Welcome to this week’s issue of Risk, Bytes and Beyond - your bi-weekly roundup of the latest insights at the intersection of data analytics, artificial intelligence and insurance. Delivered to your inbox every second Friday! In each edition, you’ll find:
Curated content from experts in data and insurance
An insight brief on a changing topic
The latest headlines on data and AI in insurance
Thanks for reading - let’s dive in!
💡 Noteworthy Content
Pravina Ladva of Swiss Re pushes back on the narrative that AI is pushing white-collar employees out. Instead, she argues generative AI is a force multiplier, helping the overburdened insurance workforce rebalance workloads, preserve institutional knowledge, and refocus on strategic, client-facing work. Amid rising fears of obsolescence and burnout, Ladva emphasizes that real progress lies in co-creating AI tools with frontline staff and fostering adaptability, not perfection. This piece offers a reassuring, human-centered perspective on AI’s role in insurance today.
This article spotlights Convex Insurance’s leap in productivity by deploying AI agents that transform engineering report analysis from hours into minutes, streamlining workflows and showcasing the real-world payoff of AI in complex operational environments. It’s a compelling read for anyone tracking industry use cases that deliver tangible time and efficiency gains.
This article examines how insurers are moving beyond traditional practices to embrace real-time, data-driven decision-making across underwriting, claims and risk management - highlighting a structural shift that promises faster, more accurate operations and deeper insights. Ideal for readers interested in how proliferating data and analytics are transforming the core mechanics of insurance.
💭 Insight Brief
The Data You’re Ignoring Could Be Your Next Competitive Edge
When insurers talk about “data,” the focus is usually on the obvious: claims histories, underwriting factors, external datasets and so on. But apart from that, insurance companies own other valuable information that often hides in plain sight: so-called data exhaust.
Data exhaust is the trail of digital by-products created as part of normal operations.
For insurers, this might include:
Call center transcripts revealing customer pain points.
Repair invoices capturing granular cost breakdowns.
Telematics pings from connected cars.
Individually, these traces seem messy and incidental. But together, they form a rich, underutilized dataset with strategic potential.
Why it matters
Unlike third-party data, insurers already own much of this exhaust. It’s closer to the customer, fresher than purchased datasets, and often overlooked by competitors. Properly harnessed, it can:
Improve efficiency: Analyzing call logs could flag recurring claim-processing bottlenecks.
Enhance underwriting: Repair invoices can feed into better loss cost models.
Create new revenue streams: Aggregated, anonymized exhaust data might interest auto manufacturers, real-estate platforms, or municipalities.
The challenge
Data exhaust is messy by nature. It doesn’t live in neat actuarial tables; it lives in PDFs, audio files, JSON logs, or siloed applications. That means insurers need strong data engineering pipelines, natural language processing, and governance frameworks before exhaust can become fuel.
There’s also the trust question. Customers may be surprised if their “by-product data” suddenly appears in third-party products. Transparency and anonymization are essential.
The opportunity
Think of data exhaust as the smoke from an engine: most companies let it drift away. But insurers that learn to capture, filter, and channel it can generate entirely new forms of insight.
The winners won’t just be the ones with the biggest datasets, but those who see value in the traces others discard.
💡 Takeaway: Every claims call, log file, or invoice carries hidden insight. Insurers who turn “waste” into knowledge can not only sharpen their own operations but create new markets for risk-relevant data.
📰 Industry Headlines
A major cyber incident stemming from a compromised vendor database exposed sensitive information - like names, addresses, birthdates, driver’s license numbers, and partial Social Security numbers - of over 1 million Farmers Insurance customers, illuminating vulnerabilities in third-party data management.
🔗 Newsweek
Datos Insights has acquired London-based InsTech, merging deep analytical expertise with a vibrant insurance innovation community. This strategic move strengthens Datos’ foothold in the critical London Market while giving InsTech expanded reach, particularly in the US, and positions both firms to help insurers navigate digital transformation, regulatory shifts, and emerging risks.
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