions that ignore insurance industry specifics
Underestimating the cost of maintaining control – like the hidden costs of manual data processes and system maintenance
Traditional methods of data integration are labor-intensive and prone to errors.
Automated systems, trained by experts, minimise manual intervention, thereby reducing the margin for error and significantly accelerating the data management process.
The Constitution of Data: Establishing Lasting Frameworks
The Articles of Confederation failed because they created a weak central government that couldn't effectively coordinate between states.
The Constitution succeeded by balancing federal power with state autonomy. Insurance companies need similar constitutional thinking about data governance.
Praxi's Curation as a Service ensures data compliance, mitigates risks, and meets GDPR and other regulatory standards with robust data governance tools.
This represents a constitutional approach – establishing strong central frameworks while preserving operational flexibility.
The Bill of Rights for Data Users
Just as the Bill of Rights protected individual liberties within the new federal system, data governance frameworks need explicit protections for business users:
First Amendment: Freedom of data expression – users shouldn't be censored or restricted from accessing information needed for legitimate business purposes
Fourth Amendment: Protection against unreasonable data seizures – automated systems shouldn't lock away data behind unnecessarily complex approval processes
Fifth Amendment: Due process in data decisions – users deserve clear explanations when data access is restricted or when quality issues affect their work
The Louisiana Purchase: Expanding Data Territory
Thomas Jefferson's Louisiana Purchase doubled the size of the United States overnight, creating unprecedented opportunities but also new governance challenges. Insurance companies face similar opportunities with emerging data sources – IoT sensors, social media, satellite imagery, and real-time behavioural data.
The research predicts that by 2032, insurers could potentially generate approximately US$4.7 billion in annual global premiums from AI-related insurance, yielding a robust compounded annual growth rate of around 80%.
This represents a "Louisiana Purchase moment" for data-driven insurance products.
The historical lesson is that territorial expansion requires new administrative capabilities.
The U.S. couldn't govern the Louisiana Territory using systems designed for thirteen coastal colonies.
Similarly, the challenges have intensified with the rise of big data, characterised by volume, variety, and velocity, making consistent curation difficult.
The Lewis and Clark Expedition: Data Discovery
Lewis and Clark's expedition mapped the Louisiana Territory and established relationships with Native American tribes.
Insurance companies need similar expeditionary approaches to new data territories. Praxi's platform automatically scans all data platforms and silos to provide comprehensive understanding of data relationships and continuously discovers new data to ensure accuracy and reliability.
This isn't just about cataloging data – it's about understanding the relationships and opportunities that exist within expanded data territories, much like Lewis and Clark mapped not just geography but trade routes, natural resources, and political relationships.
The Industrial Revolution: Automation and Scale
The American Revolution enabled the Industrial Revolution by establishing stable institutions that could support large-scale economic coordination.
Similarly, data independence creates the foundation for automation and AI-driven innovation in insurance.
AI-driven telematics reduces bias in auto insurance pricing for underserved or high-risk areas by focusing on what truly matters—behaviour behind the wheel.
This represents the kind of industrial-scale transformation that becomes possible once foundational data governance is established.
The Praxi Factory System
Praxi Data's unique approach to automated data curation uses pre-trained expert libraries of terms specific to the insurance industry to classify data estates quickly and take meaningful action automatically.
This mirrors how the factory system replaced artisanal production with standardised, scalable processes.
Just as the Industrial Revolution didn't eliminate the need for skilled workers but augmented their capabilities with machinery, automated data curation doesn't eliminate the need for human expertise but amplifies its impact across the organisation.
The Monroe Doctrine: Protecting Data Sovereignty
The Monroe Doctrine declared that European powers should not interfere in American affairs.
Insurance companies need their own "Monroe Doctrine" for data – clear policies about when and how external vendors can access or control critical data assets.
Insurers will be challenged to deliver needed cyber coverage at a reasonable cost, especially given the reality that the nature and scale of potential losses are still difficult to predict.
Data sovereignty isn't just about internal efficiency – it's about maintaining control over information that determines competitive advantage and regulatory compliance.
This requires careful balance.
Complete isolation would prevent beneficial partnerships and innovations, but excessive openness creates vulnerability.
Praxi embeds deeply with insurers, solving their toughest data challenges with a hands-on, high-agency approach, where your success is our success.
Manifest Destiny: The Future of Data-Driven Insurance
America's concept of Manifest Destiny – the belief that westward expansion was both justified and inevitable – has parallels in how insurance companies should approach data-driven transformation.
The expansion of data capabilities across all business functions isn't just beneficial but essential for long-term survival.
We forecast 2.6% total global real premium growth on average in 2025 and 2026, lower than 2024 but higher than the past five years, supported by steady global economic growth, resilient labour markets, rising real incomes as inflation moderates, and still elevated long-term interest rates.
In this competitive environment, companies that fully realise their data potential will capture disproportionate market share.
The Transcontinental Railroad of Data
The Transcontinental Railroad connected the Atlantic and Pacific coasts, enabling unprecedented economic integration.
Insurance companies need their own transcontinental railroads – data pipelines that connect front-office customer interactions with back-office operations, real-time market data with historical analysis, and internal processes with external partnerships.
Praxi CaaS automates data discovery, profiling, classification and automated action, ensuring businesses can trust and unlock the full value of their data.
This comprehensive automation creates the "transcontinental railroad" infrastructure necessary for modern insurance operations.
The Civil War: Choosing Sides in the Data Revolution
The Civil War tested whether the Union could survive fundamental disagreements about its future direction.
Insurance companies face similar tests as they choose between legacy approaches and data-driven transformation.
There's no middle ground – companies will either embrace comprehensive data strategies or fall behind competitors that do.
Insurance leaders do need to take more purposeful action than they have in the past, including closer collaboration with a variety of other stakeholders, to meet industry, customer and societal needs.
Like Lincoln's call for a "new birth of freedom," the insurance industry needs a new birth of data-driven capabilities.
The Emancipation Proclamation freed enslaved people and transformed the war's moral framework.
Insurance companies need their own emancipation proclamation – freeing data from silos and manual processes that prevent it from contributing to organizational success.
Reconstruction: Building Data Infrastructure
The Reconstruction period focused on rebuilding Southern infrastructure and integrating freed slaves into American society.
Insurance companies completing data transformation initiatives face similar reconstruction challenges – not just implementing new systems but ensuring they integrate effectively with existing operations and empower all stakeholders.
Praxi Data aims to continue pushing the boundaries of what's possible in data management, with ongoing commitment to research and development, consistently improving pre-trained machine learning models and expanding services.
This represents the kind of ongoing reconstruction effort necessary for sustainable data transformation.
The Homestead Act: Democratizing Data Access
The Homestead Act provided free land to settlers willing to develop it. Insurance companies need similar policies for data access – making high-quality, curated data freely available to employees willing to use it productively.
Democratisation means making data findable, interoperable, and reusable by breaking down data silos, enhancing collaboration across departments.
The Progressive Era: Data Reform and Innovation
The Progressive Era brought systematic reforms to address problems created by rapid industrialisation.
Insurance companies entering the AI era need similar progressive reforms to address problems created by rapid data accumulation.
AI-driven solutions are revolutionising data management in insurance by offering comprehensive strategies to navigate hurdles through automated data curation, compliance monitoring tools, and predictive analysis that empowers companies to make informed decisions.
This isn't just about implementing new technology but systematically reforming how organisations think about data quality, access, and governance.
Like Progressive Era reforms, these changes require sustained commitment rather than quick fixes.
Conclusion: The Continuing Revolution
The American Revolution didn't end with the Treaty of Paris in 1783 – it continued through the Constitution, the Bill of Rights, westward expansion, and ongoing refinements to democratic institutions.
Similarly, insurance companies' data revolutions won't end with implementing new platforms but will require continuous evolution and improvement.
The insurers who act fastest will win - whether it's assessing risk, pricing policies, or preventing fraud.
Praxi's platform enables real-time, high-confidence decision-making by delivering the right data at the right time.
The lessons from July 4, 1776, and its aftermath provide a framework for understanding how fundamental transformation succeeds:
Unity of Purpose: Just as the colonies needed unified commitment to independence, insurance companies need organisation-wide commitment to data transformation
Revolutionary Thinking: Incremental improvements to broken systems won't suffice – comprehensive reimagining is necessary
Strong Institutions: Success requires building lasting frameworks, not just solving immediate problems
Continuous Adaptation: The revolution continues through ongoing refinement and expansion of capabilities
John Cleese's humorous observation about "Dependence Day" for Britain contains a serious insight: every revolution creates winners and losers based on how quickly and effectively they adapt to new realities.
For insurance companies, the choice is clear – declare independence from legacy data constraints and build the capabilities necessary for long-term success, or remain dependent on approaches that constrain growth and competitiveness.
The biggest risk in insurance is NOT acting on data fast enough.
The time for incremental change has passed.
Like the American colonists in 1776, insurance companies must choose between the security of familiar constraints and the opportunities of data independence.
History shows that those who choose freedom and build the institutions to support it ultimately thrive, while those who resist change find themselves increasingly irrelevant.
The revolution begins with recognising that data independence isn't just about technology – it's about organisational transformation that enables faster decisions, better risk assessment, and superior customer experiences.
As the Founding Fathers discovered, the most powerful force for change isn't external pressure but internal commitment to principles that create lasting advantage.
Source : Founding Fathers, Dirk Deklein
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Why We Wrote This Post - And What You Should Do Next
The AI landscape is undergoing a seismic transformation.
The future belongs not to those with the largest models, but to those with the most precise, compliant, and context-aware data.
We wrote this post to help decision-makers in regulated industries, but particularly Insurance - understand what we can learn on this historic day in America’s history books 📚
In sectors where human lives, financial stability, and legal liability are on the line, precision and auditability aren’t optional - they’re mission-critical.
The shift toward Expert-Trained Contextual Curation (ETCC) isn’t just a technical evolution.
It’s a strategic imperative.
And those who embrace it early will gain a lasting advantage in trust, performance, and regulatory resilience.
Revolution Requires Vision, Courage, and Tools
History teaches us: those who seize the moment shape the future.
2025 is the insurance industry's July 4th. The opportunity isn’t just to “modernise”—but to lead a revolution in how data powers insight, action, and advantage.
🔔 Declare your Data Independence.
And if you're ready to go from Declaration to Implementation - Praxi is your Lafayette. 🇺🇸📊
Schedule a discovery session with our team at Praxi.ai, or reach out directly to start your shift toward compliance-first intelligence.