PRD

Summary

As our operations teams scale alongside increasing claims volume and fraud risk, our legacy internal tooling has become a significant bottleneck to productivity and decision quality. Today’s platform is fragmented, slow, and forces users to toggle across multiple systems just to resolve a single case. These inefficiencies not only delay work and reduce morale, but also threaten our ability to identify and prevent fraud in a timely manner. To solve this, we will design and launch a new, integrated internal platform that centralizes ticket management, automates routing, surfaces real-time data, and reduces repetitive tasks. This will allow our operations team to move faster, focus on higher-value investigations, and directly contribute to cost savings.

Goals

• Increase average tickets resolved per user per day from 50 to 70

• Improve annual fraud savings from $30M to $50M

• Reduce ticket misrouting or manual reassignment incidents by 90%

• Eliminate at least 3+ frequent swivel-chairing workflows through system integration

• Ensure 100% audit log coverage for compliance and traceability

Project Scope

We will scope this MVP around the fraud investigation team (~50 users), focusing on high-volume, high-impact workflows first. The platform will support real-time data connections across claims, provider, and member systems, and enable automated ticket routing, customizable views, and improved case handoffs. UI and visual polish will be handled post-MVP to allow more iteration space for engineering and UX. While future expansion to additional ops teams is likely, this initial rollout will focus on fraud-specific ticket workflows only. Dependencies will include data engineering (for source systems and integration), product design (for UX flows), and operational change management (for onboarding and adoption).

User Personas

We are designing this solution for:

• A structured, detail-oriented investigator who wants predictable workflows and minimal manual tracking

• A fast-moving, metrics-driven team member who thrives with automation and shortcuts

• A methodical but tech-resistant veteran who values documentation and minimal disruption

Maria Chen
Age: 32
Location: Sacramento, CA
Maria is a senior claims processor who prides herself on quality and precision. She’s the team’s go-to for policy questions and handles edge cases with care.

Goals & Motivation: Maria wants to complete work efficiently and correctly the first time so she can wrap up her day without loose ends.

Frustrations: She loses time switching between tools and retracing unclear ticket histories—especially when updates aren’t visible in one place.

Jamal Rivera
Age: 25
Location: Dallas, TX
Jamal is a quick learner and newer to the team. He enjoys uncovering better ways to work and is always looking for automation, shortcuts, or smart workflows.

Goals & Motivation: He wants to level up in his career by hitting his metrics and finding ways to work smarter.

Frustrations: He finds the current system too rigid and slow, especially when dealing with exception cases that fall outside the typical flow.

Tanya Patel
Age: 41
Location: Columbus, OH
Tanya has been in claims ops for nearly a decade. She’s known for consistency and mentoring newer team members, but isn’t quick to embrace new systems.

Goals & Motivation: She wants to feel confident in her decisions and avoid surprises in process or tooling.

Frustrations: Unannounced updates or changes to workflows break her momentum. She dislikes toggling between too many tools to complete simple tasks.

Requirements

P0 – Must-Haves (Launch Blocking):
We will ingest real-time data from member, provider, clinical, and claims sources to ensure every ticket has the most up-to-date and accurate context.
We will build a routing engine that automatically assigns tickets based on configurable logic—factors such as ticket type, region, and fraud risk score.
Users must be able to reliably update ticket status, assign ownership, leave comments, and transfer tickets without errors or latency.
An audit log system will capture every user interaction, edit, and handoff to maintain compliance and operational visibility.
The platform must scale to 50+ concurrent users without performance degradation.

P1 – High Impact Features (Enhance Utility):
We will introduce filters and views that allow users to sort and prioritize tickets based on urgency, impact, and age in queue.
Bulk ticket actions (e.g. close, reassign, escalate) will reduce manual load for high-volume users.
External data (e.g. fraud scoring results) will be integrated directly into the ticket view to support faster decision-making.
Users will be able to link related tickets and view case groupings to support investigations spanning multiple sources.
A permissions system will ensure that data visibility is role-based and auditable.

P2 – Future Enhancements (Post-MVP Quality-of-Life):
Users will have the option to save custom filters and workflows for common ticket types.
Slack/email integrations will notify users of ticket updates, assignments, or escalations.
A read-only dashboard will be created for leadership and legal review without editing rights.
Historical data patterns will be used to surface trends, repeat issues, and workflow bottlenecks.

Launch Plan / GTM

Considering the critical nature of fraud operations, we will take a phased and low-risk rollout approach, while maintaining momentum through weekly cross-functional syncs with ops, engineering, and enablement.

• Week 1: Launch to a pilot group of 15 users focused on low-risk, low-urgency tickets

• Week 2: Expand to another 15 users working medium-priority workflows

• Week 3: Full migration of the fraud team with remaining workflows transitioned

We will develop UAT test matrices for each major feature, share SOPs ahead of time, and designate team-level launch captains to answer questions and triage bugs. Feedback from pilot phases will directly inform backlog prioritization for P1 features. Post-launch, we will hold weekly retros to review success metrics, identify issues, and scope iteration needs.

Success Criteria

This platform will be considered successfully adopted when:

• Over 90% of tickets are worked on the new platform within 30 days of full rollout

• Median ticket resolution time improves by at least 20% from pre-MVP benchmarks

• At least 3 redundant manual workflows (e.g. double-entry or system toggling) are eliminated

• CSAT surveys from internal users show a satisfaction rating of 4.0+ (out of 5) for workflow speed and data reliability

Measurement Plan

To track success and adoption, we will monitor:

• Time-in-ticket: comparing average ticket resolution durations before and after rollout

• Platform adoption: % of tickets created, worked, and closed within the new system

• Routing efficiency: % of tickets auto-routed vs. manually reassigned

• Audit integrity: completeness of audit logs and absence of logging failures

• Feedback intake: themes and volume of post-launch feedback from frontline ops teams

Risks

• The routing engine could misfire early if metadata is incomplete or outdated, causing manual rework

• Without proper onboarding, users may revert to old tools or shadow systems

• Cross-system integration bugs could cause tickets to display stale or conflicting data

• Compliance issues could arise if audit logs fail or if permissions are misconfigured

• Extended dependency on engineering bandwidth may delay key P1 enhancements