AML/KYC Domain Pack — ψ-stack for compliance intelligence
ψ-stack configuration for AML/KYC detection. Encodes behavioural patterns, entity connections and regulatory rules as ψ-patterns for context-aware compliance analytics.
AML/KYC Domain Pack
Configure the ψ-stack for AML/KYC workflows. Encode compliance narratives, case material, and policy text into ψ-patterns so entities, stated relationships, qualifiers, negation, and uncertainty remain visible during retrieval across financial networks.
In compliance, the common failure mode is context loss: “no match”, “previously cleared”, exceptions, and conditional clauses can disappear under paraphrasing. This pack keeps those meaning switches intact — so you surface the right evidence, fast, and keep reviews consistent across teams.
Available as an add-on to EchoThesis and ResonanceDB.
What it configures
Domain Packs are ψ-stack configurations: operator rules, patterns, and couplings that shape how text is projected into ψ(x)=A(x)·e iφ(x) . The AML/KYC pack targets compliance language and makes key signals behave as first-class retrieval features — so evidence stays precise and reviewable under wording drift.
Entities & identifiers
Make people, organisations, roles, accounts, jurisdictions, and reference identifiers stand out as stable signals — the way they actually appear in case notes, screening logs, and investigative narratives.
Relationship language
Preserve how sources *state* relationships: ownership, control, representation, intermediaries, repeated counterparties, and narrative linkage across transactions — so retrieval follows the relationship, not just the keywords.
Negation & uncertainty
Keep high-stakes operators explicit: “no match”, “not associated”, “previously cleared”, “alleged/suspected”, “cannot confirm”, plus threshold and exception language — so “cleared” doesn’t collapse into “hit” under paraphrase.
Capabilities
Use the pack to harden evidence retrieval across compliance corpora: locate the right passages, preserve the meaning of qualifiers, and keep review trails consistent — even as narratives change form.
Evidence-first retrieval
Retrieve relevant fragments across case notes, alerts, screening logs, transaction narratives, and policy text. Keep “cleared” distinct from “hit”, and “not related” distinct from “related”, without relying on brittle keyword logic.
Cross-case similarity
Find prior cases with matching relationship language and narrative structure to support analyst triage, consistency checks, and faster investigations — with evidence grounded in the same configured signals.
Policy & procedure lookup
Map a case narrative to the most relevant internal procedures — including conditional clauses, exceptions, and required controls — so critical constraints don’t get missed in review.
Representative use cases
Day-one workflows you can deploy on top of your existing case management and document stack — powered by stronger encoding and retrieval over the text you already have.
False-positive hardening
Preserve “no match / false positive / cleared” semantics so resolved hits don’t resurface as active signals due to wording drift or paraphrasing.
Beneficial ownership evidence bundle
Gather the strongest fragments around ownership/control statements — including uncertainty and exceptions — to build a coherent, defensible evidence trail for review.
Narrative-to-policy mapping
Given an investigator narrative, retrieve the most relevant procedure sections and constraints to reduce missed steps and inconsistent application of rules.
Case consistency review
Compare a new write-up to prior cases with similar relationship language and reasoning structure to support consistent, auditable decisions across teams and time.
Deployment
Enable the AML/KYC pack in EvaCortex Lab cloud deployments, or deploy it on-prem / in a private VPC alongside your existing case management and data pipelines. Extend it with custom curation to align operator rules with your internal terminology, documentation style, and governance requirements.