Thursday 28 May 2020, 12 PM BST
AI have become more and more popular within the financial industry, and many insurers have started out on their AI journey.
We will talk about some of the worries around delegating decisions to machines, and how to overcome some of these challenges.
We will build on this to help identify ways to obtain sufficient comfort in the models in order to make business decisions and to be able to explain the impact to stakeholders, in particular the AI risk management and governance framework that could be used to support this.
Join us for a virtual roundtable discussion, with experts from across the insurance risk management spectrum as we discuss and explore:
AI and its role within the business (for example the differentiation between using AI models as back office tools to understand the business versus building AI models to automate process and decision making)
The adoption of AI within the business including reliability versus ethical & trust debate
The Governance around AI and accountability
The operating model in which AI are being used
We will attach a link to the ICO draft guidance "AI auditing framework” and the PRA requirements that automated trading model retain a "switch off" controlled by a human that can be activated when markets are tailspinning.
A huge increase in data generation, data capture and data storage combined with significantly increased computing power is providing insurers with a unique opportunity to re-evaluate the value that their data can provide; and the technologies available to do that.
Methods used in non-life pricing are evolving at a fast pace and more advanced actuarial and statistical techniques are being used in pricing, competition analysis and profitability analysis.
How can life insurers address low persistency? How can data and analytics help? Join our webinar on Friday 12 March 12pm as we discuss how the full cycle of actuarial analysis is evolving
A huge increase in data generation, data capture and data storage combined with significantly increased computing power is providing insurers with a unique opportunity to re-evaluate the value that their data can provide.
Improvements in computational power has given rise to the use of data science and artificial intelligence techniques in a wide variety of areas, including finance, driverless cars, image detection, speech recognition etc. This is directly impacting business practices within the financial services through its application within banking, insurance and asset management.
In the current economic climate, insurers need to improve their processes continually – making them more efficient and cost-effective while maintaining the agility to deal with new requirements. At the same time, technological change is providing new ways of achieving these objectives. In particular, the term ‘robotics’ appears to be used everywhere, and it is important to grasp the impact and potential use of these new technologies.
Listen to Valerie du Preez, founder and Managing Director of Actuartech, on the panel for Legerity's IFRS 17 webinar discussing, "Can IFRS17 help deliver digital transformation?".
In a world of high volume and varied datasets, data science techniques can add valuable tools to an actuary’s toolkit to provide actionable insights from data.
Sophisticated machine learning models have the potential for high predictive accuracy but their complexity may sometimes result in black box models, which, in some cases, may appear to be a trade-off between accuracy and interpretability.
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