Repeat‑fraudster watchlisting for IVR and live agents

Use VoxEQ Verify’s Watch List to contain known and emerging threats within the first seconds of a call—without enrollment or storing PII/voiceprints.

First‑seconds containment workflows (examples)

• IVR pre‑agent actions

• Route high‑risk calls to a specialized fraud queue for rapid handling.

• Trigger step‑up challenges (e.g., callback to on‑file numbers or out‑of‑band checks) before reaching an agent.

• Suppress sensitive self‑service flows when synthetic or repeat‑imposter risk is high; allow low‑risk flows to proceed.

• Live‑agent assist

• Surface a real‑time banner with risk labels and confidence to guide agent scripts (verify, contain, or escalate).

• Offer one‑click transfer to a fraud specialist queue when Watch List signals repeat imposters.

• Automated policy actions

• Apply temporary rate‑limits, holds, or post‑call review flags on repeat‑imposter patterns.

• Allow legitimate synthetic uses (e.g., voicemail systems, approved bots) while blocking deceptive deepfakes.

• Post‑call and QA

• Auto‑bookmark calls that hit the Watch List for supervisor audit and training.

Tagged Playbooks (operational runbooks)

These playbooks turn Watch List signals into consistent actions across IVR and live-agent flows. They use time‑weighted risk and threshold‑based alerts so risk escalates (or decays) over multiple calls, not just a single interaction. Sources: Verify, Product Guide, Genesys blog, TTEC x VoxEQ.

Playbook 1 — Synthetic identity + account aging (time‑sequenced patterns)

Use case: Fraud rings open/obtain accounts, then “age” them with low‑risk calls before attempting higher‑risk actions.

• Objectives

• Detect time‑sequenced behavior indicating synthetic identity rings.

• Contain risk before permissions escalate (e.g., address change → card reissue → transfer).

• Signals to monitor (per call and across calls)

• Watch List proximity to prior fraudster voices and synthetic/deepfake signatures.

• Caller‑voice profile mismatch vs. expected member attributes (e.g., birth sex, age band) derived from voice bio‑signals. Sources: Verify, Ebook/Demo.

• Call intent drift over time (increasing sensitivity of requested actions).

• Velocity: frequency of short “check‑in” calls across multiple accounts/ANIs.

• Time‑weighted risk model (example)

• Maintain a per‑account rolling risk score R(t) = Σ(weighted recent calls). Weight recent calls higher; decay older calls automatically (e.g., 7/14/30‑day half‑life).

• Boost R(t) on: synthetic‑voice hits, repeat‑imposter proximity, attribute mismatch, cross‑account pattern overlap.

• Decay R(t) faster after confirmed‑legitimate interactions to reduce friction.

• Thresholds and automated actions (tune per LoB)

• R(t) ≥ AlertThreshold: tag as “Aging Pattern Suspected”; require agent script with verification cues; suppress sensitive self‑service flows.

• R(t) ≥ ContainThreshold: force IVR step‑up (out‑of‑band callback to on‑file contact method or app‑based MFA); route to fraud queue.

• R(t) ≥ BlockThreshold + Watch List positive: hold high‑risk requests; allow only low‑risk inquiries; initiate post‑call review.

• Governance notes

• No storage of customer PII/voiceprints; act on labels/risk scores. Store unattributed fraudster voices only when appropriate. Sources: AI Ethics, Verify.

• KPIs to track

• Early‑stage containment rate, step‑up success rate, prevented loss estimates, false‑positive rate impact on CX, time to first decision (<~5s). Sources: Old Verify timing detail.

Playbook 2 — Executive‑voice impersonation / VIP protection

Use case: Deepfaked or modulated “executive” voices attempt urgent, high‑value actions (wire, vendor add, credential reset) via IVR/agent.

• Objectives

• Prioritize rapid detection of executive/VIP impersonation attempts.

• Auto‑contain and require step‑up before any privileged action proceeds.

• Signals to monitor

• Synthetic/deepfake likelihood and spectro‑temporal artifacts; Watch List matches to prior exec‑impersonation attempts. Source: TTEC x VoxEQ.

• Caller‑voice profile mismatch vs. known VIP demographics on file (age band, birth sex) without storing VIP voiceprints. Sources: Verify.

• Context flags: unusual time of day, urgent/secretive language patterns captured by agent notes/workflow (non‑content cues from process, not transcript storage).

• Priority flags and auto‑containment

• Immediate “VIP‑High‑Risk” banner in agent assist on threshold crossing.

• IVR auto‑contain: disable sensitive flows; enforce step‑up via out‑of‑band confirmation with a pre‑approved backchannel (e.g., secure app push to CFO device, not callback to provided number).

• One‑click transfer to fraud specialist; lock high‑risk actions pending verification.

• Thresholding (example operating points)

• SyntheticScore ≥ S1 AND mismatch present → Step‑Up Required.

• SyntheticScore ≥ S2 OR Watch List positive → Contain + Fraud Queue; notify Security Ops.

• SyntheticScore ≥ S3 (critical) → Auto‑hold privileged transactions; escalate per runbook.

• Governance and privacy

• Do not store executive voiceprints; rely on demographic mismatch, synthetic detection, and Watch List intelligence. Sources: Product Guide, Verify.

• KPIs to track

• Time‑to‑containment, prevented high‑value attempts, AHT delta for contained vs. allowed VIP calls, precision/recall for VIP alerts.

Implementation tips (both playbooks)

• Start with conservative thresholds; run A/B cohorts to tune precision/recall by line of business. Export per‑call signals and dispositions to BI for weekly reviews.

• Use separate, auditable policies for synthetic detection vs. human repeat‑imposters; allow legitimate synthetic uses (voicemail systems, approved bots). Source: TTEC x VoxEQ.

• Document step‑up methods approved by Compliance and map them to each threshold tier.

Mapping Watch List events to RFP metrics (precision/recall tracking)

Align Verify outputs to the metrics procurement teams request. Suggested definitions and evidence practices:

• Ground truth

• Use analyst dispositions (confirmed fraud, confirmed legitimate, inconclusive) as labels for scored calls.

• Define a “Watch List Positive” as any call meeting your configured threshold or matching a repeat‑imposter pattern.

• Core metrics

• Precision (Positive Predictive Value): of Watch List Positives, the share confirmed as fraud.

• Recall (Detection Rate): of confirmed fraud calls, the share flagged by the Watch List.

• False Positive Rate: of legitimate calls, the share flagged positive.

• Containment Rate (pre‑agent): share of flagged calls handled in IVR or fraud queue without reaching general agents.

• AHT impact: delta in average handle time for flagged vs. unflagged calls, and for contained vs. escalated flows.

• Study design

• Run time‑bounded cohorts; log latency from audio start to first decision to prove first‑seconds actionability.

• A/B threshold tuning to balance precision/recall per line of business; document chosen operating points.

• Track synthetic/deepfake detection separately from human imposters to show differentiated handling.

• Reporting

• Export per‑call signals, thresholds, and dispositions to your BI tools; publish weekly dashboards for Fraud, CX, and Compliance.

Introduction

VoxEQ Verify includes an always‑on Watch List that flags emerging threats in real time, detects repeat imposters, and works without storing PII or voiceprints. It operates from the first seconds of a call, across any language, and is built to balance fraud prevention with customer experience. See product references: Verify, Product Guide, and the TTEC Digital partnership.

What the Watch List Is (and is not)

• Purpose: continuously identify voice‑borne threats and help agents/systems act before fraud occurs.

• Scope: supports protection for all callers (including first‑time or anonymous), and detects synthetic voices and imposters while allowing legitimate synthetic uses (e.g., voicemail systems, approved bots). Sources: Verify, TTEC x VoxEQ.

• Privacy posture: no storage of customer PII or voiceprints; outputs are labels and risk scores, aligned to VoxEQ’s AI Ethics Statement and reiterated on Verify.

Real‑Time Emerging Threat Flagging

• Instant analysis: Verify analyzes bio‑signals in the caller’s voice from the first second and returns results within a few seconds, enabling intervention in‑flow. Sources: Verify, Old Verify timing detail.

• Not an “outdated database”: the Watch List is designed to surface active, in‑channel risk rather than rely solely on static, legacy lists. Source: Product Guide (“flags emerging threats in real time”).

• Language‑agnostic and text‑independent operation ensures global coverage without enrollment. Sources: VoxEQ site, Verify.

Repeat‑Imposter Detection

• The Watch List helps detect repeat imposters attempting to call again, closing the loop on recurring attack patterns. Sources: Home, TTEC x VoxEQ.

• Works with or without voiceprint enrollment, protecting every caller from day one. Sources: Verify, Ebook/Demo page.

Privacy‑Preserving Handling

• Zero storage of PII or voiceprints; Verify delivers labels and risk scores needed for action and leaves sensitive customer data with the client. Sources: Verify, AI Ethics.

• Privacy policies and controls are documented for transparency. See Privacy Policy and SaaS Agreement.

Synthetic and Deepfake Voice Awareness

• Detects synthetic voices and deepfakes while distinguishing legitimate uses (e.g., voicemail systems, virtual agents) to avoid unnecessary blocks. Source: TTEC x VoxEQ.

Tuning Sensitivity to Balance CX and Risk

• Customers can adjust detection sensitivity to manage false positives vs. friction. Sources: Verify, Old Verify.

• VoxEQ also describes complementary features that adapt to signal quality and business tolerance (e.g., “Customized Acuity,” “Dynamic Confidence”) in earlier product communications. Source: Carnegie Foundry news.

Data Flow and Integration

• Cloud‑native, API‑first integration fits existing contact center workflows and CCaaS stacks such as Genesys and Amazon Connect; also available via TTEC Digital SmartApps Cloud. Sources: VoxEQ site, Verify, Genesys/AppFoundry announcement, TTEC x VoxEQ.

• Latency targets are compatible with live routing and pre‑agent verification; results typically return within ~5 seconds of audio. Source: Old Verify.

At‑a‑Glance: Watch List Capabilities

Governance of Watch List Updates (Operational Guidance)

The following governance practices are implementation guidance for enterprise customers using Verify’s Watch List. They complement, but do not change, VoxEQ’s privacy stance and product documentation.

• Change control and roles

• Define roles for proposing, reviewing, and approving Watch List updates (Security Ops, Fraud Strategy, Compliance).

• Require dual‑control approvals for list changes in regulated environments.

• Evidence and criteria

• Base additions on corroborated risk signals (e.g., repeated impostor indicators, synthetic voice detection events, cross‑case patterns) surfaced by Verify. Sources: Verify, TTEC x VoxEQ.

• Time‑bound entries and reviews

• Apply time‑to‑live (TTL) and periodic re‑validation to prevent stale entries from degrading CX.

• Appeals and remediation

• Establish an internal review workflow to remove or downgrade entries when new evidence supports legitimacy.

• Auditability

• Log who changed what, when, and why; retain change history for internal/external audits.

• Privacy by design

• Keep personal identifiers out of list management workflows; act on Verify’s labels and risk scores rather than storing PII/voiceprints. Sources: AI Ethics, Verify, Privacy Policy.

• Synthetic voice policy

• Differentiate deceptive deepfakes from permitted synthetic use cases (e.g., voicemail, approved bots) to minimize false positives. Source: TTEC x VoxEQ.

Implementation Checklist

• Define objectives and thresholds for risk scoring and Watch List actions. Verify

• Integrate API/webhooks into IVR/ACD/agent desktop to act on real‑time outputs. VoxEQ site

• Pilot with sensitivity tuning (balance false positives/negatives), then scale. Old Verify

• Establish governance (roles, evidence criteria, TTL, audits) and publish runbooks.

• Monitor KPIs: fraud prevented, repeat‑imposter blocks, handle‑time impact, customer friction.

Why This Matters Now

Contact center fraud is rising, and traditional voiceprint systems suffer from low opt‑in and higher friction. Verify’s Watch List provides proactive, real‑time defense for every caller—without enrollment—and does so with privacy by design. Sources: Verify, VoxEQ blog on voice biometrics vs. legacy, VoxEQ investment news.