With record-high inflation, climate change, and an economic downturn on the horizon, the insurance industry is in a pressure cooker of unpredictable change. Sometimes this change happens over time. Sometimes it seems to happen all at once.
To come out on top, insurance companies need new workflow and operations strategies that leverage process automation to streamline processes, reduce errors, and improve the customer experience.
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Insurance workflow automation: 5 best practices.
Let’s explore five ways for insurers to get the most out of workflow automation:
- Standardize and automate data workflows.
- Implement real-time pricing models.
- Utilize analytics and machine learning to improve risk assessment and pricing accuracy.
- Embrace agile methodologies to accelerate innovation and adapt to changing market conditions.
- Leverage process mining to improve compliance and reduce operational costs
1. Standardize and automate data workflows.
Using manual data management to keep up with change is a significant challenge for insurance companies. This approach is both time-consuming and error-prone. Insurers must navigate complex data collection processes involving multiple stakeholders, including agents, underwriters, and claims adjusters, often using disparate, disconnected systems. This can lead to inefficiencies, inaccuracies, and delays that frustrate customers and increase operational costs. Additionally, manual data management can limit an insurer’s ability to gain insight into customer behavior and market trends, putting them at a disadvantage in a competitive landscape.
To overcome these challenges, insurance companies are embracing automation to streamline data acquisition and management. Automating insurance includes using
a data fabric architecture to unify data from multiple systems (CRMs or systems for policy admin, claims, billing, accounting, etc.) to enable secure, easy access to enterprise data and deliver a 360-degree view of business and customer interactions. Taking a data fabric approach can dramatically accelerate application development, simplify system integrations, and empower more users to securely build new digital solutions to keep up with the speed of change.
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Insurers are also leaning on machine learning algorithms to extract data from documents and automate decision making, reducing the risk of error and improving accuracy. And with the mainstreaming of artificial intelligence (AI), insurers are also leveraging AI to more quickly process claims data and unlock next-level operational efficiency that can generate 99.7% customer satisfaction levels.
2. Implement real-time pricing models.
Real-time pricing models are catching on in the insurance industry, offering several benefits to companies that adopt them. For example, by leveraging real-time data on customer behavior and market trends, insurers can more accurately assess risk and adjust pricing. This contributes to a more personalized customer experience by enabling insurers to tailor coverage options to fit customer expectations and stay competitive in a crowded marketplace.
It’s also worth noting the rapid rise of telematics (data gathering) technology in the insurance industry. In fact, the global telematics market is experiencing double-digit growth in insurance and will hit the $3.96 billion mark by 2026, up from $2.7 billion in 2020. Top insurers are using telematics to track customer behavior, enabling them to offer personalized pricing based on individual risk factors.
Here’s something else worth considering: Real-time pricing models are allowing some insurers to rapidly expand their customer base and attract new investors, demonstrating the value of data-driven pricing strategies. With the advantage of real-time pricing models, leading insurers can meet the fast-evolving needs of customers in a dynamic industry.
3. Use analytics and machine learning to improve risk assessment and pricing accuracy.
Insurance fraud is a massive problem that’s costing life and property and casualty insurance companies alone over $119 billion per year. Beyond that, insurance fraud erodes profit margins and drives up premiums for customers. But data is a powerful tool in the fight against insurance fraud. With digital fraud detection solutions, insurers can leverage AI and advanced case management capabilities to streamline fraud detection and prevention. Furthermore,. By connecting advanced fraud detection solutions with existing legacy systems, insurers can better manage data from all sources, including claims systems, watch lists, third parties, and external database or fraud services.
4. Embrace agile methodologies to accelerate innovation and adapt to changing market conditions.
Agile methodologies offer a flexible and iterative approach to insurance workflow automation that is particularly well suited to the complex and ever-changing nature of the insurance industry. Rather than relying on a rigid, step-by-step process, agile methodologies emphasize flexibility and collaboration, enabling insurers to rapidly develop and test new product offerings and refine their operations based on customer feedback and market trends. This can help insurers outmaneuver the competition and supercharge their operations by rapidly adapting to changing market conditions.
In today’s unpredictable market, having the ability to quickly innovate and adapt is essential to success. Agile methodologies allow insurers to rapidly develop and launch new products and services, test new ideas, and quickly pivot based on customer and market trends. Agile methodologies also contribute to a culture of innovation and collaboration within insurance companies.
By emphasizing the importance of teamwork, communication, and collaboration, agile methodologies can break down silos and enable cross-functional teams to collaborate on achieving common goals, leading to better outcomes for both customers and insurers. Agile methodologies are essential to insurance workflow automation, providing insurers with the flexibility and adaptability to turn change into profit.
5. Leverage process mining to improve compliance and reduce operational costs.
Across the insurance value chain, conditions are changing faster than ever before. To stay competitive, insurers need the speed to run fast and the agility to turn on a dime to meet changing customer expectations, reduce risk and increase compliance. For insurers, gaining real-time visibility into critical processes across the value chain is essential. That’s where process mining can help.
For example, instead of relying on reports and dashboards to optimize workflows, process mining can give insurers a more detailed view of how claims management and underwriting processes are working from start to finish, and uncover opportunities to automate workflows, improve compliance and reduce operational operational costs.
Insurance workflow automation takeaways.
The rules of the road laid out in this blog can serve as a quick-start guide for insurance workflow automation. To recap, the rules include:
- Standardize and automate data acquisition and management processes.
- Implement real-time pricing models.
- Utilize analytics and machine learning to improve risk assessment and pricing accuracy.
- Embrace agile methodologies to accelerate innovation and adapt to changing market conditions.
- Leverage process mining to improve compliance and reduce operational costs.
By following these best practices, insurers can get ahead of change and be better prepared for the future. The key is to connect automation strategies with business goals to turn change into profit. That means finding a solution that offers quick integration of disparate data sources and a low-code approach that works with legacy systems, so there’s no need to rip and replace your existing systems of record.
Learn more about insurance workflow automation.
