State model
A decision snapshot binds period, entity hierarchy, measures, formula versions, assumptions and source cut-offs. Scenarios never overwrite actuals.
Customers need to understand how timing, contribution regularity, access and rate uncertainty affect a savings goal without receiving a disguised recommendation.
The simulator produces customer-controlled scenarios, separates assumptions from account facts and compares contribution paths without ranking products or predicting returns.
Organisations, systems and operating conditions are intentionally anonymised and recomposed. The design demonstrates engineering and banking-domain reasoning; it does not represent a named client estate, vendor product or measured production result.
Typed commands, state changes and receipts cross an event spine without surrendering domain ownership.
Permitted workThe system explains approved information and calculations. Product eligibility, suitability, tax interpretation and legal effect remain separately governed.
Consistency ruleResolve brand, legal entity, product version, jurisdiction and effective date before using a rule or term.
Hard boundaryThe model is not a system of record, identity provider, policy authority or proof that an external effect occurred.
A business operator needs a reconciled view, explanation or scenario from several data products while retaining ownership of the business decision.
Every projection displays assumptions, uncertainty and scope; the system cannot infer risk appetite or label a scenario suitable.
A deterministic outer workflow contains model-led work inside typed, observable calls. Dashed messages remain proposals until policy or a human grants authority.
A decision snapshot binds period, entity hierarchy, measures, formula versions, assumptions and source cut-offs. Scenarios never overwrite actuals.
Read from curated analytical products rather than operational tables. Use drill-through links for source detail and typed write-back only for approved decisions.
Definitions and units are resolved before aggregation. Missing data stays missing; mixed grains and double-counted entities fail reconciliation.
These roles are deliberately vendor-neutral. Each can be independently owned, versioned and replaced.
Evaluates identity, purpose, capability, amount, risk tier and policy version; returns allow, deny, step-up or human-review with reasons.
Chooses an approved model route by task, risk, evidence quality, latency budget and cost ceiling; enforces structured outputs.
Serves owned, audience-qualified and effective-dated content; exposes supersession, withdrawal and dependency metadata.
Builds time-qualified projections from source events and reconciliations without becoming the legal system of record.
Appends request, versions, policy result, model proposal, approval, action receipt, readback, correction and custody events under one correlation key.
Durable records carry provenance, authority, effect and custody without turning a transcript into an uncontrolled memory store.
Resolve brand, legal entity, product version, jurisdiction and effective date before using a rule or term.
The selected design is not universally superior. It is the safer fit for this boundary and failure cost.
Compile stable decision logic and retain retrieval for explanation and residual ambiguity.
Ask a model to interpret the source document for every request.
Cost acceptedRule compilation needs controlled change, but creates repeatable decisions, regression tests and clear exceptions.
Reserve larger models for residual reasoning after deterministic and smaller-model gates.
Send every request to the most capable available model.
Cost acceptedRouting adds evaluation work and operational complexity, but controls cost, latency and unnecessary data exposure.
Federate authoring while centralising lifecycle metadata, validation and serving rules.
Create one centrally authored knowledge corpus.
Cost acceptedFederation requires stronger contracts and owner discipline, but preserves domain accountability and release velocity.
Use event-fed projections for scale and direct readback for consequential effects.
Fan out to all systems of record for every interaction.
Cost acceptedRead models introduce lag and reconciliation work, but reduce source load and make cross-system views feasible.
Use append-only events plus a rebuildable current-state projection.
Overwrite the case row with its latest status.
Cost acceptedReplay and storage are more complex, but point-in-time reconstruction and correction lineage remain possible.
Retries are bounded by knowledge of business effect; unknown outcome remains visible, owned and independently reconciled.
Actual thresholds belong to accountable service owners. The design exposes the equations and observables that those owners must baseline.
query_load = active_users x decisions_per_hour x source_scansscenario_work = entities x periods x assumptions x alternativesreview_value = avoided_rework + decision_gain - compute - human_effortUse customer holdings only when necessary for the current explanation and keep external or assumed circumstances visibly separate.
A design is production-ready only when teams can prove what happened, recover it and change it safely.
product and rule applicability
guidance-versus-advice boundary
superseded-content withdrawal
calculation and citation verification
Customer inputs, source balances, rate assumptions, calculation version, alternatives shown, boundary classification and selected scenario.
The customer chooses inputs and action; an adviser handles requests that cross into personalised recommendation.
Begin with explanation and transparent calculations. Add recommendation only where decision rights, counterfactual evaluation and outcome measurement are established.
Product, conduct, legal, tax, knowledge and advisory owners define the permitted answer boundary.