The insurance industry is undergoing massive disruption. Profits have declined, risks have mushroomed, and nimble new competitors have emerged. For insurers to not just survive but thrive in 2024 and beyond, shrewdly managing risks is absolutely essential.
In my decade as a data scientist advising top insurers, I‘ve witnessed firsthand the forces buffeting this sector. Here I‘ll share 5 proven yet forward-looking risk management strategies insurers must embrace now to future-proof their organizations.
1. Harness the Power of Data with Advanced Analytics
Data is the rocket fuel that will propel insurance into the future. Insurers already sit on mountains of data about customers, policies, claims, providers, risk conditions, and more. The winning insurers will be those who can best harness this data through advanced analytics.
Sophisticated analytical models allow insurers to find insights buried within massive, messy datasets. This powers improvements across the value chain:
Risk Assessment
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Predictive models can forecast losses and required reserves with far greater accuracy than traditional actuarial methods. Machine learning algorithms can find subtle patterns and correlations between millions of data points that even the sharpest human actuaries would overlook. This allows tighter risk analysis.
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For example, by analyzing terabytes of IoT telematics data, insurers can identify the riskiest 1% of drivers responsible for 10% of losses. Special underwriting models can be developed for such subsets.
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Image recognition algorithms trained on millions of photos can be used to automatically assess property risk categories from images, reducing manual effort.
Pricing
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Granular geo-spatial analysis can allow hyperlocal pricing tuned to conditions in a specific zip code. Factors like climate risk, crime rate and traffic congestion can be modeled at the neighborhood level.
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Similarly, algorithms can auto-score individuals based on thousands of data points and create highly customized premium rates. This balances risk and revenue far better than grouping people into coarse pricing segments.
Underwriting
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Near-instantaneous quoting and binding can be achieved by having analytical models interface with customer and risk data APIs in real-time.
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Documents like medical reports can be ingested via OCR and fed into automated underwriting systems. Natural Language Processing can also extract insights from raw text and notes.
Claims Processing
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Image recognition and natural language processing help extract key data points from photos, estimates, police reports and adjuster notes, speeding assessment.
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Network analysis can detect suspicious links between multiple claims that point to fraud. This allows more rigorous investigation of potentially fraudulent activity.
Customer Experience
- Sentiment analysis tools can parse call center transcripts, social media posts and reviews to identify pain points and monitor how satisfied customers feel with experiences. This guides improvement efforts.
The most analytically mature insurers are assembling cross-functional data teams combining data engineers, data scientists, actuaries and business translation specialists. Together they build the models and systems that enhance capabilities and drive measurable business results.
Many insurers also work with analytics vendors and insurtech partners who can accelerate their data journeys. But having in-house analytics firepower is key to absorb external innovations.
Those who neglect advanced analytics risk making decisions in the dark while competitors use data to unlock hidden insights and operate with far greater precision.
High impact analytical focus areas for insurers include:
- Claims fraud detection
- Customer lifetime value modeling
- Risk pooling and selection optimization
- Automated underwriting systems
- Hyperlocal pricing algorithms
- Predictive loss forecasting
- Customer experience analytics
- Product propensity modeling
Data analytics is key to unlocking hidden insights from vast siloes of insurer data
2. Adopt the Internet of Things for Deeper Risk Insights
The Internet of Things – a vast mesh of connected sensors, devices and equipment – is transforming insurance. IoT provides a real-time stream of behavioral data that can substantially sharpen risk assessment, underwriting, pricing and loss mitigation.
Consider how sensors and telemetry are being incorporated across the value chain:
Auto Insurance
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In-car telematics track real driving behavior – speed, acceleration, braking, turning, mileage, and more. This allows highly customized usage-based insurance pricing and underwriting. Safest drivers enjoy lower premiums while risky driving can incur surcharges.
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Smartphone apps can also track driving behavior and be used for insurance scoring. External data on traffic and road conditions provides additional context.
Home/Property Insurance
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Smart home sensors monitor activity and conditions to prevent losses. Water and smoke detectors along with security systems allow early alerts to minimize damage and dispatch assistance immediately. Some insurers even provide policy discounts for smart home tech.
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Drones with cameras can be used to inspect roofs and other hard-to-reach areas during underwriting and claims adjustment. This reduces manual effort and boosts accuracy.
Life/Health Insurance
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Wearables that monitor wellness stats like activity, sleep and heart rate allow insurers to incorporate real-time health behaviors into underwriting and pricing, with customer consent. Qualifying behaviors can trigger rewards or premium discounts.
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Medical devices can transmit patient recovery data after procedures or hospitalization to alert care managers about any complications. This improves health outcomes.
Supply Chain / Cargo Insurance
- Sensors that track temperature, humidity, light exposure and vibration can help monitor cargo conditions throughout transit to avoid losses. GPS tracking provides location data to optimize routes and response time in case of any incidents enroute.
As more ‘things‘ get connected, the IoT data universe will grow exponentially. Insurers must cherry pick the highest value-add use cases for their business and customers. This requires thinking creatively about how emerging data streams can be leveraged.
Many insurtechs are also devising innovative IoT solutions tailored to insurance. Partnering with them can help incumbent insurers quickly prototypes and scale the most promising IoT models.
While the IoT holds great promise, insurers must also invest in data security and privacy controls to keep sensitive data safe. Still, used properly, IoT can give insurers an unprecedented real-time barometer into risk and behavior. This data edge will be a key competitive differentiator going forward.
3. Forge Strategic Partnerships to Accelerate Innovation
Insurance is an industry with high barriers to entry, dominated by massive legacy players. Yet disruption is now the norm. Agile insurtechs are reinventing every part of insurance with the latest digital capabilities.
Many incumbent insurers recognize the existential need to innovate yet lack the skills and agility to transform quickly enough. This is where strategic partnerships come into play.
Teaming up with insurtechs and other innovative tech companies allows insurers to quickly assimilate cutting edge solutions. Some models for insurer-insurtech collaboration include:
Licensing Software as a Service: Insurers can license ready-to-deploy insurtech applications on a pay-per-use cloud subscription model. This offers low risk and quick time-to-value.
Co-Developing Products: Joint product development sessions where insurtechs translate ideas into real solutions tailored for an incumbent‘s needs. This lets insurers rapidly prototype innovations.
Incubator Programs: Insurers provide funding and support to incubate early stage startups with disruptive concepts. This seeds future partnerships.
Venture Investment: Many insurers are active strategic venture investors, taking minority stakes in emerging insurtechs with an eye on future relationships.
M&A: Once innovators gain traction, insurers often acquire them outright to quickly assimilate game changing capabilities.
Partnerships also increasingly go beyond insurtechs, tapping Big Tech‘s prowess in AI, cloud computing, IoT and more:
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Amazon supplies cloud infrastructure for many insurers to run advanced analytics models faster and cheaper.
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Google provides TensorFlow, its enterprise AI platform, to insurers to accelerate development of smart algorithms.
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Microsoft supplies tools like Azure Cognitive Services that enable insurers to quickly incorporate APIs for image recognition, language processing and more.
The most successful insurers will build open ecosystems incorporating solutions from multiple best-of-breed tech partners. They will also align their organizations to seamlessly integrate these innovations.
Those who cling to old ways risk losing relevance. Partnering amplifies strengths and plugs capability gaps far faster than going it alone.
4. Offer Parametric Insurance to Unlock New Opportunities
Most insurance compensates the actual losses sustained by the policyholder. Parametric insurance, on the other hand, pays claims based on a triggering event hitting predefined parameters. This unlocks major benefits:
1. Rapid Payouts
Claims are automatically triggered when the criteria are met. For instance, a hurricane policy may pay if wind speeds hit a designated threshold. This pre-agreed payout structure eliminates lengthy claims investigations and adjustments, speeding funds to victims.
2. Lower Costs
With no claims teams needed to adjudicate losses, parametric policies save substantial administrative costs. They also limit unpredictable payouts since parameters cap the insurer‘s maximum exposure.
3. Wider Coverage
Triggers can be designed around unorthodox perils like tourism revenue shortfalls. This expands options for customers previously unable to buy coverage.
4. New Markets
Parametric insurance can be the solution for geographies where traditional insurance is impractical, like remote rural regions. Payments get triggered by data feeds, no field visits needed.
While parametric insurance is still an emerging niche, its problem-solving potential for complex risk scenarios makes it extremely promising. Consider these real world use cases:
Natural Catastrophe Coverage
- Policies that pay farmers if rainfall or crop yields in their county drop below set parameters.
Event Cancellation Insurance
- Coverage that pays venues or event organizers if a key datapoint like local hotel bookings falls below a threshold due to event cancellation.
Disaster Recovery Funding
- Parametric sovereign risk coverage that pays countries rapidly if a hurricane or earthquake reaches a certain severity useful for funding urgent recovery efforts.
Trade Credit Insurance
- Policies that make payments to exporters or importers based on triggering events like major currency devaluations or commodity price collapses.
In addition to paying claims quickly, the transparency and certainty of payout parameters makes parametric insurance easier for insurers to hedge their own risks through reinsurance and cat bonds.
Parametric insurance unlocks new pathways to serve clients and communities. Insurers should creatively explore opportunities where it aligns with customer needs. The Internet of Things makes this even more viable through connected sensors that supply the data to trigger payouts.
Parametric insurance allows automated triggering of claims based on pre-set data parameters.
5. Reimagine Distribution for the Digital Age
The traditional model of selling insurance through agents and brokers remains invaluable for many customers. However, accelerating technology and changing consumer preferences demand that insurers make their distribution far more digitally agile.
This means meeting customers how they want to research, purchase and manage insurance. Key trends include:
Omnichannel Customer Engagement
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Allowing customers to interact across the channels they prefer – online, mobile, contact center, in-person, etc.
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Information seamlessly flows across touchpoints, eliminating the need to repeat details.
Digital Self-Service
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Enabling customers to quote, purchase, make payments, file claims and access policies through digital self-service. Chatbots support common queries.
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This allows round-the-clock sales and servicing without call center costs.
Insurance Marketplaces
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Offering products through third-party platform stores like auto dealers, travel aggregators and financial services marketplaces.
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These embedded channels simplify purchases and expand reach.
Personalized Micro-Targeting
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Using predictive analytics to estimate individual risks and preferences. This allows tailored offers and content.
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For instance, targeted ads and emails for add-on coverage to customers likely needing it.
Pay-per-Use Models
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Usage-based insurance allows pay-as-you-go pricing based on actual utilization – like pay-per-mile auto policies.
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Parametric insurance is also a form of customized pay-per-use model.
Digitally native customers demand buying insurance as easily as hailing a rideshare. Insurers must adapt across the customer journey:
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Product Development: Devise modular, platform-enabled products that allow nimble bundling and selling through diverse channels
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Lead Generation: Use programmatic advertising, social media listening, and analytics-driven targeting to reach high-potential segments
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Sales: Support omni-channel quote-to-bind journeys blending human advisors and digital self-service
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Servicing: Engage policyholders through their channel of choice – app, email, chatbot, agent
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Renewals: Rigorously value each customer to focus retention efforts on those warranting the effort
While leveraging digital capabilities, the human touch remains vital for both customers and sales agents. Therefore, insurers must take an and approach – digital AND human.
The future remains bright for insurers bold enough to reimagine processes and embrace the fluidity customers demand today.