Algorithmic Sovereignty in Digital Banking

Abstract

Digital banks increasingly use machine learning and generative AI inside decisions that affect access to credit, fraud interventions, financial-crime controls, customer support and internal operations. The principal governance problem is not that regulators have demanded a single form of ‘explainable AI’. It is that a regulated firm must be able to identify which legal obligations apply to a particular use of a system, allocate responsibility, constrain execution, preserve evidence and respond when the model, data, product or law changes. This paper calls the capability to do so algorithmic sovereignty: the institution’s practical ability to govern automated decisions throughout their lifecycle rather than merely consume opaque outputs.The paper develops a UK–EU framework for converting regulatory sources into versioned obligations, testable controls and decision-level evidence. It corrects two common overstatements. First, the EU AI Act does not classify every banking model as high-risk, and the United Kingdom has not created a general AI Act for financial services. Secondly, deterministic rules or formal proofs do not make a system legally compliant by themselves. They can prove properties of an encoded specification, but the specification, facts, institutional process and legal interpretation remain contestable.A hybrid architecture is proposed: probabilistic systems perform perception, prediction and drafting; a deterministic policy layer evaluates structured facts against versioned rules; a separate evidence layer records inputs, model and policy versions, reasons, overrides and outcomes. Logic-based and formal methods—including Datalog, policy-as-code languages, SMT solvers and proof assistants—are useful in selected parts of this control plane. They are not a replacement for statistical models, legal judgment, data governance or meaningful human review. The result is a narrower but more defensible thesis: compliance can become partially executable and continuously testable, provided the organisation treats code as one controlled representation of law rather than law itself.