Exploring the future of financial data architecture: AI-native financial data foundation, large-scale financial data processing, and financial AI safety & governance
As discussed in the previous article, the CDM Event Model is built around state transitions: a TradeState, an Instruction carrying primitive changes, and a resulting after TradeState. Nine primitives compose into business events. A partial novation, for example, is three primitives in one BusinessEvent producing two after-states. This article starts with an end-to-end example - … Continue reading AI-Native Financial Data Foundation (23) – The Full Lifecycle, Lineage, and Two Kinds of Change
The previous article argued that lifecycle modelling should move from event labels to state transitions: before state plus instruction produces after state. This article makes that concrete. First, the two types that sit at the centre of every lifecycle event — Trade and TradeState. Then, the nine primitives that change them. Trade and TradeState A Trade extends TradableProduct. … Continue reading AI-Native Financial Data Foundation (22) – Trade, TradeState, and the Primitives That Change Them
In the previous articles, I spent a lot of time discussing the static structure of financial products. We looked at product nature, economic terms, payouts, price, quantity, schedules, settlement terms, and product qualification. The main question explored was: what is this financial product, structurally and economically? That was a necessary foundation. If an AI-native financial … Continue reading AI-Native Financial Data Foundation (21) — From Product Definition to Trade Lifecycle
The previous articles traced the eight payout types and how they compose into products. An IRS is two InterestRatePayouts. A CDS is an InterestRatePayout plus a CreditDefaultPayout. A commodity swap is a FixedPricePayout plus a CommodityPayout. But if the product type is expressed only through composition, how does a system know what to call it? … Continue reading AI-Native Financial Data Foundation (20) — Product Qualification: The Product Is What Its Structure Says It Is
The previous articles traced six extensions of PayoutBase. This article covers the final two: CommodityPayout and FixedPricePayout. They belong together because they are the fixed and floating legs of a commodity swap — the same compositional pattern as an IRS, but for physical goods rather than interest rates. One leg pays a fixed price per unit. The other … Continue reading AI-Native Financial Data Foundation (19) – CommodityPayout and FixedPricePayout
The previous articles traced five extensions of PayoutBase: InterestRatePayout (scheduled) CreditDefaultPayout (contingent) OptionPayout (conditional) SettlementPayout (deterministic) and PerformancePayout (performance-based). This article covers the sixth: AssetPayout (collateral-based). At its core, AssetPayout models the movement of securities against cash — a repo, a reverse repo, a securities lending transaction, a buy/sell-back. Where every other payout type is about cash flows, AssetPayout is about asset flows. Securities … Continue reading AI-Native Financial Data Foundation (18) – AssetPayout: Securities Financing, Repo and Asset-Based Obligations
The previous articles traced four extensions of PayoutBase: InterestRatePayout (scheduled) CreditDefaultPayout (contingent) OptionPayout (conditional) SettlementPayout (deterministic). This article covers the fifth: PerformancePayout (performance-based). At its core, PerformancePayout models a payment determined by the observed performance of a market observable — the appreciation of a stock, the dividends paid by an index, the realised variance of a currency pair, the correlation within a … Continue reading AI-Native Financial Data Foundation (17) – PerformancePayout: Modelling Return-Based Products
The previous articles traced three extensions of PayoutBase, InterestRatePayout (scheduled), CreditDefaultPayout (contingent), and OptionPayout (conditional). This article covers the fourth and simplest: SettlementPayout (deterministic). At its core, SettlementPayout models a forward commitment. Two parties agree today to exchange one thing for another at a fixed price on a future date. Both are obligated. Neither has a choice. No schedule. No contingency. … Continue reading AI-Native Financial Data Foundation (16) – SettlementPayout: From Trade Terms to Asset Settlement
The previous article introduced the business meaning of OptionPayout — a conditional right attached to anything, appearing in three structural roles across products. This article walks through the type structure itself: the attributes, how they map to the four stages of F-PAL framework, and how they differ from the InterestRatePayout and CreditDefaultPayout structures we have … Continue reading AI-Native Financial Data Foundation (15) – OptionPayout: The Structure and Composition
The previous articles traced two extensions of PayoutBase: InterestRatePayout (scheduled) and CreditDefaultPayout (contingent). This article introduces a third: OptionPayout (conditional). At its core, OptionPayout models a right, not an obligation. Someone holds the right to do something. Someone else bears the obligation if that right is exercised. The right may be exercised on a single date, on multiple dates, or continuously … Continue reading AI-Native Financial Data Foundation (14) – OptionPayout: Business Meaning and Product Examples
Data Ninjago (Financial Data Architecture) 
You must be logged in to post a comment.