MARK DEARMAN
“AI-driven analytics continuously learn from realtime data to detect fraud issues within seconds”
MARK DEARMAN
TITLE: DIRECTOR OF BANKING INDUSTRY SOLUTIONS
COMPANY: FINTECHOS INDUSTRY: FINTECH LOCATION: UK
a separate model to estimate power outages based on the wind forecast. Finally, an economic model could use the predicted outage to estimate the financial impact.”
This multi-model approach provides greater resilience when facing unprecedented scenarios.“ By layering these models, the overall prediction becomes more reliable,” Alan concludes.
Adapting to market volatility Market volatility presents another significant challenge for predictive analytics. Rapid regime changes and shifting market conditions require models that can quickly adapt to new realities.
“ With increasing market volatility, predictive models are evolving to handle rapid regime shifts by incorporating real-time data processing, adaptive machine learning techniques and alternative data sources,” Mark notes. Traditional models reliant on historical trends and static assumptions often struggle during sudden economic disruptions.
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