Optimisation & Training Insights
AI/ML solution for enhancing team and business outcomes in loss adjuster management
2022 | Product vision, research, and end-to-end design
Overview
At Tractable, the product had matured, but its UX, workflows, and long-term strategic direction needed evolution. The goal was to standardise core experiences across regions while prototyping a 3–5 year AI-driven roadmap and validating it with clients under tight time constraints.
Overview
At Tractable, the product had matured, but its UX, workflows, and long-term strategic direction needed evolution. The goal was to standardise core experiences across regions while prototyping a 3–5 year AI-driven roadmap and validating it with clients under tight time constraints.
Discover
Problem & Context
Claims adjusters face complex, error-prone decision workflows, inconsistent tools across regions, and limited training support — reducing productivity and trust in automated insights.
Problem & Context
Claims adjusters face complex, error-prone decision workflows, inconsistent tools across regions, and limited training support — reducing productivity and trust in automated insights.
The challenge was:
Fragmented experiences across roles and regions
Limited trust in AI outputs due to lack of clear rationale
Need for a strategic vision that balanced immediate UX improvements with a long-term AI ecosystem
This was not just a UI problem — it was a systems problem requiring alignment between people, data, interfaces, and business goals.
The challenge was:
Fragmented experiences across roles and regions
Limited trust in AI outputs due to lack of clear rationale
Need for a strategic vision that balanced immediate UX improvements with a long-term AI ecosystem
This was not just a UI problem — it was a systems problem requiring alignment between people, data, interfaces, and business goals.
Define
How might we
How might we utilize AI-suggested estimates to efficiently train adjusters, resulting in increased productivity and aligning with the goal of increasing net profit for insurance companies?
How might we
How might we utilize AI-suggested estimates to efficiently train adjusters, resulting in increased productivity and aligning with the goal of increasing net profit for insurance companies?
Analysing data
Investigate the drivers of insurance business growth and decline, including costs and potential causes for fluctuations in performance.
Analysing data
Investigate the drivers of insurance business growth and decline, including costs and potential causes for fluctuations in performance.
Task flow
Task flow
Design & Deliver
Approach & Key Decisions
Holistic mapping: Mapped product journeys and pain points across markets to understand variance in workflows and trust signals.
Service-oriented framing: Merged qualitative research with service analysis to connect frontstage user tasks with backstage models and analytics.
Strategic exploration: Used Product Field Canvases and internal hackathons to explore AI integration use cases and prioritise high-impact themes.
Stakeholder alignment: Facilitated cross-functional collaboration with claims specialists, internal teams, and enterprise clients to refine concepts and validate assumptions.
Approach & Key Decisions
Holistic mapping: Mapped product journeys and pain points across markets to understand variance in workflows and trust signals.
Service-oriented framing: Merged qualitative research with service analysis to connect frontstage user tasks with backstage models and analytics.
Strategic exploration: Used Product Field Canvases and internal hackathons to explore AI integration use cases and prioritise high-impact themes.
Stakeholder alignment: Facilitated cross-functional collaboration with claims specialists, internal teams, and enterprise clients to refine concepts and validate assumptions.
Main feature: key insights
Main feature: key insights
Outcomes & Impact
Aligned teams around a long-term AI-enhanced insurance services vision
Validated future roadmap direction directly with enterprise clients, strengthening partnership opportunities
Built a scalable design system and workflow patterns that reduced delivery friction
Influenced product strategy toward new revenue-enabling use cases
Outcomes & Impact
Aligned teams around a long-term AI-enhanced insurance services vision
Validated future roadmap direction directly with enterprise clients, strengthening partnership opportunities
Built a scalable design system and workflow patterns that reduced delivery friction
Influenced product strategy toward new revenue-enabling use cases
Design Details
Design system & accessibility
Following with design activities, include building the design system, together with other product teams and marketing team’s rebranding project.
Making sure design pass the AA assissiblity test, working the copy and translation with external agencies or our translation team.
I managed the design backlog and feedbacks do make sure further iterations are planed and delivered.
Design system & accessibility
Following with design activities, include building the design system, together with other product teams and marketing team’s rebranding project.
Making sure design pass the AA assissiblity test, working the copy and translation with external agencies or our translation team.
I managed the design backlog and feedbacks do make sure further iterations are planed and delivered.
