AI and generative AI are revolutionizing risk management, replacing standardized, one-size-fits-all models with personalized risk assessments and precisely tailored mitigation strategies. This transformation empowers businesses to make data-driven decisions, fostering a more predictive and proactive approach to risk. Insurance organizations that embrace AI-driven solutions in risk management will not only enhance their resilience but also gain a competitive edge in an increasingly dynamic market. 

This article explores key foundational strategies for risk mitigation, emphasizing the integration of AI and agentic AI to enhance workflow efficiency, mitigate hazards and enable proactive decision-making.

Aggregating Data and Seamless Integrations

To truly realize the power of "predict and prevent," insurers must first establish a strong data foundation. This involves bringing together enormous and diverse pools of data – everything from prior claims and customer data to real-time IoT sensor data and external environmental data – into a single coherent and shareable repository. 

Modern architectures like the data lakehouse bring the scalability and flexibility required to set up such an endeavor, while allowing structured and unstructured data to exist together. Flexibility to consolidate this data centrally and integrate it with sophisticated analytics tools and third-party data sources is also key. This can be achieved through partnerships with specialized data providers that offer pre-packaged risk intelligence or by building sophisticated homegrown integration solutions, whereby actionable insights can be extracted and communicated efficiently within the organization. 

The ability of AI to aggregate and interpret information from increasingly heterogeneous sources (text, images, video, sensor inputs, geospatial data, biometric data, etc.) will produce ever more inclusive and contextually aware risk estimates.

The Dual Approach to Future-Proof Risk Management

To mitigate risks by addressing hazards in real time, organizations must implement a well-structured central repository to store rules, manage versions, track changes, and facilitate reuse across applications or processes. Logical grouping—whether by process stage or product line—enhances navigability and ensures streamlined rule deployment. 

A centralized rules engine powered by agentic AI can enable carriers to dynamically adapt straight-through processing workflows, allowing for real-time risk mitigation and proactive decision-making. With access to central data, agentic analytics can be used for live streams of IoT sensor data, telematics, and customer behavior to detect risk patterns as they develop. For instance, by analyzing claims data anomalies in combination with external signals (such as weather and market trends), agentic platforms can alert insurers to high-risk conditions before they translate into large-scale losses.

While agentic AI analytics detect anomalies, simulate exposure, and trigger actions in real time, centralized rules ensure uniform decision-making across underwriting, claims, compliance, and catastrophe response. Together, they reduce fraud, improve regulatory adherence, and enhance operational resilience in an increasingly complex risk landscape.

Ethical AI in Risk Mitigation

The integration of AI comes with complex ethical considerations. Bias in data can result in unfair or discriminatory outcomes, creating significant reputational risks. Privacy and data security remain critical concerns, given the extensive use of personal information in AI-driven systems. The opaque nature of certain reasoning models, particularly their hidden layers, raises challenges around explainability and trust.

To ensure responsible adoption, organizations must establish clear accountability measures and conduct regular audits of AI systems. Concerns about AI fabricating responses further underscore the importance of verification methods, such as retrieval augmented generation (RAG), to ground outputs in factual data. 

Additionally, discussions around AI bias in underwriting highlight the necessity of objective criteria and human oversight to prevent discriminatory practices. By integrating actuarial oversight into the AI lifecycle, organizations can create a more transparent, accountable, and resilient risk mitigation strategy. Actuaries play a vital role in contextualizing model-generated predictions within real-world constraints, protecting against overfitting, bias, and unforeseeable consequences.

Looking Ahead

The shift to a "predict and prevent" model of risk management is a continuing approach, and both opportunity and challenge are compelling it forward. As catastrophic loss prediction using AI becomes increasingly sophisticated, the industry has the rare opportunity to put more effective preventative solutions in place, potentially reducing the impact of major events and creating a positive effect on the property market. 

In spite of risks like data bias and job displacement, AI's role as an intelligent assistant is indisputable—augmenting human knowledge instead of replacing it. The insurance sector is at a tipping point, having the technology and strategic intent to create a more robust tomorrow. 

Effective use of AI and GenAI for pre-loss risk prevention demands an integrated approach—one that weighs technological advancement with a resolve for responsible development, ethical application, and continuing learning. As these technologies develop, their impact in helping to protect assets, save lives, and create improved organizations and communities will only increase, heralding a new era where loss prevention is no longer a dream but a reality.

The insurance industry is built on trust, scale, and history. But legacy systems and decades-old infrastructure are slowing insurers as they navigate increasingly digital supplier relationships. External administrators, legal service providers, and managed IT vendors all depend on digital access, yet many insurers still rely on identity systems built for internal employees.

These systems were not designed for today's demands. As insurers lean more on third parties to deliver services, the inability to manage supplier access efficiently becomes a source of risk, delay, and noncompliance.

The Hidden Cost of Supplier Friction

Suppliers are critical to daily insurance operations, but their user experience is often overlooked. Onboarding can take days. Most insurers still rely on fragmented tools to manage supplier access. These include email requests, ticketing systems, and one-off provisioning scripts. The workflows are slow, inconsistent, and heavily reliant on institutional knowledge. As external relationships grow more complex, this patchwork leads to errors, delays, and blind spots in access visibility. Communication is fragmented. Manual provisioning introduces delays and errors. These bottlenecks do not just frustrate external teams. They delay policy servicing, claims handling, and tech rollouts.

Loose identity verification also opens the door to impersonation and fraud, especially when outdated processes rely on email requests and human approvals.

Inadequate Delegated Access

Insurance workflows often mean insurers must manage multiple external users or teams across various systems, be they claims adjusters, legal representatives, or IT support. If they cannot autonomously manage access rights, they are forced to rely on centralized IT intervention, creating bottlenecks and increasing the risk of human error.

Not unlike the challenge insurers face with delegated access for policyholders and their proxies, suppliers frequently operate under a hierarchy of users that need different levels of access. Without well-designed, role-based access controls, these relationships can introduce vulnerabilities and inefficiencies.

Security Vulnerabilities

The increase in third-party integrations has expanded insurers' attack surface. Poorly managed suppliers can become inadvertent conduits for cyberattacks. High-profile incidents, such as the Infosys McCamish Systems breach, highlight how external access points can be a stepping stone to compromising millions of sensitive records.

Bad actors are highly adept at exploiting fragmented identity and access management (IAM) systems, pivoting between digital portals and human-assisted channels like call centers. If a supplier's access is not continuously monitored and intelligently verified, attackers can escalate privileges or move laterally across systems unnoticed.

Regulatory Compliance Challenges

Insurance providers operate under growing regulatory mandates such as GDPR, CCPA, PIPEDA, and industry-specific compliance requirements. When suppliers interact with sensitive customer data, complexity around consent, data minimization, auditability, and breach reporting is inevitable.

When suppliers are not fully integrated into an IAM system, insurers battle to track which external users accessed what data and when, facing a lack of visibility that can endanger the business.

Operational Inefficiencies

Many insurers still rely on manual processes to create and remove supplier accounts. This increases the chance of human error and makes it harder to ensure that access is removed when a contract ends.

This mirrors a broader insurance industry challenge: outdated customer directories that aren't regularly audited or verified. Just as insurers must revisit and clean up dormant policyholder records, they must also manage the supplier identity lifecycle continuously.

How B2B IAM Addresses These Challenges

Modern B2B IAM solutions are designed to handle the scale, complexity, and operational nuance of insurance-related industries. Key capabilities include:

Federated Identity and Single Sign-On (SSO)

In the insurance sector, third-party agents, brokers, and service providers often need access to internal portals for claims processing, underwriting tools, or policy management systems. Federated identity enables these external users to authenticate using their own trusted identity providers, reducing the need for duplicated credentials and minimizing overprovisioning. Combined with single sign-on (SSO), federated identity ensures seamless and secure access while maintaining strict access controls aligned with compliance requirements.

Self-Service Onboarding and Automated Lifecycle Management

Modern B2B IAM solutions automate the entire supplier onboarding process. Self-service portals, identity proofing, and pre-configured workflows simplify access provisioning and apply consistent verification requirements to all users. Access is automatically revoked when contracts or relationships end, reducing human error and limiting risk.

Delegation

B2B IAM enables suppliers to manage their own users and access rights within strict, pre-defined boundaries through delegated user management. This model solves a key scalability problem: Insurers cannot realistically handle every external access request themselves. By allowing trusted third parties to manage their internal teams, insurers reduce operational overhead without giving up control. Governance and security policies still apply, and the process avoids the bottlenecks of central IT intervention.

Adaptive Authentication and Risk-Based Access

Advanced B2B IAM systems enforce strong, continuous authentication, including multi-factor authentication (MFA) and adaptive access based on behavioral analytics. real-time monitoring and detection of anomalies, like access from high-risk geographies or at odd times.

Fine-Grained Authorization

Most insurers rely on role-based access control (RBAC) as the foundation for managing access. It assigns permissions based on a user's function and is effective for internal teams. But in supplier ecosystems, roles alone are not enough.

As external relationships become more complex, attribute-based access control (ABAC) helps refine access using context like geography, business unit, or risk level. Even then, a key dimension remains missing: who the user represents.

Relationship-based access control (ReBAC) fills that gap. It evaluates the connection between the user and the insurer. A supplier working on behalf of Insurer A should only see data tied to that relationship, even if they have the same role and attributes as a supplier representing Insurer B.

RBAC, ABAC, and ReBAC are not competing models. Together, they provide the layered control insurers need to manage external access precisely, reduce exposure, and support growing third-party networks without added risk.

Audit Logging and Compliance Reporting

To meet regulatory standards, these solutions provide detailed audit trails, consent monitoring, and policy-enforced access controls. Every supplier activity is logged, verifiable, and auditable.

Managing Supplier Relationships Securely and Efficiently

Insurers will always depend on external partners to deliver digital services, so the challenges of supplier integration will become more complex and riskier. Whether the threat comes from dormant accounts, weak verification standards, or inefficient workflows, the consequences can be dire: data breaches, regulatory fines, and lost trust.

B2B IAM is becoming a critical capability in managing these supplier relationships securely and efficiently. It improves security and compliance while enhancing agility, UX, and operational alignment. In a digital insurance market, entities prioritizing flexible, risk-aware identity strategies will mitigate threats and set themselves apart as trusted, modern partners.

In the world of insurance and asset-heavy industries, all eyes are typically on big-ticket items — policy claims, premium collection, and operational risk. But lurking in the shadows is a low-profile, high-impact problem that's quietly draining value from balance sheets: salvage fraud.

While not as sensational as staged collisions or inflated invoices, salvage fraud is often systemic and undetected, especially in businesses that deal with high volumes of returns, damaged goods, or warranty claims.

What Is Salvage Fraud?

Salvage fraud occurs when damaged, returned, or written-off items — which still hold residual value — are misappropriated by the very people entrusted with disposing of them. These items are supposed to be sold, auctioned, or destroyed, but instead, they may be diverted, undervalued, or sold off informally for personal gain.

This isn't limited to the insurance industry. It affects:

• Retailers dealing with high-volume returns
• Manufacturers handling warranty parts
• Construction and auto industries with equipment write-offs
• Logistics firms responsible for damaged inventory

Real Example: A Car Quietly Written Off

In one investigation, our team was engaged by the head office of a major auto dealership chain. A customer had returned a vehicle twice, citing minor defects. Instead of undergoing a proper evaluation or being repaired for resale, the car found its way into the customer service department, where it was quietly written off the books.

Despite being in almost perfect condition, it disappeared from inventory without a trace — no auction, no resale, no recovery. Because it was "damaged" and outside the core business focus, no one followed up. And no value was reclaimed.

The "Destroy to Dispose" Loophole

In many industries, parts and products that are returned under warranty or recall are required to be destroyed. This is often done to prevent damaged, outdated, or brand-sensitive items from entering the resale market at a discount — something manufacturers want to avoid to protect brand integrity and pricing power.

But here's the problem: When a company expects the item to be destroyed — not sold — and has already budgeted for disposal costs, it becomes even easier for internal actors to write off the item and quietly divert it.

If no one expects revenue from a destroyed item, there's no red flag when nothing is received. That's the loophole.

The Typical Scheme

Here's how salvage fraud often plays out:

1. An item is returned or deemed unfit for regular sale.
2. A manager or staff member marks it for destruction or disposal.
3. Instead, the item is sold privately, often to a friend or contact.
4. Because no proceeds were expected anyway, no questions are asked.

Over time, this creates a low-risk, high-reward opportunity for fraud, especially when oversight is weak or nonexistent.

Why This Matters

Each case might seem minor, but over time, the cumulative losses can be substantial. Even worse, salvage fraud creates a culture of dishonesty and entitlement — and it often spreads if left unchecked.

Organizations face:

• Undocumented financial losses
• Inventory and audit discrepancies
• Reputational damage if the fraud is exposed
• Legal risk if regulatory or tax reporting is affected

How to Prevent Salvage Fraud

1. Track salvage value – Keep records even for items marked for destruction.
2. Implement clear chain-of-custody protocols – No single person should control the disposal process.
3. Audit salvage and disposal activities – Especially those showing zero revenue.
4. Use third-party disposal or auction services – With transparent records and verification.
5. Educate staff – Make clear that "damaged" or "returned" does not mean "valueless" or "free to take."

Final Thought

Salvage fraud thrives in blind spots. Whether it's a slightly damaged vehicle, a batch of electronics returned under warranty, or parts earmarked for destruction — if it has value, it carries risk.

It's time for insurers, manufacturers, and retailers to rethink how they handle salvage. Those items written off the books may be more valuable — and more vulnerable — than anyone realizes.

Fraud doesn't always wear a mask. Sometimes, it just wears a company badge and walks out the side door with a "worthless" return.

It's easy to find an insurer working on actuarial transformation. It's less easy to find one that's getting it right.

That's because moving actuarial data and the key tools of the trade to the cloud is much less a technical challenge than it is a political and organizational one, and that distinction remains surprisingly opaque among insurers.

Yes, actuarial transformation is inherently technical, involving Python, SQL, Databricks, Dataiku, and the like. But success and the business benefit it can bring depend most on human communication at both the executive and implementation-team levels.

The unique context of actuarial transformation puts a premium on communication, because differing motivations and shared turf are a recipe for friction between the actuarial and IT teams, and that friction can stall projects.

Actuaries want control over their tools, because their deep understanding of those tools' strengths and weaknesses is critical to producing precise risk models and actuarial processes. The IT team wants to control all of an insurer's IT infrastructure for a host of reasons, not least to prevent security and maintenance problems that can stem from systems that actuaries are more than capable of developing on their own.

Any major IT project needs buy-in from both IT and the business it will serve. The change management involved in fostering such acceptance is exceptionally important in actuarial transformation, because actuaries are at least as comfortable with data as the IT team, albeit with different aims.

Start at the executive level

The transformation project's executive sponsor must engage in the earliest days of an actuarial-transformation effort. This can't be an arbitrary assignment based on title or convenience. The executive sponsor must have real skin in the game tied to the transformation's success or failure and the right level of formal and informal authority within the organization. Their main role involves aligning executive peers as well as stakeholders on the actuarial and IT teams and others whose support will advance the project (or whose resistance could impede it). That happens in two ways.

First, the executive sponsor builds and presents the business case for why actuarial transformation is worth doing with messaging tailored to the top of the organization as well as to the actuarial and IT staff who will be doing the transformation work. Those messages include clarifying process changes and technology upgrades; providing estimates on the time, effort and money involved in the project; and explaining the expected benefits. Those benefits may include expected revenue increases thanks to more accurate risk assessment and pricing accuracy, higher productivity, improved actuarial creativity resulting in new products, and better positioning for future growth.

Second, the executive sponsor clearly conveys what's needed to achieve that business case. That can include the processes to be automated, the nature and timing of the implementation effort, the outside resources to be engaged, the budget and cost centers bearing it, and the KPIs against which you'll measure success. To effectively inform, persuade, and cajole peers and stakeholders, the executive sponsor must be engaged throughout preplanning, readiness assessments, and execution plans.

Next, engage with the actuarial and IT teams

The actuarial and IT teams then need special attention. Actuaries must comprehend the value of automating and codifying processes they've been doing in their heads and using custom combinations of algorithms in various data-manipulation runs. They must be convinced that the new solutions are at least as reliable as their old standbys.

IT staff involved in developing the systems enabling actuarial transformation must be comfortable with the actuarial team's processes and approaches and be able to explain the IT team's needs effectively to them. Not every developer has the combination of IT skills, business knowledge, and communication abilities required. Importantly, the chosen few should be embedded with the actuarial function, where they can interact, collaborate, and build trust.

That trust will only deepen as deliverables accrue and the actuary team sees the value of transformation. That trust building goes both ways: Actuaries should respect the IT organization's best practices related to scope definition, documentation, version control, testing, and deployment, especially as actuaries gain skills in Python, SQL querying, and other tools enabling them to develop their own cloud-based solutions.

Like so many technology initiatives, successful actuarial transformation hinges on the human element. Foremost, it takes the right executive sponsor. That person must be heavily invested in the transformation and have the formal and informal authority to make sure the work gets done and delivers the right business outcomes.

While artificial intelligence brings massive opportunities, it also introduces serious ethical and compliance risks, especially when it comes to data privacy, algorithmic bias, and cybersecurity.

According to McKinsey, generative AI alone could contribute up to $4.4 trillion in annual global profits. Studies show that AI can improve productivity by as much as 66%. In insurance, chatbots and virtual assistants are now offering 24/7 support, cutting wait times and improving customer satisfaction. Behind the scenes, algorithms are analyzing vast datasets to better assess risk and detect fraud. Claims that used to take days can now be processed in hours – sometimes even minutes – with AI-powered damage assessments and automation. Internally, insurtechs are using AI to improve onboarding, tailor employee training, and streamline HR processes.

These are powerful shifts. But they also raise tough questions. How do we ensure the data being used is handled ethically? How do we guard against discrimination in pricing or hiring algorithms? What happens when a customer is denied coverage based on an opaque machine-learning model?

These aren't theoretical concerns. According to KPMG's most recent CEO Outlook Survey, more than half of executives pointed to ethics as one of their top worries around AI. That's especially true in insurance, where fairness and transparency are essential; people's financial futures often depend on it.

That means insurtechs need to think carefully about how AI decisions are made and how they're explained. Customers deserve to know when a bot or model is involved in determining their premiums or claim payouts. Employees must understand how performance data is being tracked and used. And both groups need reassurance that their data is being protected.

Beyond ethics, there's a growing threat from cyberattacks. With AI systems increasingly integrated into core operations, the attack surface is expanding. Insurtechs handle enormous volumes of personal and financial data – prime targets for cybercriminals. The stakes are high, especially under regulations like GDPR, which carry heavy penalties for non-compliance.

So, how can companies stay ahead of both the innovation curve and the compliance curve?

One answer lies in global standards, specifically ISO 42001 and ISO 27001. ISO 42001 is a new framework designed to help organizations govern AI responsibly. It offers guidance on managing risk, ensuring transparency, preventing bias, and embedding ethical practices across the AI lifecycle. For companies building and deploying AI systems, it's a powerful tool to operationalize responsible innovation.

Meanwhile, ISO 27001 focuses on information security. It's been around longer but is just as critical – especially for insurtechs handling sensitive customer data. This standard helps organizations identify and treat information security risks, implement appropriate safeguards, and respond to incidents quickly and effectively.

Used together, these standards provide a strong foundation for AI governance and cybersecurity. But they're not plug-and-play. Each insurtech faces a unique set of risks, serves different use cases, and operates under distinct expectations. Rather than treating compliance as a checkbox exercise, the best approach is to align it with the practical needs of the business and its customers.

As AI becomes more deeply woven into the fabric of the insurance industry, the expectations around its responsible use will only increase. Regulatory scrutiny will intensify. Cyber risks will grow more sophisticated. And stakeholders – from customers to regulators to employees – will demand greater transparency, fairness, and accountability.

Insurtechs that recognize this shift and take steps now will be better positioned for long-term success. Clear governance, ethical AI practices, and alignment with international standards like ISO 42001 and ISO 27001 are no longer just best practices. They're quickly becoming competitive requirements.

People still talk about international broking as if it were a chain of tasks. Quotes come in, documents go out, placements get issued, premiums are tracked. The workflow looks neat on a dashboard. But that view hides the real substance of the work. 

What actually holds a multinational insurance program together is not the list of deliverables. It's the structure that lets those deliverables happen at all. International broking is not a service pipeline. It is a system under pressure, held together by coordination, interpretation, and rhythm. And when it's misunderstood, things don't break loudly. They slowly fall out of alignment.

The broker operates at the center of this system. Not just as a go-between but as the one who sees how each part interacts with the others. The client has expectations. The local broker has constraints. The insurer has timelines. The reinsurer has their own frame. None of them see the full picture, but the broker is meant to keep the whole thing coherent. That requires more than following process. It requires shaping a space where tension doesn't turn into friction and where deviation doesn't spiral into drift.

What makes this system fragile is not a lack of competence. It's the volume of silent stress it absorbs. Every actor is operating under pressure. The client's HQ wants clarity. The local office wants autonomy. The underwriter wants data formatted their way. Meanwhile, no one controls the whole structure. And yet they all expect it to work. This is why coordination in international broking isn't just about sending reminders. It's about sustaining a system of partial control through alignment, trust, and timing.

The hardest part isn't the volume of work. It's the fact that the system is always on the edge of losing coherence. A delay in one country causes a shift in the client's internal deadlines. A misunderstood term in one binder raises doubts across the whole program. The structure reacts. And unless someone reads those reactions in time, they compound. One quote late becomes two. One frustrated broker becomes disengaged. One unclear update becomes a signal that the broker isn't in control. And trust doesn't vanish in a crisis. It thins over time.

Tools can help track movement, but they don't create meaning. You can have a perfect table of milestones and still lose control of the system. That's because what actually drives program success is interpretive. Knowing when a silence matters. Knowing when to push and when to wait. Understanding why one office is late, not just that it is. These things aren't captured in KPIs. But they're what determines whether the program holds.

International coordination is often mistaken for middle management. In reality, it's the most exposed and structurally important role in the system. It's where tension accumulates, where ambiguity lands, and where recovery starts. When a system begins to drift, it's not the tools that correct it. It's the person who notices that the tone of updates has shifted. That someone who used to respond in one hour now takes three days. That there's no escalation, just ambient hesitation. And knowing how to restore rhythm before anything explodes.

Thinking of broking as infrastructure changes how performance is judged. It's no longer about just being fast or responsive. It's about whether the structure can absorb a shock. Whether it holds coherence after a failed claim. Whether actors remain aligned under pressure. You can only judge that by seeing how the system reacts when something goes wrong. Does the team coordinate to protect narrative, or does it collapse into blame and silence? The answer tells you more than any placement stat.

As international programs become more complex, coordination becomes less about movement and more about design. Not design in a visual sense, but in how the system is built to bear weight. Do timelines match the actual capacity of the people involved? Are updates structured so different actors interpret them the same way? Is there a shared sense of how long silence is acceptable before intervention? These are structural questions. And if they're not answered in advance, they get answered in crisis.

The broker's role is not just to respond to requests. It is to hold the shape of the program while it moves through pressure. That includes building relationships that absorb short-term failure. That includes managing time not just in days but in signals. And that includes preserving a narrative that makes the program make sense to all sides. Because when that narrative is lost, even efficient delivery feels random. And when it feels random, the client starts asking questions they used to trust you to handle.

What international broking needs is not more dashboards. It needs a clearer understanding of what holds the system together. And it's not speed or volume. It's coherence. The broker is not just a deliverer of coverage. They are the person responsible for keeping a structure alive. And when that role is taken seriously, the system starts to respond differently. People work with you, not around you. Delays become manageable. Tension becomes signal, not threat.

This is not a romantic view. It's the practical reality of running complex programs across jurisdictions, languages, legal codes, and internal client politics. The work doesn't fail loudly. It frays. And the only way to keep it together is to see the job for what it really is. Strategic control through structural care. Quiet pressure management. And design in motion.

Digital claims, AI-assisted underwriting, and automation in policy administration are all top-of-mind when it comes to insurance innovation. But there is one function that remains under the radar but underpins the entire insurance lifecycle: payments. Payments are a core function of insurers, but many are dealing with outdated, rigid payment systems that are not only clunky but a liability.

According to the National Association of Insurance Commissioners (NAIC), direct premiums written (DPW) in the P&C sector climbed to $529 billion in 2024, an 11% increase over the previous year. That growth is tremendous, but many carriers are not equipped to efficiently handle the sheer volume and complexity of financial transactions that come with it. Legacy payment infrastructure, much of it designed for a paper-based world, is cracking under the pressure.

Where Payments Fall Short

The traditional P&C payment setup is riddled with gaps. Premium collections are siloed from claims disbursements. Reconciliation happens manually. Adding payment vendors takes months, and compliance tracking is often an afterthought. This is leaving customers wondering why a refund or claim payment takes a week when Venmo can move money instantly.

These inefficiencies are costing insurers more than operational overhead. They are damaging customer trust at the worst possible moments, like after a car accident or natural disaster, when policyholders expect fast, seamless payouts. If a delay or mix-up happens during that crucial window, no amount of customer service and marketing will win that customer back.

Even worse, regulatory pressure is mounting. Payment compliance is not optional, and falling short, whether on timing, transparency, or data handling, can invite fines or audits. Old systems were not built with today's rules and expectations in mind.

From Back Office to Brand Differentiator

Once relegated to the back office, payment systems are now becoming a critical differentiator. Customer experience is no longer just about how quickly a claim is approved, or a policy is bound; it is about exceeding customer expectations across the entire insurance journey. To ensure these expectations are met, how payments are distributed is key.

Today's consumers live in an instant payout society and expect immediacy, transparency, and choice that brands like Amazon, Uber, and Apple provide. The same is true for the insurance industry. Consumers want to pay premiums how and when they want and receive claims payments just as easily. If that is not possible, they will find an insurer that can meet their expectations.

For forward-thinking insurers, that shift presents an opportunity. The same infrastructure overhaul that improves operational efficiency can also unlock brand differentiation. Real-time payment capabilities, digital wallet integration, automated reconciliation, and compliance built-in from the start are not just technical upgrades, they are critical competitive advantages.

What Modernization Looks Like

Payment modernization is not about ripping everything out and starting over. It's about building an ecosystem that is flexible, scalable, and connected. Insurers need to deploy payment orchestration platforms that plug into existing core systems while unlocking powerful new capabilities. Here are some of the benefits when payments and core systems seamlessly work together:

• Instant collections and disbursements – Customers can pay premiums using any major method (credit card, ACH, digital wallet) and receive payouts the same way, often in minutes rather than days.
• End-to-end visibility – Finance teams can track every dollar, from initiation to settlement, across billing and claims.
• Faster integration with vendors – What once took 12 months now takes two weeks. That means insurers can add or switch payment providers without stalling operations.
• Automated compliance – Built-in tools ensure payments meet state and federal regulations, with full audit trails and reporting.
• Automated workflows – Errors and bottlenecks from using paper-based, manual processes can be eliminated.

Insurers that have adopted modern payment infrastructure are not only more agile but are saving millions annually in processing costs, reducing call center volume, and scoring higher in customer satisfaction.

Real Risks of Maintaining the Status Quo

The risks of not modernizing are growing by the day. As more insurtechs enter the space with fully digitized platforms, the gap between modern and traditional carriers will only widen. And while legacy players may still hold customer trust and market share today, their lack of payment flexibility and immediacy will test that trust. Every delay, every friction point in the payment process erodes confidence. And in an industry built on trust, that can be costly.

Payment technology is evolving quickly, including initiatives such as embedded finance and real-time rails. Insurers that are not already modernizing may soon find themselves too far behind to catch up. This is especially true as regulators increase scrutiny and potential monetary fines over digital payment compliance and transparency.

Building a Future-Ready Foundation

Modernizing payments is not just about fixing what is broken. It is about building for future considerations. Payments touch every aspect of an insurer's operation. By improving how money moves, insurers can accelerate product launches, personalize billing strategies, streamline claims, and gain deeper financial insight across the enterprise.

For carriers looking to lead, and not just survive, payments is the place to differentiate and digitally transform. Because if one insurer cannot pay quickly, securely, and conveniently, another will.

Recent articles by a Wall Street Journal reporter and by a highly regarded veteran journalist suggest that generative AI could render management consulting firms obsolete. The headline in the WSJ begins, "AI Is Coming for the Consultants," and refers to an "existential" threat to McKinsey. The headline's dek reads: "If AI can analyze information, crunch data and deliver a slick PowerPoint deck within seconds, how does the biggest name in consulting stay relevant?"

But let's not get carried away just yet. 

From my perspective both as a long-time follower of technology and of insurance and as a former partner in a 2,000-person management consulting firm, gen AI will require adapting the business model for consultants and, perhaps a bit later, insurers. But gen AI will actually accentuate the value of the sharpest consultants and the best underwriters, claims professionals, and agents and brokers — not put them out of business. 

As a way of sorting through the hype and the reality surrounding generative AI, I thought it would be worth taking a look at what's really likely to happen.

Here are the two articles: the WSJ piece and one written for the Free Press by veteran business reporter Joe Nocera. The text of the WSJ article isn't as alarmist as the headline but still makes the case that gen AI can produce presentations as slick as a consultant can, so who needs human consultants? Nocera, scarred from his experience as an employee at Time Warner during the disastrous, consultant-heavy takeover by AOL, makes much the same argument, and rather gleefully. The headline of his piece reads: "The Consulting Crash Is Coming: Bloated, overpaid, and outpaced by AI—big firms confront a future they can’t outsource."

I see two major problems with the thesis, neither of which undercuts the power of gen AI but which suggest tempering expectations at least about how quickly gen AI will take over the world. Both issues also apply in insurance.

First, the articles get caught up in the glitz of AI and ignore a question that gets ignored all too often: What if the AI is wrong? 

Yes, an AI can do a remarkable amount of analysis quickly and can turn it into a slick PowerPoint presentation with breathtaking speed, leaving the usual army of 20-something MBAs way behind. But what if the analysis is wrong? 

I see this sort of assumption of AI-as-oracle all the time. But in a lot of cases, it isn't even possible to know whether the AI will be right. It can't know for sure how competitors will react to a new strategy by a client. It can't know for sure whether predictions about morality for life insurers will be accurate, not for years or even decades.

Sure, those armies of MBAs make mistakes, too—plenty of mistakes, including some big ones—and the AI will keep learning and improving over time. But the AI will have to earn its stripes just as consulting firms have over time, so we can't just assume the speed of AI will win the day.

Second, the articles gloss over the value of the seasoned, senior consultants and miss how those senior consultants—like their counterparts among underwriters, claims professionals, and agents and brokers—became so valuable.

Much of the value comes from the sort of behind-closed-doors interactions that an AI simply doesn't have access to, even as it scans terabytes of public information. With management consulting, the issue isn't just about producing the right strategy. It's about assembling the right team to implement it. Senior consultants get good at reading the room based on decades of experience across companies and across industries and help CEOs make often-radical changes in their leadership teams during a major pivot.

There is also an issue of comfort level. Consultants become valuable not just because they're smart but because they're trusted, based on years of successful interactions with a particular client, sometimes on a personal level. 

Yes, the comfort issue can lead to unseemly fawning. I vividly remember sitting at a bar at Pebble Beach after a day of golf as a Fortune 500 CEO client ordered rounds of different grappas for a few of us and explained their nuances. I nodded along and carefully sipped each shot, even though I hate grappa. It smells like nail polish remover to me.

The need for comfort can also, as both the WSJ and Nocera noted, lead to CEOs hiring major consulting firms for huge fees just to ratify decisions they would have made anyway. (At my firm, Diamond Management & Technology Consultants, acquired by PwC in 2010, we griped that McKinsey got most of that business, while we, as a far smaller brand, had our noses pressed against the window, watching with envy.)

But management teams do need support as they make decisions that risk the company's future—and their own careers—and experienced consultants at firms with long histories can provide that support in a way that an AI cannot.

Deeply experienced human underwriters, claims professionals, and agents and brokers provide the same sorts of emotional intelligence and comfort/support to those they serve, as well, making a lot of their work safe from gen AI.

All that said, gen AI will require changes to consulting firms' business model. The firms don't just make gobs of money for their partners by charging such hefty fees for their time. The firms are built as pyramids, with thousands of young MBAs at the lower tiers being billed at rates far above their salaries—the excess going to the partners. But much of the work done at the lower levels, including those slick PowerPoints highlighted in the WSJ headline, can, in fact, be automated by AI. A big chunk of revenue will disappear. 

I say good riddance to a lot of that work. I remember teams at Diamond staying up all night because, as members combined their work, they found that fonts didn't match or that someone had messed up the page numbers, and they had to get everything perfect for the presentation first thing in the morning. Who needs to pay a bunch of 20-somethings $1,000 an hour to fix formatting when an AI could do the work in seconds and let them get some much-deserved sleep?

But the thinning out of lower ranks doesn't just take away revenue. It takes away talent, too—an issue for insurers, as well. If you don't need so much research done by the lower tiers in a firm, you don't need as many people, and you don't have as much talent fighting its way up the pyramid in the up-or-out culture of a consulting firm. Those who make it will still be impressive, but what have you lost? 

The same goes for insurers. What do you lose among your senior underwriters, claims professionals, and agents and brokers in a decade if gen AI means you're drawing from a smaller base?

I remain a huge fan of the potential of gen AI, and I could tell you loads of stories mocking consultants and their firms, but I think the glee about the supposed comeuppance for consulting firms is overdone. They, like key players in insurance, will have to adapt plenty, but I predict they'll be as influential as ever. 

Cheers,

Paul

An effective strategy to optimize the work experience and satisfaction for insurance customer service agents focuses on two factors. Incorporating employee assistance technologies, like agentic AI and large language models (LLMs) into workflows, while also placing a greater emphasis on workplace culture and support, can help decrease burnout and raise retention.

Increasing employee feelings of fulfillment is good business. This approach not only helps the individual, but it also can elevate overall staff satisfaction. Customer service representatives who feel supported by both assistive technologies and management will be happier, which can improve satisfaction and long-term retention of customers.

Insurance customer service representatives experience multiple challenges. They are expected to be patient, professional, and resourceful, finding relevant answers for a wide range of customer issues in real time. Also, they must navigate complex and ever-changing insurance regulations.

Technology to the Rescue

AI and LLMs can help with this multitasking. Gone are the days when the only choice was a pre-scripted chatbot that provided callers with limited options, such as operating hours or directions, before switching them to a representative. LLMs can now handle these basic inquiries as well as assist customers with other issues using natural language processing, delivering a more personalized, context-aware solution.

These technologies allow customer service representatives to focus more time on human factors like empathy. Agents are front-line workers who help customers during times of need, such as after a death in the family, a motor vehicle accident, job loss, or other major life event. The most skilled agents use emotional intelligence to connect on a human level during these times. Simultaneously, representatives need to get their jobs done with accuracy, compliance, and speed.

When AI is implemented seamlessly, it also can alleviate other customer representative pain points. For example, AI can automatically find and analyze policy data relevant to each customer in real time, sparing a representative from jumping tabs or putting a client on hold while they search. AI augmentation can make agents' workloads more manageable and allow them to perform their jobs with greater confidence.

Technology can also ease the burden of tasks that require multiple steps. For example, automating insurance claims management can save both time and frustration when employees skip manual tasks like verifying details, checking policy limits, updating records, and sending communications.

Burnout Is Common

The technology solutions could be coming just in time. Recent research from Liberty Mutual and Safeco Insurance found that more than half of frontline agents at independent insurers are struggling with stress and burnout. The same report found:

• 65% of staff often feel stressed at work
• 57% say they feel mentally and physically exhausted
• 51% report feeling burned out
• 39% of agency staff have considered leaving their jobs

The study also revealed that employees at agencies with more digital tools report lower levels of burnout.

If left unaddressed, burnout can lead to reduced productivity, more frequent absences, and increased employee turnover. These outcomes in turn degrade customer service quality. For insurance companies, the consequences may include not just the loss of skilled staff but also potential damage to the brand's reputation.

Company Culture Must Be Improved

Insurance companies that cultivate a culture of empathy and psychological safety create a work environment where employees feel supported to do the best job possible. There is a direct relationship between engagement and customer service representative burnout, according to a study of nearly 400 representatives working in a roadside assistance call center.

Workforce management technologies can also reduce stress and prevent burnout. By anticipating peak demands and noting emotional signals, these platforms make sure agents are neither overwhelmed nor underused, which also supports greater job satisfaction.

AI and LLMs are rapidly evolving. They are accelerating a transition of agents facing high-volume, repetitive labor to a role focused on delivering genuine human connection, an essential factor in enhancing job satisfaction and employee retention. Organizations that understand the growing potential for these technologies to assist customer service representatives benefit from greater efficiency, happier employees with greater resilience against burnout, and increased customer loyalty over the long run.

Insurers that invest in LLM- and AI-augmented agent support systems will be best positioned to reduce burnout, improve employee retention, and maintain service excellence over the long term.

Running an independent insurance agency without the right technology can feel like an uphill battle. You're constantly pulled in different directions: chasing down quotes, managing multiple carriers, handling policy changes, and trying to keep up with client demands. Every day brings new fires to put out, and without the right tools, even the simplest tasks can eat up valuable time. In a fast-paced market, doing everything manually just isn't sustainable.

The old way of working limits your capacity and makes it harder to deliver the kind of service your clients expect. The good news is that modern insurance technology is changing that and can help you stay ahead.

Here are three areas where the right tech can make a real difference in running your agency.

Digital Payments That Streamline Collections and Enhance Security

According to McKinsey, nearly nine out of 10 consumers now use some form of digital payment. So why should paying for insurance be any different?

Today's insurance agencies have a prime opportunity to modernize payment collection. By offering secure digital payment options via ACH, credit, or debit card that seamlessly integrate with your agency management system, you can significantly reduce the time your team spends manually double-checking collections and reconciliations.

But the benefits don't stop at the back office. Clients also enjoy a smoother experience. With 24/7 access from any device, they can pay whenever it's convenient—no waiting on office hours or worrying about late payments. Instant confirmations provide peace of mind, so they always know where their policy stands.

With built-in security features, digital payments also help protect both your agency and your clients' sensitive information, reducing the risk of fraud and potential liability. It's a simple upgrade that delivers a meaningful impact on your operations and your customer experience.

Smarter Renewals That Save Time—and Clients

With competing renewal deadlines across multiple clients, it's easy to fall behind. If you don't reach out with enough lead time before a policy expires, you risk missing the renewal altogether. That not only reflects poorly on your agency, it can also lead to lost business.

Having a solid handle on renewals is essential, and fortunately, technology is making it easier than ever to manage the process. Modern agency management systems can automatically track your clients' policy expiration dates and send you alerts when renewals are approaching, ensuring you never miss a critical deadline and allowing you to plan your outreach strategically.

Some tools go even further by pulling updated carrier rates directly into the system, empowering you to offer better options to your clients before they start shopping around on their own. Not only does this protect your book of business, but it also turns renewals into valuable opportunities to showcase your commitment and expertise.

Real-Time Reporting That Helps You Make Better Decisions

Analytics-driven organizations are 23 times more likely to acquire customers, six times more likely to retain them, and 19 times more likely to be profitable. When you're running a business, static spreadsheets aren't enough—you need actionable insights.

Real-time data and reporting tools provide a clear view of your agency's performance, tracking everything from new business and retention rates to client growth and commissions. Intuitive dashboards simplify complex data, helping you spot trends, identify potential issues early, and focus on what's working best.

Some platforms even let you benchmark your results against similar agencies so you can see exactly where you stand and uncover opportunities for improvement. The bottom line is: When you understand your numbers, you can make smarter decisions that drive meaningful growth.

The Smarter Path to Agency Success

The insurance landscape is evolving faster than ever, and adapting to these changes means rethinking how your agency operates.

You don't have to handle everything on your own. The technology is here—and it's designed to simplify your operations and maximize your impact. That means less time spent on manual tasks and more time focused on strengthening client relationships and growing your book of business.