Financial Services
Transactions, counterparties and risk, read as they happen.
Financial work is eventful by nature: an authorisation, a settlement, a claim, a decision. Each one is a record with a time and a counterparty, and the useful questions are asked across both at once.
Transactions, counterparties and risk, read as they happen.
From the transaction to everything it touches.
Every movement carries a record, and the record has to be reconstructable later. Four readings of the same system, starting where the question starts: the movement, the shapes around it, the layer it lands on, and the decisions answered from it.
The contexts this industry runs in.
- 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.
The shapes the data takes across them.
- SQL Records, keys and joins
- Graph Relationships and traversal
- Time series Measurements and events in time order
- JSON / documents Documents and nested objects
- Objects Large assets with queryable metadata
Where the shapes stop being separate systems.
- One plan per request
- Snapshot reads under continuous writes
- One storage contract
The questions asked across the industry.
- Exposure across a network
- Anomaly with context
- Consistent books under load
- Case evidence
One layer holds these shapes at once, which is what removes the copy between them: an event, the record it belongs to and the document around it are read from the same place, whichever environment is asking.
Where this industry runs.
The environments this industry runs in. All of them write events continuously and answer questions about them afterwards, which is what makes the read path the hard part rather than the write path.
- 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.
What runs against financial data.
Workloads drawn from every environment in this industry. Choose one to see the shapes it moves and where it lands.
Postings, holds, balances and statements as records. — Banking
- Planned once against the layer, not once per store
- Read beside the records it shares a key with
- Persisted under one storage contract
Latency, channel, merchant and device measurements. — Banking
- Planned once against the layer, not once per store
- Read beside the records it shares a key with
- Persisted under one storage contract
Customers, accounts, devices, counterparties and beneficial owners. — Banking
- Planned once against the layer, not once per store
- Read beside the records it shares a key with
- Persisted under one storage contract
Reviews, decisions, policies and correspondence. — Banking
- Planned once against the layer, not once per store
- Read beside the records it shares a key with
- Persisted under one storage contract
Requests, responses, clearing files and settlement positions. — Payments
- Planned once against the layer, not once per store
- Read beside the records it shares a key with
- Persisted under one storage contract
Latency, success rate, issuer response and retry measurements. — Payments
- Planned once against the layer, not once per store
- Read beside the records it shares a key with
- Persisted under one storage contract
Merchants, acquirers, schemes and their relationships. — Payments
- Planned once against the layer, not once per store
- Read beside the records it shares a key with
- Persisted under one storage contract
Chargebacks, evidence, correspondence and decisions. — Payments
- Planned once against the layer, not once per store
- Read beside the records it shares a key with
- Persisted under one storage contract
Which workload touches which model.
The work, the shapes it names, and the path a request takes to reach them — including the relationships a ledger has to traverse, carried with the roadmap treatment where they are still being built.
What runs against this data.
- Transactions and balances
- Signals over transactions
- Party relationships
- Case and policy documents
- Authorisation and settlement records
The shapes those workloads read and write.
- SQL
- Graph
- Time series
- JSON / documents
- Objects
One path from a request to the data it names.
- Planning Predicates narrow the work before it runs
- Execution Records, fields and windows answered together
- Transactions Readers and writers do not block each other
How the work reaches the layer.
- SQL surface The query language the layer is documented in
- Applications Services and jobs writing and reading as they run
- Analytics & AI clients The same layer, the same access path
The parts of the layer this industry leans on.
Counted across the environments above rather than chosen for this page: the properties every environment in this industry depends on, and the workload answers they keep returning to.
- One data layer Rows, documents and time-ordered events live in one system, so a question is asked once instead of once per store.
- 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.
- Relationships held as data Edges expressed directly remove the reconstruction that happens at query time when relationships live in a join.
- One storage contract Every model inherits the same durability and recovery rules instead of one guarantee per system.
- One plan per request A request is planned once against the layer rather than per system, which is where cross-system glue usually accumulates.
- A public surface from the start The SQL surface, the documentation and a browser playground exist today. Nothing described here needs a private API.
Solutions this industry keeps returning to.
Derived from the industry's own environments: the solutions referenced by the most of them, each one a page of its own.
- Risk & Fraud → Decisions made across transactions, entities and their relationships. Referenced by 5 of 5 environments.
- Real-time Analytics → Windows and aggregates over data that is still being written. Referenced by 4 of 5 environments.
- Transactional Systems → Application records with consistent reads and writes while reports run against them. Referenced by 3 of 5 environments.
- Operational Analytics → Reporting that reads the operational source instead of a copy of it. Referenced by 3 of 5 environments.
- Enterprise AI → AI features across an organisation’s systems, with access rules that hold. Referenced by 2 of 5 environments.
- Enterprise Search → One search surface over records, documents, events and their metadata. Referenced by 2 of 5 environments.
- BankingAccounts, transactions, counterparties and the relationships between them.
- PaymentsAuthorisations, clearing, settlement, routing and fraud signals.
- InsurancePolicies, claims, risk factors and the documents behind every decision.
- FintechLedgers, balances, product events and the relationships behind them.
- Risk & FraudSignals, relationships, cases and decisions across an institution’s data.
Every movement, reconstructable.
Tell us which ledgers, rails and risk surfaces you run and who has to reconstruct them later. We will map them to the workloads, the shapes and the parts of the layer that carry them.