Practical Data Science in Financial Supervision
The Cambridge SupTech Lab accelerates the digital transformation of financial supervision, with a focus on building resilient, inclusive, and accountable financial sectors.
The future of financial supervision is data-driven intelligence
This course is designed to bridge that gap. It equips financial supervisors with practical knowledge of data science methodologies, while offering experienced, socially conscious data scientists a pathway to contribute meaningfully to public interest outcomes. Together, they will help shape a new generation of suptech applications that make supervision smarter, faster, and more responsive.
Online
Self-paced
Asynchronous
6 weeks
7h/week
This training is for You, if you
- Hold a leadership role in a private or public sector orgranisation or are an aspiring analyst looking to enter the field of data science.
- Seek to drive the strategic direction, application, and responsible use of data science to address real world supervisory challenges.
- Are eager to broaden your understanding and skills in data science, applying it to various supervisory use cases and emerging technologies.
- Aspiring to enhance your data science capabilities by working with live data sets, advanced tools, and innovative techniques, while embracing interdisciplinary roles and approaches.
Testimonials
Upcoming 5th cohort starts on
6 October 2025
- Practical, hands-on familiarity with data science, encompassing advanced analytics, data strategy, and management roles, providing you with the expertise to explore application opportunities beyond the course within the context of financial supervision
- Proficiency in utilising advanced analytics and machine learning techniques to extract meaningful intelligence from raw data, enabling you to make data-driven strategic decisions with precision and confidence
- Enhanced technical skills in data science, including familiarity with relevant programming languages, data manipulation, and statistical modeling, equipping you with the necessary tools to excel in data-driven environments
- A deep understanding of data governance and ethics, ensuring you can responsibly handle sensitive data and comply with regulatory requirements while leveraging data science for improved financial supervision
- The ability to effectively communicate complex data-driven insights to both technical and non-technical stakeholders, enabling you to bridge the gap between data science expertise and practical application in financial supervision
Curriculum
Get oriented and inspired
- Develop an understanding of the context and importance of data science in financial supervision
- Identify reasons for data science increasing significance in the field of financial supervision
- Distinguish the value proposition of data science for both financial supervisors and data scientists
- Feel inspired to think beyond the boundaries of existing roles towards an inter-disciplinary perspective
1 week
Data science as suptech: a primer
- Describe data science roles, tools, and best practices
- Discuss and explain the SupTech Taxonomy and SupTech Generations models and their application
- Identify key applications of data science in the context of suptech
3 weeks
Data science in the wild: hands-on suptech case studies
Three interactive case studies & data gymnasium
- Identify the supervisory value proposition of the data science solution
- Practice via interactive data science notebooks the technical details of the implementation and tools utilized
- Investigate and compare the implications of changing parameters in the synthetic model version
1 week
Deploying data science products in the supervisory context
- Define the importance of the responsible use of data science tools and technologies
- Identify the ethical considerations when using data science in financial supervision
- Categorize data science management and team structure in financial supervision
- Weigh opportunities for capacity and skills application within institutional and supervisory contexts
The capstone project offers you a unique opportunity to integrate your learning, showcase expertise, and create tangible value for your organisation. Throughout the project, you will build a conceptual brief on a proposed application of data science in supervision, drawing from the diverse portfolio of solutions provided by the Data Gymnasium. These solutions encompass various models, tools, and techniques such as supervised and unsupervised machine learning, trend analysis, sentiment analysis, network analysis, natural language processing (NLP), and image processing.
Demonstrating your critical thinking skills and applying new analytical frameworks to address supervisory challenges within your organisation, you will make strategic decisions on the deployment of new technologies and data science to effectively tackle these challenges.
DATA SCIENCE
CAPACITY
- Actively explore the value of interdisciplinary collaboration between financial supervisors and data scientists and understand why this collaboration is increasingly relevant in today’s landscape
- Gain a practical understanding of the roles, tools, and best practices involved in building and deploying advanced analytics tools, machine learning models, and other suptech data products
- Apply the SupTech Taxonomy and SupTech Generations frameworks introduced in our State of SupTech Report to develop a strategic approach for building data science roadmaps, assembling teams, and creating products that can be utilised in financial supervision beyond the course
- Delve into three practical examples of data science in suptech, dedicating one week to each example
- Identify the specific supervisory value proposition of each data science solution, gaining a clear understanding of how it can enhance financial supervision
- Learn the technical intricacies of implementing each solution and become proficient in employing the appropriate tools for data analysis and modeling
- Gain an understanding of the implications of altering parameters within synthetic versions of the models, allowing you to grasp the broader impact of such changes on the effectiveness of the solutions
Tuition Fee
Financial Authorities
£1,600/person
5 seats minimum
Individuals
£1,800
Financial Assistance
Financial assistance might be available for participants from emerging economies and developing countries. If funding represents a challenge, please connect with us.
DISCOUNTS FOR INDIVIDUALS
ENROLL IN 2 PROGRAMMES
£1,600*
ENROL IN 3 PROGRAMMES
£1,200*
*TUITION FEE PER PROGRAMME
The training programme is open to all individuals who currently hold positions such as supervisor, regulator, policymaker, economist, examiner, actuary, analyst, data scientist, or technologist within regulatory, supervisory, or policymaking authorities.
We highly encourage agencies to enrol individuals representative of the various roles relevant for the development of a suptech application, roadmap, strategy, open data project, innovation hub, or digital transformation initiative. Take special note of the discounted tuition fee for enrolment of 5 people or more.
Power your transformation!
GovSpace is our collaborative platform for data-driven diagnostics, co-design, and digital solution deployment. Built to power digital transformation and innovation across the SupTech ecosystem.
A community of communities that connects local priorities and innovation leaders to peers and global partners.
GovSpace will soon unify digital tools, knowledge assets, and collaboration environments developed by the Cambridge SupTech Lab into one secure and immersive AI-powered space.
As we transition, you may notice tools and services gradually moving under the GovSpace banner.
