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This is a summary of an episode of Pioneers, an educational podcast on AI led by our founder. Join 2,000+ business leaders and AI enthusiasts and be the first to know when new episodes go live. Subscribe to our newsletter here.
TLDR:
- High-volume, low-complexity insurance tasks like data entry are prime areas for intelligent process automation using AI to free up human employees for more complex analysis and customer interactions.
- Having transparent, explainable AI systems that humans can audit and provide feedback on is critical for building trust and improving models over time.
- Calculating realistic ROI by factoring in not just technology costs but also ongoing human costs to maintain and enhance AI systems over time is essential for making a business case.
- Successful AI adoption requires careful change management - redefining roles and setting expectations rather than just cutting headcount. Involving process experts early in designing AI workflows is key.
- AI can monitor complex claims processing for anomalies and escalate them to skilled human adjusters, maximizing the strengths of both humans and machines.
Before we dive into the key takeaways from this episode, be sure to catch the full episode here:
Meet Meredith — An Insurance Veteran
Meredith's career in insurance spans an impressive four decades, with 33 years spent at Liberty Mutual and now a partner at ReSourcePro Consulting.
Her journey has taken her across various roles, from claims and underwriting to product management and technology. A significant portion of her career was dedicated to the business side of technology, giving her a unique perspective on the intersection of insurance intelligent automation and innovation.
Meredith's pivotal moment came when she recognized the untapped potential of insurance automation.
She saw an opportunity to streamline high-volume, low-complexity repetitive tasks, freeing up human talent to focus on more complex insurance processes like analysis and customer interactions. This realization led her to explore innovative solutions and advocate for change within the industry.
The Intelligent Automation Journey
One of the key insights from our conversation was the immense potential for intelligent automation in insurance.
As Meredith points out, the insurance industry is overflowing with high-volume, low-complexity tasks that are prime candidates for automation.
By leveraging AI and machine learning, insurers can streamline these manual processes, freeing up their human workforce to focus on more complex analysis and high-touch customer satisfaction, interactions, as well as customer relationship management.
Our founder, Ankur Patel, agreed and shared his thoughts on how smart it is to focus on one high-volume part of a role and give human employees more time to focus on complex tasks.
As Meredith also pointed out, the industry is at varying stages of this automation journey, with many opportunities yet to be fully realized.
Ankur went on to exemplify why everyone should look into automation:“[It’s like] using a calculator versus doing long-form math on paper; if you don’t need to do it and it saves time, why do it the old way if some of the newer ways are going to add value…” - Ankur Patel
Intelligent Document Processing: The Game Changer
A standout application of AI in insurance automation is Intelligent Document Processing (IDP).
Powered by natural language processing and machine learning, IDP solutions have made significant strides in recent years. They enable insurers to automatically extract data from the diverse documents they handle, from policies to claims processing forms and medical reports.
After the insurance industry started digitizing inbound paper, there was still a lot of human labor required to get the digital documents to the right person for the right:
- Claim
- Policy
- Invoice
Meredith mentions how this problem was solved with the help of high powers of generative AI, where solutions help truly digitize papers without requiring a lot of human resources.
As Meredith highlighted, IDP can revolutionize the intake process, reduce manual processes like data entry, and significantly improve accuracy. As the technology continues to mature, it's capable of becoming an indispensable tool in the insurer's arsenal.
Intelligent Automation in Insurance Helps Address the Talent Crisis
“In the industry, we are in the midst of an ever-moving talent crisis where half of our industry will be retiring by 2036.” - Meredith Barnes-Cook
The insurance industry faces a looming talent crisis, with a significant portion of its experienced workforce set to retire in the coming years.
Intelligent automation, as Meredith emphasized, can be a key strategy in mitigating this challenge.
By enabling insurers to grow and optimize business processes without a linear increase in headcount, AI can help bridge the talent gap. However, implementing automation isn't solely a technological challenge; it requires effective change management.
Engaging employees early, addressing their concerns, and providing opportunities for reskilling and career growth will be critical in this transition.
Both Ankur and Meredith agreed that insurance is the staple and there’s no world without insurance. It’s all about getting and retaining the younger generations into the insurance to fill enough of the roles as more of the population retires. Automation can be a part of the solution, which makes it a necessity.
The Quest for the Right Automation Insurance Solution
When evaluating automation solutions, Meredith advises insurers to seek flexible systems that can handle cases without breaking down.
The technology should provide explainability, allowing users to understand how decisions are made, and include a feedback loop for continuous model improvement.
Meredith advocates for a human-in-the-loop approach, where AI augments rather than replaces human expertise. This strategy allows insurers to reap the benefits of automation while still leveraging the judgment and experience of their human experts.
“Sometimes there isn’t going to be one solution that over time is going to be able to span across all the different use cases. It’s not a good strategy to do nothing until you measure and map everything, because by the time you do; you’ll have to keep going back and doing it again because problems keep shifting and changing.” - Meredith Barnes-Cook
Measuring Success/The ROI Conundrum
One of the biggest hurdles in implementing automation is calculating the return on investment (ROI).
Insurers must look beyond simple cost savings and consider the revenue growth potential across the entire policy lifecycle.
To build a compelling business case, Meredith recommends having open conversations with technology vendors about realistic impact and timelines.
Setting clear expectations and defining success metrics upfront can ensure that automation initiatives deliver measurable value.
Both Ankur and Meredith agreed that even after missing an estimated ROI, it is still worthwhile considering:
- How much human effort is reduced through technology
- How much more volume a business can handle
- How much operating expenses can be reduced with such technology
As difficult as it is to estimate the ROI, it’s necessary. Having an estimate down the road will help remind the companies that the insurance automation is worth it.
The Future of Insurance Automation: AI's Potential for Complex Claims Processing
While automation is often associated with simple, repetitive tasks, Meredith highlighted an exciting frontier for AI: complex claims.
By continuously monitoring claims data and proactively flagging potential issues for human adjusters, AI systems can help insurers manage risk and improve outcomes.
This application underscores AI's potential to augment human expertise rather than replace it.
Both Ankur and Meredith agreed on using AI as a tool that helps people become better at what they do.
“Trying end-to-end automation completely with software without any humans involved is a recipe for disaster” - Ankur Patel
By providing real-time insights and recommendations, AI can help adjusters make faster, better decisions, ultimately enhancing customer satisfaction and reducing costs.
Best Approach to Automate Insurance
The insurance industry stands at a critical juncture, facing the challenges of a changing workforce, evolving customer expectations, and the need for operational efficiency.
As Meredith's insights illustrate, AI and automation offer a path forward, enabling insurers to navigate these challenges, unlock new opportunities, and improve operational efficiency.
But success requires more than just technology; it demands a strategic, human-centric approach focused on change management and measurable ROI.
Collaboration between insurers and technology providers will be key, as will a willingness to experiment and iterate.
The insurance industry's digital transformation is not just about technology; it's about reshaping an industry to better serve its customers and society as a whole.
And for those, like Meredith, who are willing to lead this change, the rewards extend beyond business outcomes – they lie in shaping a future where insurance is more accessible, personalized, and responsive to the needs of our ever-changing world.
Want to learn more about AI in insurance? Check out this episode on AI's impact on insurance through improved risk assessment and customer service with Niko Fotopoulos, CEO of Sparx.
