S
SESIM
Decision Integrity Layer
Synthetic Shadow Mode Simulation

Decision Integrity Layer for Financial Institutions

Shadow-mode AI infrastructure for detecting compromised financial decisions before irreversible loss occurs.

Fraud systems detect malicious actors. Sesim detects when a real customer may no longer be making a free decision.

Synthetic demo only. No real customer data is used on this website or dashboard preview.
Shadow Mode
Explainability
Audit Trail
Human Review
CASE-DI-0427
72-year-old customer, known device, active call context
Shadow mode active
DIS
42/100
compromised decision risk
AUPA
78%
authority-pressure pattern
YUDA
71%
decision autonomy degraded
Action
Soft Pause
reconfirmation before loss
Intervention Recommendation
Soft Pause + Reconfirmation

TRY 180,000 transfer to new beneficiary

Synthetic demo only. No real customer data is used on this website or dashboard preview.
Category Shift

The actor can be legitimate while the decision is compromised.

In coercion-style transfer risk, the device, login, and customer identity can all look clean. Sesim adds a decision integrity layer that observes pressure, urgency, stress movement, and behavioral drift beside the existing fraud stack.

Clean fraud profile

Known device, valid login, real customer, authorized transfer.

Compromised decision

Active call pressure, unusual urgency, new beneficiary, rising hesitation.

Operational recommendation

Soft pause, safer-channel reconfirmation, or silent escalation to fraud care.

Live Enterprise Dashboard

Synthetic operating console for a coercion-transfer review.

A bank risk team sees a clean fraud engine result, but Sesim flags compromised decision context and produces reason codes, timeline evidence, analyst notes, and audit logs.

Decision Integrity Score
42
/100
Intervention Recommendation
Soft Pause + Reconfirmation

TRY 180,000 transfer to new beneficiary

Transaction Timeline
10:42:11
Transfer initiated

Fraud profile clean; known mobile device and normal login.

10:42:27
Pressure context detected

Customer remains on an active call during beneficiary setup.

10:42:43
Decision drift rises

Hesitation and contradiction increase during confirmation.

10:43:02
Intervention recommended

Soft pause before irreversible transfer execution.

Explainability Panel
Actor appears legitimate; actor risk remains low.
Decision context shows authority-pressure pattern.
Voice stress trend rises during beneficiary confirmation.
Recommended action avoids exposing the customer to a coercer.
Analyst Notes
Do not hard block on first signal. Introduce friction without alerting the caller.
Ask customer to reconfirm through a safer channel after a cooling interval.
Escalate to fraud care if stress and urgency persist after reconfirmation.
Audit Logs
10:43:02
policy.recommendation.created
Soft Pause + Reconfirmation
10:43:04
explainability.reason_codes.attached
4 reason codes
10:43:07
human_review.queue.updated
fraud-care tier 2
Fraud vs Decision Integrity

Sesim does not replace the fraud engine. It covers the decision blind spot.

Fraud Engine

Optimized for malicious actor, credential, device, location, and session anomalies.

Known device: clean
Login risk: clean
Actor identity: legitimate
Transaction authorization: present
Decision Integrity

Optimized for pressure, autonomy, urgency, stress trend, and contextual drift.

Authority pressure: elevated
Decision autonomy: degraded
Voice stress: rising
Intervention: soft pause
Explainability Flow

Every recommendation is backed by a reviewable signal path.

1

Pressure Indicators

Authority cues, urgency language, active call context, repeated prompting.

2

Behavioral Deviation

New beneficiary, compressed confirmation time, unusual transfer path.

3

Emotional Stress

Rising voice stress trend and hesitation during sensitive prompts.

4

Recommendation

Soft pause, safer-channel reconfirmation, or silent care escalation.

Accessibility & Elderly Protection

Protect vulnerable customers without exposing them to the person applying pressure.

The first wedge is not generic fraud automation. It is a care-aware review layer for moments when an elderly or vulnerable customer may be guided through a legitimate-looking transfer under fear, urgency, or social pressure.

Active call pressure

The customer stays on a call while adding a new beneficiary and confirming a high-value transfer.

Fear of contradicting the caller

The customer appears compliant but hesitates when asked to explain the transfer purpose.

Safe reconfirmation

The bank introduces a pause and asks for confirmation through a safer channel without warning the coercer.

Customer protection workflow
Human review layer
Reason-code audit trail
Policy-safe intervention ladder
Enterprise Architecture

Deploy beside existing fraud workflows before touching production decisions.

Sesim starts in shadow mode: observe high-risk journeys, generate explainable decision-integrity signals, compare against existing outcomes, and only then define production-safe intervention policy.

1
Existing Fraud Stack

Receives device, login, session, and transaction risk outcomes.

2
Sesim Shadow Mode

Observes selected journeys without blocking customer flow.

3
Explainability Engine

Generates DIS, AUPA, YUDA, pressure indicators, and reason codes.

4
Audit Trail

Stores recommendation, reason code, analyst note, and review status.

5
Human Review Layer

Routes sensitive cases to fraud, compliance, or customer care teams.

Week 1-2

Discovery with fraud, compliance, innovation, and customer protection teams.

Week 3-6

Shadow-mode simulation on selected synthetic or anonymized transaction journeys.

Pilot Report

Decision integrity lift, false-positive review, and intervention policy proposal.

Review a synthetic coercion-transfer scenario with your risk team.

We are looking for 3 shadow-mode pilot conversations with banking and fintech teams.

Request Shadow-Mode Pilot

Tell us who should evaluate Sesim. We will reply with the shadow-mode pilot brief, synthetic scenario, and dashboard walkthrough.

Prefer email? Contact admin@sesim.net