Non-life insurance relies on structured processes and workflows that involve complex steps. An industry traditionally based on data and human judgment is now seeing its core pillars tested in new ways.
Insurers today handle a huge volume of data than ever before. However, a large portion of this data is unstructured and remains locked away across the organization, in multiple systems and amongst various teams.
The challenge is making sense of this fragmented information and quickly retrieving it when needed to make a decision.
The next phase of insurance modernization will depend on how effectively systems help insurers not just capture but also organize and reuse dispersed information across the enterprise.
The Hidden Value Inside Everyday Information
Imagine the value that an Insurance company can derive when the institutional knowledge, its greatest asset, is easily accessed, organized, and utilized. Senior underwriters possess critical insights about risk nuances, claims handlers recognize patterns that warrant closer scrutiny, and product teams know how customers respond to changes in coverage.
Over time, these decisions, observations, exceptions, and learnings become part of an organisation’s collective intelligence. However, much of this knowledge isn’t readily retrievable, as it exists in silos and is bogged down by fragmented systems and inefficient workflows.
The cost of Disconnection
An often-neglected cost in insurance is the time employees spend developing workarounds when systems for policy, billing, claims, pricing, and documentation don’t communicate well. These employees frequently serve as connectors between various systems by re-entering data, reconciling spreadsheets, searching for documents, and manually linking information that ideally should be accessible in a single location.
A BCG Report reveals that integration issues can turn skilled professionals into data mules, diverting focus from decision-making to routine tasks. When underwriters spend 30% to 40% of their time on administrative tasks, risk assessment suffers.
Fragmented workflows can harm productivity and financial results, causing 7% to 14% claim leakage and 18% to 40% spreadsheet errors. Modernization isn’t just about adding a new digital front end; it is about ensuring that knowledge flows smoothly throughout the entire organisation, and this is where Artificial Intelligence (AI) can be a game-changer.
How AI Transforms Fragmented Systems into Reusable Expertise
AI can seamlessly weave through unstructured data, link context, surface history, and bring the right information to the right decision at the right moment. Used well, AI can turn individual experience into institutional memory that can be retrieved in real time.
It can quickly summarise lengthy claim files, identify similarities in past cases, spot missing data, spot risk trends, and help teams compare decisions across portfolios. For underwriters, this means integrating internal policy details, claims history, and external signals into a single platform, helping them determine whether the case they are handling is similar to previous claims or requires further investigation.
According to a Deloitte report, Property and Casualty Insurers could save up to $160 billion by 2032 by using real-time AI fraud detection.
AI needs governance
The insurance industry relies on trust. Pricing, underwriting, and claims decisions must be transparent and compliant with regulations. This is especially crucial as insurers move beyond small tests to using AI in main processes. This is also why readiness has to begin before implementation. For these systems to be compliant, governance needs to be engineered into them. Without it, AI may add speed but will falter at reliability and accountability. The question is no longer whether AI is useful but whether systems and human resources are ready to use it responsibly.
Better Context, Better Pricing, Better Products
Integrating institutional knowledge into AI benefits product creation and risk management. When knowledge is shared, product, actuarial, underwriting, and claims teams can see risks more clearly. This makes it easier to update prices, create new coverage options, respond to risks such as climate change and cyber threats, and explain decisions more confidently.
Modern pricing teams are moving toward platforms that enable rapid iteration, in which rate changes, product configuration, and risk model updates can be deployed in days rather than months. This matters because insurance is a dynamic product. Risks evolve, customer expectations shift, and regulations are updated. The carriers that will have a competitive edge are not necessarily those with the most sophisticated models, but the ones that can get those models into production and act on them faster than anyone else.
What’s Next
The next phase of non-life insurance will not be defined by the early adopters of AI, but by those who can make their institutional knowledge visible, usable, and trusted across the organisation. Insurers need to treat knowledge as infrastructure, not as something that sits informally in documents or individual experience.
Ultimately, insurance is still a business of judgment. What is changing is how that judgment is supported. When expertise can be reused, decisions are made more quickly, consistently, and transparently.
Authored by
Mohammed Anzy
Managing Director
Guidewire Software
India
