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Devancore Post-Trade Glossary

Natural Language Portfolio Questions

Natural language portfolio questions let institutional users ask about positions, cash, exposure, performance, restrictions, and breaks while the answer remains grounded in controlled portfolio records.

Definition

Natural language portfolio questions are controlled queries over institutional portfolio records. A user can ask about positions, cash, exposure, performance, restrictions, unsettled trades, fees, tax lots, corporate actions, or reconciliation breaks without writing SQL, building a spreadsheet, or waiting for a custom report.

The control problem is precision. A question that sounds simple can depend on different books of record. "How much cash do we have?" may mean settled cash at the custodian, projected cash after pending trades, accounting cash in ABOR, or available cash after restrictions and collateral. "What is our Apple exposure?" may mean issuer exposure, equity position, option delta, sector weight, currency exposure, or mandate concentration.

Portfolio question to source record

Portfolio question to source record

A useful answer starts by identifying the book, scope, time, and calculation basis.

Question type Record needed Control question
Position IBOR position, account, fund, security, quantity, location, trade date, and settlement date Which book and date define the holding?
Cash Settled cash, projected cash, ledger cash, currency, bank or custodian source, and pending movements Is the answer using available, projected, or accounting cash?
Exposure Position, price, FX, issuer, country, sector, strategy, derivative mapping, and risk factor Which taxonomy and valuation source created the exposure?
Performance PBOR return, benchmark, weights, prices, FX, cash flows, income, fees, and attribution method Can the return explanation be reconstructed?
Restriction Mandate rule, restricted list, account eligibility, concentration limit, override, and approval state Is the question testing policy or only describing data?
Break Reconciliation item, source records, owner, age, reason code, materiality, and evidence bundle Is the difference open, explained, escalated, or closed?

A natural-language answer should start by resolving four things: portfolio scope, book basis, time basis, and calculation basis. Scope determines which funds, sleeves, accounts, entities, or strategies the user is allowed to query. Book basis determines whether the answer comes from IBOR, ABOR, PBOR, custodian records, risk data, or a reconciled view across them. Time basis determines whether the answer is current, end-of-day, as-of a historical date, or as-at what the firm knew at a specific timestamp. Calculation basis determines how prices, FX rates, benchmarks, accrued income, pending trades, fees, and overrides are handled.

The distinction between record interrogation and action is important. A portfolio question asks what the controlled records show. It may reveal a break, restriction, liquidity issue, stale price, or exposure concentration. That does not make the answer an approved trade, accounting entry, cash movement, or exception closure. If the user wants to act on the answer, the workflow should create a separate draft, validation, review, and approval path.

Good portfolio answers include citations. A response such as "cash is lower because of unsettled purchases" is not enough for institutional operations. The answer should identify the accounts, currencies, trades, cash movements, settlement dates, source systems, timestamps, and unresolved breaks that support the statement. Without that evidence, natural language becomes another reporting surface that teams must manually verify.

Portfolio questions - record dependency map

Devancore · message matrix

Rail Message Purpose Record
Holdings what do we own? position answer IBOR position, account, security, quantity, custodian, trade date, and settlement date
Cash what can we use? liquidity answer settled cash, projected cash, ledger cash, pending movements, currency, and source timestamp
Exposure where is the risk? risk answer issuer, sector, country, currency, derivative mapping, price, FX, and risk-factor data
Return why did it move? performance answer PBOR return, benchmark, weights, cash flows, income, fees, attribution method, and exceptions
Breaks what is unresolved? operations answer reconciliation item, source rows, owner, aging, reason code, materiality, and evidence

How it works

Natural language portfolio questions work by turning a plain-language request into a governed data query. The workflow scopes the user, interprets the question, retrieves permitted records, calculates the answer, returns source-grounded text, and records the question-answer pair.

Natural-language portfolio query controls

Natural-language portfolio query controls

The workflow should convert a question into a deterministic answer request.

Step What the system resolves Evidence retained
Scope User, role, desk, fund, account, portfolio hierarchy, permitted fields, and data domain Entitlement result and denied fields
Interpret Intent, book basis, metric, date range, currency, aggregation, filters, and ambiguous terms Parsed query, missing fields, and clarification state
Retrieve IBOR, ABOR, PBOR, cash, position, price, benchmark, restriction, settlement, and break records Source system, record IDs, version, and as-of timestamp
Calculate Exposure, cash view, P&L, return, aging, limit result, or reconciliation status Formula, input set, currency, price source, FX source, and calculation timestamp
Answer Plain-language explanation with cited records and warnings Displayed answer, cited IDs, stale-data flags, and user session
Route Follow-up query, export, task draft, exception note, or action request Boundary between answer, draft, approval, and downstream workflow

Scoping runs before retrieval. A portfolio manager, operations analyst, controller, compliance user, and executive may have different portfolio access, field access, and permitted actions. The system should not retrieve records the user is not entitled to see and then rely on the model to hide them in the final answer.

Interpretation converts human phrasing into a structured answer request. The system should resolve portfolio name, account, security identifier, issuer, currency, date, aggregation, metric, and book basis. If the wording is ambiguous, it should ask for clarification or show the assumption. It should not silently choose between IBOR and ABOR, settled and projected cash, trade-date and settlement-date positions, or current and historical knowledge.

Retrieval gathers the source records needed for the answer. Depending on the question, the workflow may pull positions, trades, cash balances, prices, FX rates, benchmarks, classifications, restrictions, tax lots, settlement status, corporate actions, and open breaks. Each retrieved data set should carry source, timestamp, version where available, and record identifiers.

Calculation should be deterministic. AI can explain the result, but the math should come from defined calculation logic: sum positions, convert currency, aggregate exposure, apply benchmark weights, calculate return, age breaks, or compare cash views. The answer should show the as-of timestamp and the calculation basis so users know whether the number reflects current operating state, prior close, or corrected historical knowledge.

Answer generation translates the result into usable language. The answer should include citations, warnings, unresolved data-quality issues, stale-source flags, and drill-through records. If a citation references a trade, account, CUSIP, cash movement, or break ID, the system should validate that the referenced record exists before showing it.

Routing handles follow-up. The user may ask another question, export evidence, create a task, draft an exception note, or request an action. Those follow-ups should preserve the original question, retrieved context, answer, citations, and timestamp. Any order, correction, override, or close decision should move into its own approval workflow.

In Devancore™

Devancore supports natural language portfolio questions as a governed query layer over operating records. The platform can help users ask about positions, cash, exposure, performance, restrictions, settlement state, and reconciliation breaks while keeping the answer connected to source records.

Devancore should not be framed as an investment adviser, portfolio manager, broker, custodian, accounting authority, performance standard-setter, or autonomous trading engine. Its role is to help firms expose controlled portfolio records through permissioned, cited, and auditable workflows.

In a Devancore-style workflow, the user asks a question. The system checks entitlement, resolves portfolio scope, selects the relevant book, retrieves permitted records, applies deterministic calculations, generates an answer with citations, and stores the full question-answer record. The answer can then feed a task draft, exception workflow, reconciliation review, compliance check, or report without losing lineage.

This page complements the conversational finance cluster by focusing on the portfolio inquiry surface. Conversational finance describes the broader interface. Conversational books and records explains governed access to regulated records. Natural language portfolio questions explains how investment teams, operations teams, controllers, and risk users ask practical questions about portfolio state and receive answers that can be checked.

The useful product boundary is simple: answer with evidence, then route action through controls. A natural-language answer may reveal that cash is short, a position is stale, a restriction is breached, a performance number moved, or a break is aging. The platform should help the user understand that state, cite the records behind it, and move the next step into a controlled workflow.