- Utilising synthetic data to supercharge innovation in financial servicesThe Bayes Centre, The University of Edinburgh, Edinburgh
Data drives good decisions, it is critical to innovation… but what if the data doesn't exist or is locked away behind layers of financial legislation and compliance?
This Fireside Chat will consider the opportunities to breakdown barriers and accelerate innovation in FinTech and financial services through the adoption and utilisation of synthetic data sets.
Key discussion points will include:
-Data access, data sharing and innovation in financial services
-Data privacy and risk management
-Delivering impact with synthetic data
-Risks and limitations of synthetic data
Marilena Karanika, Head of Data Innovation, Experian
Marilena Karanika is the Head of Data Innovation at Experian, providing data and analytics support across different product domains such as affordability, credit risk and insurance.
With more than 10 years of experience in Credit Risk Modelling and Analytics in financial services, a key area of her expertise is enabling organisations to make better use of data, reach more informed decisions and support consumers throughout the customer lifecycle. Most recently Marilena and her team created and launched products that helped clients understand the impact of events such as the Cost of Living crisis and COVID to help them navigate these challenging times.
Marilena is passionate about the power of financial education and works with universities and professional bodies to deliver guest lectures and industry talks promoting a better and wider understanding of analytics and responsible data ownership. She has been voted Innovator of the Year 2021 in the Women in Credit Awards.
David Tracy, Head of Data Product, Smart Data Foundry
At Smart Data Foundry, David is responsible for leading the product development team. His main objective is to utilise financial data in order to gain insight into how individuals and businesses manage their finances. David collaborates with government institutions, banks, charities, fintech and academics to make more informed decisions, develop better policies and create superior products that will ultimately lead to improved outcomes.
Prior to joining Smart Data Foundry, David held the position of leading the Data Science and Innovation team for the UK Consumer data division at Experian. He has also gained extensive experience in the banking and insurance financial services industry, as well as contributing to the success of start-ups such as FanDuel and Castlight Financial.
Robin Huggins, Director of Client Services, MBN Solutions
As Director of Client Services for MBN Solutions, Rob has spent over two decades at the sharp end of Talent Acquisition practice for the Data sector.
During this time, he has partnered with some of the UK’s leading data-driven businesses to deliver best-in-class talent solutions. In addition, working in an advisory capacity, Rob designed, built, and delivered the Data Lab’s MSc Placement Programme, has contributed to forums including Scotland’s AI Strategy and DMA Council and sits on University of Glasgow’s School of Maths & Stats Industrial Advisory Board.
A regular data industry blogger and event host, Rob also now hosts a data leadership focussed podcast called Boss’n’Data and has been recognised by Data IQ as one of their 100 most influential Data and Analytics practitioners in UK organisations for two years running.
Can you please also register here so we can monitor the numbers of attendees - Utilising synthetic data to supercharge innovation in financial services Tickets, Thu 28 Sep 2023 at 18:00 | Eventbrite
- AI Fairness: Measuring and mitigating social bias in automated decision-making..Needs location
AI Fairness: Measuring and mitigating social bias in automated decision-making models
Please register here, its helps us keep an eye of the numbers - AI Fairness: Measuring and mitigating social bias in automated decision-mak Tickets, Thu 12 Oct 2023 at 18:00 | Eventbrite
Automated models are extremely efficient in predicting human behavior. Unfortunately, they have tendency to discriminate towards protected characteristics by law. Despite these adverse outcomes, there are ways to detect and mitigate social bias. This however comes at a cost – the trade-off between fairness and an AI model’s accuracy is the most striking one. Fairer AI models might not be as efficient, likely leading to fall in profits.
Are private organisations expected to correct and pay for historical developments in society? Or is this the role of the regulator? The key to success probably lies somewhere in between – a collaboration between governments and businesses. First, we must settle on what is fair.
Come to the talk to find out what goes on behind the AI Fairness scenes!
Speaker: Vlad Fojtik, Data Scientist at Aggreko
Vlad is a Data Scientist with experience in the banking and energy industries. Vlad wrote an award-winning Consultancy Project report, highlighting ways to detect and mitigate social bias in automated decision-making processes.
He previously acted as a Model Fairness Champion in a UK bank, where he was able to apply his expertise.
As a keen reader of economic, political, and behavioural literature, Vlad highlights the perils of Ethical AI as well as arguing that it is extremely unfair to punish private organisations for not deploying fair Machine Learning models.
6:00 PM – 6.30 PM: Networking (Drinks & Pizza)
6:30PM - 7:30 PM Vlad Fojtik, Data Scientist at Aggreko (presentation and Q&A)
7.30 PM - 8.30 PM: Networking and Drinks