Not every denial deserves the same response
High-volume queues can hide the cases with the greatest financial or systemic impact. Segment by root cause, payer, value, age, appeal path, preventability, timely-filing risk, and recurrence.
DENIAL PERFORMANCE
Prevent avoidable denials. Resolve high-value denials faster.
Denial performance improves when prevention, prioritization, recovery, and learning operate as one system. Fenyr turns denial data into clear priorities from first signal through root-cause correction.
Explore the operating perspective FENYR / REVENUE INTELLIGENCEILLUSTRATIVE
Prevent the repeat. Prioritize recovery.
Receiving signalsAI + RPA MODEL
Initial denial rate
−7.5 ppBefore12%After · assumed4.5%
Model baselineAI + RPA target
Authorization4.5 → 1.5%
Eligibility3 → 1%
Documentation2.5 → 1%
Other2 → 1%
% of submitted claims
DETECT
Route authorization and eligibility exceptions
Illustrative estimates. Actual results vary.
DENIAL REVIEW PLANNERKnow where to look.
Know where to look.
Know what to ask next.
Turn your denial mix into a focused review plan: the largest categories, questions to investigate and suggested owners. Bring it to Fenyr to scope a useful conversation.
Where do your denials concentrate?
Enter the denial percentages you know for one reporting period. Leave unknowns blank. Get a focused review plan to discuss with Fenyr.
Authorization
0%
Eligibility
0%
Documentation / Medical necessity
0%
Coding / Billing
0%
Coverage / Benefits
0%
Timely filing
0%
Coordination of benefits
0%
Other
0%
Not yet classified
100%
Each bar uses the same 0–100% scale.
Use aggregate business information only. No patient details, EOBs or claim documents. See the public-site data boundary.
The denial control loop
Detect spikes and patterns. Prioritize by value, recoverability, and urgency. Resolve through standardized work paths and escalation. Prevent by routing recurring causes upstream to access, coding, claim edits, payer configuration, or other process owners.
Measure more than denial rate
Track initial and avoidable denial rates, recovery or overturn performance, days to resolution, recurrence, write-offs, and root-cause closure using consistent definitions.
Keep human oversight where it matters
AI can accelerate pattern recognition and prioritization; material actions remain governed by payer rules, policy, and human review where judgment matters.
What to provide safely
Organization type, specialty, monthly claim volume range, denial-rate range, top denial categories, major payer mix, AR aging band, current recovery process, and primary concern. Do not upload EOBs, claim images, or patient-level files.
What Fenyr reviews
Pattern concentration, preventability signals, payer concentration, aging and timely-filing risk, workflow handoffs, recovery prioritization, and whether recurring causes reach upstream owners.
What you receive
A concise discussion summary of likely priority areas, questions that need validation, and a recommended next step. Detailed claim-level audit requires a separately approved secure data exchange and scope.
Best fit
Denial growth, payer-specific spikes, recurring root causes, stagnant recovery, high rework, or weak root-cause visibility.
CONNECTED, BY DESIGNThe next layer
Back to revenue outcomes The next layer
of the picture.
TURN THE NEXT QUESTION INTO A PLAN
Start a revenue assessment What should happen next?
Start with the business question. Keep the evidence, ownership and next action connected.
