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Building the Bank from the Top Down, Appendix D: Glossary, sources and claims register

Part 7 of 8 of Building the Bank from the Top Down. The main paper makes the argument; this part holds the detail.

D1. Glossary

Term Meaning
AISP / PISP Account information and payment initiation service providers: the licensed third parties allowed to read accounts or initiate payments
Apex The customer-facing point where intent, context and value are coordinated. Related to, but not the same as, the upper tiers of Bain's pyramid and the top of a Wardley value chain (Section 2.1; Appendix A2)
Autonomy ladder Seven rungs from observe to execute autonomously; each action's rung depends on risk, reversibility, value and confidence (Appendix C3.3)
Baggage disintermediation Risk scenario: an agent captures the relationship while the bank retains much of the ledger, capital and compliance cost
Claims register Appendix D4: each load-bearing claim with its status (fact, evidence, interpretation or hypothesis), basis and test
Core-led / outcome-led Transformation where customer value waits for core modernisation to finish, versus transformation that starts from a customer outcome and invests in the core only where a named need requires it
Cost-to-income ratio Operating costs divided by operating income; lower is more efficient
DORA EU Digital Operational Resilience Act, applied from 17 January 2025
FiDA Proposed EU Financial Data Access regulation extending open banking to open finance
Kill criteria Pilot thresholds that trigger a shift of weight from market A to market B if missed at month 9 (Appendix C3.1)
Market A / market B The two products of one platform: A is the bank's own agent, competing for the customer's interface; B is the trust layer beneath every agent (Section 3.1; Appendix C1)
North Star A customer outcome, enabled by AI, used to decide which programmes get funded
PFA Personal Finance Agent: an AI agent that plans and acts on a customer's finances with their consent
PSD3 / PSR The EU's third Payment Services Directive and the Payment Services Regulation, replacing PSD2
SCA Strong customer authentication: two-factor authentication required for account access and payments
Semantic control plane The controlled chain that turns raw legacy data into canonical concepts, evidence and verified claims
Technical annex (T1 to T7) The second tab: agent control architecture, autonomy ladder, authentication, liability, failure scenarios, semantic control plane and a stress test against legacy cores
Trust layer Identity, verified claims, consent, delegation and liability, offered to the bank's own agent and to any other agent the customer authorises
Trustworthiness / assurance / liability The three questions trust answers: is the system reliable, can that be verified, and who pays if it is not (Appendix C1.3)
Verified financial claim A signed, purpose-bound, revocable statement from the bank, such as "income above €3,000", issued instead of raw data

D2. Sources

D3. Author's related work

Article What it adds to this paper
Enterprise Digital Office (EDO), July 2025 The operating system behind the method: Wardley maps to start every initiative, backlogs tagged to Bain's value tiers, five immutable gates and spend targets (Appendix B1, C2 and C7)
The Answer Layer, September 2026 How AI answer engines form a new layer between firms and customers, and how to test whether agents can complete tasks through a firm (Appendix C1)
Bespoke Platform Engineering (BPE), July 2025 Hypergraph and ontology patterns for reading legacy data, agents as first-class clients of platform services, and inspectable audit trails (Appendix C3 and C5)

D4. Claims register

Every load-bearing claim in the paper carries one of four labels. Fact: verifiable from law or published data. Evidence: supported by published data, with limits on scope or interpretation. Interpretation: the author's reading of facts or law. Hypothesis: a claim about causes or the future that the paper cannot yet support. Each claim below names its basis and the test that would confirm or overturn it.

# Claim Status Basis Test Where (main section; appendix)
1 Nearly 70% of bank IT spend goes to running existing systems and regulation Evidence (global figure) Accenture, 2026 Banking Trends The bank's own run-versus-change split 1; A1.1
2 Banking technology costs grew about four times faster than revenue over 15 years Evidence Accenture The bank's own cost and revenue series 1; A1.2
3 Cost-to-income is about 65% in France, 58% in Belgium, 53% in the Netherlands Fact (read from a chart, approximate) EBA Risk Dashboard Q1 2026 None needed 1; A1.3
4 The run burden limits what incumbents can redirect to new customer value Hypothesis Consistent with claims 1 to 3; not shown causally Apex share of change spend over time (Appendix C2.3) A1.1
5 PSD3 and the PSR require dedicated interfaces, list banned obstacles and introduce permission dashboards Fact Final texts agreed April 2026; Norton Rose Fulbright, Morrison Foerster None needed 2.3; B2.1
6 AI Act high-risk rules apply from December 2027; PSR core obligations around H1 2028 Evidence (planning assumption) Regulation-AI.eu; Sopra Steria Re-check at each roadmap gate 2.4; C5.2
7 Agent-initiated payments collide with SCA, which needs a known amount and payee Evidence RTS on SCA; Sopra Steria Final PSR technical standards on delegated payments 2.3; B2.2
8 In past technology waves, challengers rented the new commodity and built above it Interpretation Five cases in Appendix B1.4; illustrative, not proof Not testable in advance 2.2; B1
9 An outside agent could capture the relationship while the bank keeps the cost Hypothesis Seven-step chain; steps 1 to 3 technically possible Share of interactions in bank channels; third-party API calls 2.3; B2.4
10 Customers reward multi-element and upper-tier value with loyalty Evidence (general, not AI-specific) Bain, 2018 Retention of pilot users against a control group 1; A2.1
11 An AI agent can deliver emotional value such as reduced anxiety at scale Hypothesis Chain in Appendix A2.3 Perceived control and anxiety in the first release; behaviour over 6 to 12 months 2.1; A2.3
12 As AI makes answers nearly free, an answer a person can safely act on becomes scarce Hypothesis Reasoning in Appendix C1.2 Whether relying parties pay for verified claims C1.2
13 Banks start ahead on assurance and liability, behind on AI trustworthiness Interpretation Trust stack, Appendix C1.3 Pilot trust score; model incident rate 3.1; C1.3
14 A bank's lasting edge is vouching for facts and paying if they are wrong Hypothesis: the paper's central claim Appendix C1.4 and C1.5 Share of relying parties accepting non-bank claims on equal terms; price per claim; claims per consented customer 3.2, 3.5; C1.5, C6
15 The consent router and permission dashboard are a likely moat Interpretation PSR dashboard obligation; Map 2 Share of customer consents managed through the bank C3.4
16 Customers will choose the bank's agent over a free general assistant Hypothesis Six advantages, Appendix C3.1 Active and repeat use; the month-9 kill criteria against a general assistant C3.1
17 Outcome-led delivery reaches first customer value in quarters, not years Hypothesis (working estimate) Dependency analysis, Appendix C3.6 Time to first customer value in the first release 3.4; C3.6
18 An agent customer can be worth more than they cost Hypothesis (illustrative model only) Appendix C3.7 Pilot economics against a matched control group; the Scale gate 3.4; C3.7
19 Verified claims stay an edge only if they become infrastructure outside agents must call Hypothesis Four conditions, Appendix C1.5 Share of outside agents' high-value journeys that call the bank's claim service; relying parties integrated 3.2; C1.5

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