Page 38 - The Insurance Times February 2026

refinements in pricing, underwriting logic, and customer Insurance Function AI Application
experience responding more dynamically to changing needs
and risks. Underwriting Risk scoring, dynamic pricing,
segmentation
Stage Primary Focus Key Characteristics Claims Automated triage, fraud
detection, damage assessment
Digitisation Efficiency Online issuance, digital
KYC, automated Customer Service NLP-based chat and query
workflows resolution
Automation Speed & Scale Rule-based underwriting, Risk & Compliance Pattern recognition, anomaly
straight-through detection
processing
Table 2: AI Across the Insurance Value Chain.
Agile Adaptability AI-driven risk models,
Intelligence continuous learning, it
erative improvement Industry observations indicate that AI-supported workflows
can reduce claims processing time by 30–50% when com-
Table 1: The insurance industry’s progression from bined with structured operating models.
digitisation toward intelligent, adaptive systems powered by
AI and agile execution. 3. Agility as the Execution Engine
AI initiatives in insurance don’t usually fall short because of
2. AI as the Intelligence Layer in Insurance
technical limitations. More often, they fail because organi-
AI is becoming deeply woven into every part of the insur- zations struggle to adapt their internal processes, team
ance value chain, fundamentally changing how decisions are roles, and governance frameworks.
made and how they evolve over time.
That’s where agile operating models come in. They help
Intelligent Underwriting close this gap by enabling:
Today’s underwriting engines are far more advanced than Y Seamless collaboration between actuarial, technology,
before. They can pull in data from a variety of sources, in- and business teams
cluding historical claims, telematics, geospatial data, and
Y Ongoing compliance checks, rather than waiting for de-
even behavioral indicators. This enables insurers to:
layed, one-time approvals
Y Better segment risk
Y Faster learning cycles, while keeping risk exposure un-
Y Speed up the underwriting process
der control
Y Price policies more accurately based on real-world risk
In a highly regulated industry like insurance, agility doesn’t
Thanks to agile delivery models, underwriting teams can test mean a lack of discipline. Instead, it offers a structured, flex-
new models in specific customer segments, learn from the ible approach to innovation allowing companies to move fast
results, and scale up gradually without disrupting core busi- while still staying within regulatory boundaries.
ness operations.

4. Redefining the Customer Relationship
Smarter Claims Systems
Agile Intelligence is reshaping how insurers engage with
Claims processing has long been a manual, time-consuming
task, often leading to delays and customer frustration. AI is customers, shifting the relationship from transactional to
helping to streamline this area by enabling: participatory.
Y Automated triage of claims
Personalised and Context-Aware Insurance
Y Early detection of potential fraud
AI enables insurers to design offerings that respond to indi-
Y Image-based damage assessments vidual behaviour and usage patterns, including:
Y Usage-based insurance
When these AI tools are paired with agile feedback loops,
Y Preventive alerts and nudges
they continuously learn and improve while staying transpar-
ent, auditable, and compliant with regulations. Y Context-specific coverage recommendations

34 February 2026 The Insurance Times