Context in the decision
A decision is made against related entities rather than a single record.
Risk & Fraud
Transactions, relationships and decisions on one clock.
Fraud is a relationship pattern, and risk is a decision made under a deadline. Both suffer when the relationships arrive from another system.
A decision under a deadline, made against a network rather than a record.
Decisions made across transactions, entities and their relationships.
Detection reads transactions, behavioural signals and the links between entities, then writes a case. PLOMID is designed to hold the signals, the relationships and the case record in one layer, so a decision and its justification are produced together.
A decision under a deadline, made against a network rather than a record.
Environment
The transaction
Payments and postings arriving with their behavioural measurements.
SQL · Time series
Two estates, drawn.
The same shapes, held two ways. The difference is not the storage, it is where the agreement between them lives.
Separate systems Copies kept in step
One layer One plan · one contract
What this workload moves.
Every shape below is a surface of the layer, not a format to be converted into one. They are read and written together.
- Graph Relationships and traversal
- Time series Measurements and events in time order
- SQL Records, keys and joins
- JSON / documents Documents and nested objects
How the workload reaches the data.
The models this workload names, the path a request takes through them, and the surfaces that speak to the layer.
Risk & Fraud · architecture
Workload
The shape of the work itself.
- Signal
- Link
- Decide
- Record
Data models
The models this workload names.
- Graph
- Time series
- SQL
- JSON / documents
The layer
One path from a request to the data it names.
- Planning Predicates narrow the work before it runs
- Execution Rows, fields and windows answered together
- Transactions Readers and writers do not block each other
Surfaces
How the workload reaches the layer.
- SQL surface The query language the layer is documented in
- Applications Services and jobs reading and writing as they run
- Analytics & AI clients The same layer, the same access path
The work, stage by stage.
Choose a stage to read what happens there, or a shape to see every stage that handles it. Nothing on the map is a private interface.
PLOMID · Risk & Fraud signal · link · decide · record Select a stage
Stage
Signal
Transactional records and behavioural measurements
SQL · Time series
01
Signal
Transactional records and behavioural measurements
- SQL
- Time series
02
Link
Shared attributes and counterparties as relationships
- Graph
03
Decide
Rules and models applied to the linked view
- Graph
- Time series
04
Record
The case, its evidence and its outcome
- JSON / documents
- SQL
What changes when the data is in one place.
Stated as properties of the system rather than as results we cannot measure for you.
Explanation stored
The reasoning and its inputs are written to the same layer that produced them.
Feedback loop
Outcomes become data for the next decision without an export.
One place to audit
A reviewer reads the same layer the model read.
What this is built on.
Risk decisions are judged on explainability. These are the parts of the layer that provide it.
- Relationships held as data → Edges expressed directly remove the reconstruction that happens at query time when relationships live in a join.
- Retrieval as an access path → Similarity search arrives as another way into the same data rather than a second copy to keep in step.
- Snapshot reads under continuous writes → Readers and writers do not block each other, which is what makes a telemetry feed and an application share one system.
- One data layer → Rows, documents and time-ordered events live in one system, so a question is asked once instead of once per store.
Workloads that sit beside this one.
Where this shows up.
Derived from the industry pages that reference this solution, so the two directions of the relationship always agree.
- Banking → Accounts, transactions, counterparties and the relationships between them.
- Payments → Authorisations, clearing, settlement, routing and fraud signals.
- Insurance → Policies, claims, risk factors and the documents behind every decision.
- Fintech → Ledgers, balances, product events and the relationships behind them.
- Risk & Fraud → Signals, relationships, cases and decisions across an institution’s data.
- Cybersecurity → Telemetry, identity, asset relationships and the cases that follow.