Table of Contents
- What is banking regulation and why is it increasingly hard to manage
- Intesa Sanpaolo chooses Aptus.AI for banking regulation
- Why generic AI is not enough for banking regulation
- What Regulatory Change Management means for banks
- A step towards the democratisation of regulation
- FAQ: banking regulation and artificial intelligence
What is banking regulation and why is it increasingly hard to manage
Banking regulation is the body of rules, directives and circulars issued by national and international authorities — such as the Bank of Italy, the EBA and the ECB — that govern the operations of credit institutions. It covers prudential requirements, reporting obligations, anti-money laundering controls and standards of conduct towards clients.
The challenge for banks is not understanding any single rule. It is keeping pace with the volume: tens of thousands of regulatory updates every year, produced by hundreds of supervisory authorities across multiple jurisdictions. A flow that no traditional compliance structure can monitor manually without losing efficiency or exposing the institution to the risk of non-compliance.
Intesa Sanpaolo chooses Aptus.AI for banking regulation
Intesa Sanpaolo, one of the top five banking groups in Europe by total assets, has chosen Aptus.AI as its technology partner for automated regulatory management. The collaboration was designed by the Group Regulatory Evolution Agenda function with the support of Deloitte Risk Advisory.
As stated in the official Group announcement, the objective is to adopt a new operating model that makes the processes for defining the Group’s Regulatory Agenda more efficient and faster, allowing people to focus on high value-added analysis activities.
What Aptus.AI does for Intesa Sanpaolo
The platform supports four key processes in banking regulation management:
| Process | How Aptus.AI handles it |
|---|---|
| Regulatory monitoring | Automated tracking of new national and international regulations |
| Impact analysis | Assessment of the effects of each new rule on Group activities |
| Risk area mapping | Identification of correlations between external regulation and internal Group policies |
| Document collection | Automatic creation of customised dossiers by professional profile |
The expected outcome is faster and more accurate regulatory analysis, enabling the Group to save time and optimise its strategic decision-making process.
Why generic AI is not enough for banking regulation
One of the most common questions we receive from compliance and risk officers is: why is it not sufficient to use a generic language model to analyse regulation?
The answer is technical. Generic language models are trained on general-purpose text and do not have a structured legal data layer. When queried on specific banking regulation, they produce outputs that appear correct but are not anchored to verified regulatory sources. In a context where a misinterpretation can result in sanctions, inaccurate reporting to supervisory authorities or unmonitored risk positions, this margin of error is unacceptable.
Aptus.AI addresses the problem at its root with a different approach. The patented Legal Data Structuring Engine converts raw regulatory text into structured machine-readable data, creating a verifiable “Ground Truth” layer. The reasoning is deterministic: outputs are anchored to the regulation, not to probabilistic inference, and every result is traceable and verifiable.
What Regulatory Change Management means for banks
Regulatory Change Management is the process by which a bank identifies, analyses, implements and monitors regulatory changes that affect its operations. It is one of the most critical functions in any financial institution.
A complete cycle typically comprises five phases:
- Monitoring regulatory sources to identify new rules
- Analysis of the effect on internal processes, products and controls
- Identification of areas of non-compliance with the new regulation
- Planning of the corrective actions required
- Documentation and reporting to senior management and competent authorities
Traditionally this process is handled through manual procedures, spreadsheets and external consultancy, with high costs and significant delays. Aptus.AI automates the entire cycle, transforming compliance from a cost centre into a structured and scalable process.
A step towards the democratisation of regulation
As Aptus.AI CEO Andrea Tesei stated, being chosen by Intesa Sanpaolo from among startups from around the world is confirmation that a technology built to make law accessible can find concrete application even in the most complex institutions.
Aptus.AI’s vision goes beyond simply automating a process. It is about transforming compliance from a “cost centre” into a value generator, as underlined by Marcello Mentini, Executive Head of Group Regulatory Evolution Agenda at Intesa Sanpaolo, in his comments on the collaboration.
FAQ: banking regulation and artificial intelligence
What is banking regulation?
Banking regulation is the body of laws, regulations and provisions issued by national authorities such as the Bank of Italy and supranational bodies such as the EBA and ECB, governing the activity of credit institutions. It includes capital requirements, conduct obligations, anti-money laundering controls and prudential supervision standards.
What is the difference between vertical AI and generic AI for banking compliance?
Generic AI produces statistically plausible outputs that are not anchored to verified sources. Vertical AI for compliance operates on a structured legal data layer: every output is traceable to a specific regulation, making results verifiable and suitable for contexts subject to regulatory scrutiny.
What does Aptus.AI concretely do for banks?
Aptus.AI automates the Regulatory Change Management cycle: it monitors regulatory sources in real time, assesses the impact of new rules on internal processes, identifies risk areas and supports the production of structured reporting.
Does Intesa Sanpaolo really use Aptus.AI?
Yes. Intesa Sanpaolo has officially announced its collaboration with Aptus.AI for the management of the Group’s banking regulation, with the support of Deloitte Risk Advisory. The project was designed by the Group Regulatory Evolution Agenda function.
Is Aptus.AI reliable for a regulatory context?
Aptus.AI uses a patented legal data structuring engine that converts regulatory text into verifiable machine-readable data. The reasoning is deterministic and anchored to sources, not probabilistic like generic language models.
