EX

Simulation & Prediction

Back to journey: Regulatory & Compliance

Scenario Simulation Workspace

Compare current state, no action, recommended, upside and downside scenarios for one journey or issue.

Journey

Regulatory & Compliance

KPI under simulation

Regulatory breaches

Current

2

Target

No stored target

Scenario outcome cards

Current State

Base case

Current trajectory with in-flight initiatives only.

Stated outcome
Potential penalty exposure: $0.75M
Risk / trade-off
—
Regulatory breaches in 6 mo
2 ACTUAL
RecommendedRecommended

USSD + retail campaign

Self-verify via USSD plus retail.

Stated outcome
~85% verified
Risk / trade-off
Fraud controls needed
Regulatory breaches in 6 mo
1.14 SCENARIO
Expected value
Loss avoided: USD 750k expected
Alternative

Request extension

Ask regulator for 60 more days.

Stated outcome
Deadline relief
Risk / trade-off
Uncertain; reputational risk
Regulatory breaches in 6 mo
not modelled
Alternative

Retail-only verification

Verify in shops only.

Stated outcome
~55% verified
Risk / trade-off
High disconnection risk
Regulatory breaches in 6 mo
not modelled

Not stored for this journey: No Action, Upside, Downside. Shown as a gap rather than invented.

Scenario comparison — stated value vs cost/risk (USD M)

Amounts parsed from each scenario's stored results; ★ = recommended. Non-monetary outcomes plot as zero.

Risk / return matrix

Top-left = high value for low stated cost/risk.

Regulatory breaches — actual vs scenario paths

ACTUALFORECASTSCENARIO

Same projection as the journey Predict stage and the Forecasting page. Open full forecast →

Comparison table

ScenarioRoleAssumptionsProjected KPI (6 mo)Stated impactRisk / trade-off
Base caseCurrent StateCurrent trajectory with in-flight initiatives only.2Baseline—
USSD + retail campaignRecommendedSelf-verify via USSD plus retail.1.14~85% verifiedFraud controls needed
Request extensionAlternativeAsk regulator for 60 more days.—Deadline reliefUncertain; reputational risk
Retail-only verificationAlternativeVerify in shops only.—~55% verifiedHigh disconnection risk

Scenario → decision

Recommended scenario: USSD + retail campaign — ~85% verified; trade-off: Fraud controls needed.

No decision is saved here; the decision is recorded in the journey at Decide.

Source data, assumptions, methodology & limitations

Source data

  • Telecom KPI data (current period, target, prior)
  • Historical KPI trend data (monthly history Apr–Sep 2026)
  • Scenario library (assumptions, results, recommended flag)
  • Value realization records (expected / actual value)
  • Evidence records

Assumptions

  • No action: continues the 6-month stored trend (+0.14 per month).
  • Recommended action: reverses the trend at the same monthly rate (no stored target).
  • Scenario outcomes, costs and risks are as stored for each scenario.

Methodology

  • Scenarios of the selected journey are ordered Current State → No Action → Recommended → Upside → Downside → Alternatives.
  • With an originating issue, alternatives sharing no words with the issue move to the bottom of the table.
  • Projected KPI per scenario uses the shared deterministic forecast; only Current State, No Action and Recommended are modelled.

Limitations

  • Scenario outcomes are governed figures stored with each scenario — they are not re-computed by a simulation engine.
  • Forecasts are straight-line projections of six stored months; they ignore seasonality, shocks and interactions between measures.
  • Many KPIs have no stored target; where absent, the recommended path reverses the trend at the same monthly rate.
  • No downside scenario is stored for any journey; downside coverage is shown as a gap rather than invented.
Forecast horizon: 6 months (KPI projection); scenario outcomes as statedModel status: deterministic arithmetic — no AI or machine-learning model.
Evidence typeItemSource
limitation

Regulatory data lag

Regulator returns lag by one quarter; current quarter is estimated.

Regulatory Reporting Store
methodology

Regulatory & Compliance methodology

Track obligations against regulator calendar; Monitor QoS and SLA thresholds; Log audit findings and actions.

Finance Planning Dataset