ORAVYS FINANCIAL
Used by Hedge Funds & Institutional Analysts

Financial Prosody

AI-Powered Earnings Call Analysis for Institutional Investors. Detect CEO stress, deception, and confidence signals that transcripts can never reveal.

107
Voice Engines
Stanford
Research Validated
$500+
Starting / Month
< 5 min
Per Earnings Call
Request Access ↗ View Sample Report
Earnings Call Analysis
S&P 500 Tech Sector · Q4 2025
Live
MARGIN Q FWD GUIDANCE Confidence
Confident CEO
Stressed CEO
Confidence
78
Authenticity
85
Stress Index
47
The Science

Voice Reveals
What Words Hide

Decades of research confirm what traders have always suspected: vocal cues during earnings calls contain predictive signals that no transcript can capture.

📚 Stanford GSB · 2012
"Detecting Deceptive Discussions in Conference Calls"
David F. Larcker & Anastasia A. Zakolyukina — Stanford Graduate School of Business
CEO and CFO vocal patterns during earnings calls predict future accounting restatements with over 65% accuracy. Linguistic markers such as reduced self-reference, increased certainty language, and elevated pitch variance correlate strongly with subsequent earnings manipulation.
Confident CEO · Guidance Q
Stressed CEO · Guidance Q
🎤
Prosody vs. Semantics
Prosody (pitch, tempo, rhythm, voice quality) is a separate information channel from word choice. Under cognitive load or deception, prosody changes involuntarily — unlike scripted language.
🧠
Cognitive Load Signals
Higher mental effort while constructing false or uncertain narratives manifests as longer latencies, increased filler use, reduced pitch range, and micro-tremors in the 8–12 Hz frequency band.
📈
Baseline Comparison
Deviations from a speaker's own historical baseline are more predictive than absolute thresholds. ORAVYS builds per-executive voice profiles across quarters for maximum signal extraction.
🛡️
EU AI Act Compliant
ORAVYS Financial Prosody operates under Article 50 transparency guidelines. This is a decision-support tool — never a standalone verdict system. All outputs include confidence intervals and methodology disclosures.
What We Analyze

107 Engines,
6 Core Signals

Every earnings call is processed through our full engine stack. These six dimensions form the Financial Prosody report.

🧠
Forensic Engine
Cognitive Load Index
Measures real-time mental effort as the speaker formulates responses. Elevated CLi during specific questions signals complex information management — a key indicator of rehearsed deflection versus spontaneous recall.
8–12 Hz tremor band · Pitch variance · Latency HIGH SIGNAL
📈
Personality Engine
Vocal Confidence Score
Quarter-over-quarter baseline comparison of executive vocal confidence. Tracks assertion strength, pitch stability, speech rate, and articulation precision — with statistical deviation alerts when patterns break significantly.
Q/Q trend · Per-speaker baseline · Statistical delta HIGH SIGNAL
🔴
Stress Engine
Stress Markers
Detects micro-tremors (8–14 Hz), pitch instability, and jitter/shimmer spikes. Particularly powerful during forward guidance and margin discussion segments — the highest-stress moments in any earnings call.
Jitter · Shimmer · HNR · Tremor frequency CRITICAL
🔎
Forensic Engine
Authenticity Score
Differentiates rehearsed script delivery from spontaneous, natural speech. Prepared opening statements score high; the delta versus Q&A spontaneous responses is a critical deception signal — the wider the gap, the higher the risk.
Prepared vs. spontaneous delta · Naturalness index KEY METRIC
💡
Clinical Engine
Emotional Valence
Maps real-time optimism, concern, anxiety, and enthusiasm throughout the call. Subtle valence shifts during strategic sections — particularly when discussing competition or macroeconomic exposure — carry strong predictive weight.
Affect tracking · Valence timeline · Arousal index KEY METRIC
⏳
Temporal Engine
Temporal Patterns
Analyzes response latency before key numbers, pause structure before forward guidance, and speech acceleration when deflecting analyst questions. Temporal anomalies are among the hardest behavioral signals to consciously control.
Response latency · Pause patterns · Speech rate delta HIGH SIGNAL
Process

How It Works

From earnings call audio to institutional-grade prosody report in under five minutes.

1
Upload Earnings Call Audio
Upload MP3 or WAV directly, or paste a webcast URL. ORAVYS accepts standard IR audio formats from Bloomberg, FactSet, S&P Global, and all major earnings call providers. Files are encrypted in transit and processed in isolated compute environments.
MP3 · WAV · Webcast URL · Bloomberg Terminal API
2
107-Engine Processing
ORAVYS runs the full engine stack with forensic, clinical, personality, and temporal focus categories prioritized for earnings call context. Speaker diarization separates CEO, CFO, and analysts. Each speaking segment is analyzed independently, with particular weight on Q&A responses versus prepared remarks.
Forensic · Stress · Personality · Temporal · 107 Total Engines
3
Receive Per-Question Prosody Report
Each analyst question and executive response receives individual scoring. The report highlights which specific questions triggered stress spikes, confidence drops, or authenticity anomalies — with timestamped audio markers so you can replay flagged segments instantly.
Per-question scoring · Timestamped markers · Export PDF / JSON
4
Compare Against Historical Baseline
Institutional subscribers build executive voice profiles across multiple quarters. Every new call is automatically compared against the historical baseline, surfacing statistically significant deviations that single-call analysis would miss. Q/Q trend lines and anomaly flags are included in every report.
Q/Q Baseline · Historical Profile · Anomaly Detection · API Access
Sample Output

Financial Prosody
Report Preview

The following is a simulated report for illustrative purposes. Real reports contain full per-question breakdowns, audio timestamps, and historical comparison.

[Redacted] · S&P 500 Technology
Q4 2025 Earnings Call · CEO Voice Analysis · ORAVYS Financial Prosody v1.0
2026-02-14 · 09:03 EST · 52m 18s
Overall Confidence
78/100
-6pts vs Q3 baseline
Stress Spikes
3
Q&A: margins, guidance, competition
Authenticity
85/100
Prepared: 92 · Spontaneous: 71
Cognitive Load Peak
+47%
During Q4 guidance discussion
Detailed Signal Scores
Cognitive Load Index
73
Vocal Confidence
78
Stress Markers
61
Authenticity Score
85
Emotional Valence
69
Temporal Patterns
54
Stress Spikes:
▲ Margin Q (22:14)
▲ Fwd Guidance (38:47)
▲ Competition (44:02)
Key Finding: Significant vocal stress elevation (+47% above baseline) detected when discussing Q4 forward guidance at timestamp 38:47. Combined Cognitive Load spike, jitter increase (+2.3%), and response latency outlier (3.8s vs 1.2s baseline) warrant attention. Authenticity delta between prepared remarks (92) and Q&A segment (71) is above threshold — a 21-point gap versus historical average of 9 points.
Competitive Edge

Why Voice Analysis
Beats Text Analysis

Every alternative leaves alpha on the table. ORAVYS captures the channel that machines cannot script and humans cannot hide.

Standard Approach
NLP Sentiment Analysis
Reads the words management chose to say. Easily gamed by investor relations teams who script every sentence. Misses everything that language is designed to conceal.
VS
ORAVYS Advantage
Prosody: Reads the Voice
Analyzes pitch, tremor, latency, and rhythm — signals the speaker cannot consciously control. Catches what scripted language is designed to hide.
Standard Approach
Transcript Analysis
Delayed, often edited by IR teams before release. "[Inaudible]" redactions on exactly the moments that matter most. No temporal or prosodic information survives transcription.
VS
ORAVYS Advantage
Raw Audio — Unfiltered
Works directly from the source webcast. No transcription intermediary. Every hesitation, every micro-tremor, every pause is preserved and analyzed.
Standard Approach
Generic AI (GPT / Claude)
General-purpose LLMs trained on text, not voice. Zero understanding of prosodic features, speaker baselines, or bio-acoustic stress markers. Not built for this problem.
VS
ORAVYS Advantage
107 Specialized Voice Engines
Every engine purpose-built for voice. Trained on 114,000+ voice vectors. Forensic-grade pipeline with 99.96% F1 accuracy on authenticity detection. Built for exactly this problem — nothing else.
Pricing

Institutional
Grade Pricing

Priced for the intelligence it delivers — not the compute it costs. Every tier includes the full 107-engine stack.

Professional
For individual analysts and portfolio managers
$500
per month · billed annually
  • 50 earnings calls per month
  • Full 107-engine prosody report
  • Per-question stress breakdown
  • Timestamped audio markers
  • PDF & JSON export
  • 5 executive voice profiles (historical)
  • Email & Slack alerts
Request Access
Most Popular
Institutional
For hedge funds and asset management teams
$2,000
per month · billed annually
  • Unlimited earnings calls
  • Full 107-engine prosody stack
  • REST API access for Bloomberg/FactSet integration
  • Unlimited executive voice profiles
  • Q/Q baseline comparison & trend alerts
  • Sector-level aggregate stress index
  • Priority processing (< 3 min per call)
  • Dedicated account support
Request Access ↗
Enterprise
For large funds requiring custom deployment
Custom
dedicated pricing
  • Everything in Institutional
  • On-premise or private cloud deployment
  • Dedicated analyst team
  • Custom model fine-tuning on your sector
  • White-label output (your branding)
  • SLA: 99.9% uptime guarantee
  • Compliance package (SOC 2, audit trails)
Contact Sales

30-day money-back guarantee on Professional and Institutional plans. No setup fees. Cancel anytime.

Validation

Trusted by
Institutional Investors

107
AI Voice Engines
in the stack
114K+
Voice vectors
in training data
99.96%
F1 accuracy on
authenticity detection
65%+
Restatement prediction
(Stanford, 2012)
Academic Validation
Stanford GSB
NBER
J. Finance
Review of Acc. Studies
As Seen In
Financial Times
Bloomberg
WSJ
Risk.net
"We find that both CEOs and CFOs use language consistent with psychological distancing when they are being deceptive. Their vocal patterns deviate significantly from their baseline during segments where subsequent restatements occurred — detectable months before the restatement became public."
Larcker & Zakolyukina — Stanford GSB, 2012 · Journal of Accounting Research
"Voice stress analysis of earnings calls has emerged as a systematic, repeatable intelligence source for quantitative managers. Unlike sentiment analysis, prosodic signals cannot be edited after the fact — the audio is the ground truth."
Institutional Investor Research — Alternative Data Almanac 2025
EU AI Act · Article 50 Compliant
ORAVYS Financial Prosody operates as a decision-support tool. All outputs include confidence intervals, methodology disclosures, and explicit uncertainty ranges. NEVER marketed as a lie detector or standalone compliance instrument.
Get Started

The Edge Is in
the Voice

Request access to ORAVYS Financial Prosody. Our team will schedule a live demo using a real earnings call from your coverage universe.

Request Access ↗ Try Core Platform
GUEST