AI is being leveraged for predictive analytics to forecast market trends , consumer behaviour and economic conditions . How is it being applied to deliver these predictive insights ?
Prashant Jajodia : AI is being utilised for predictive analytics by employing advanced algorithms and machine learning techniques to analyse historical and current data related to financial services trends , consumer behaviours and economic conditions .
These models learn patterns and relationships within the data , enabling them to predict future outcomes with increasing accuracy . By integrating AI into financial services , businesses can make informed decisions based on data-driven insights , ultimately optimising their strategies and enhancing operational efficiencies .
Jamil Jiva : AI delivers predictive insights through machine learning algorithms that process large datasets , both internal and external , finding patterns and trends that would otherwise remain hidden .
In the financial sector , firms are applying AI across the board , from compliant investment decision-making to portfolio management . For example , at Linedata we have developed several solutions to help financial advisors and lending professionals to find the best offer or action for their clients .
AI identifies personalised suggestions of content , actions ( i . e . which customer to call ) products or investment portfolios which are made available through CRMs , portfolio management systems and financing software .
Marco Santos : AI ’ s ability to synthesise vast amounts of data allows organisations to connect data from previously disparate sources , and then analyse it to detect historical patterns and deliver forward-looking insights .
In the banking industry , this is happening at both a high level through traditional data analysis , and , increasingly , through more advanced AI tools including Natural Language Processing ( NLP ) and Machine Learning ( ML ). As organisations continue gathering these predictive analytics , many are also in the process of providing feedback to their AI systems which will ultimately improve their predictive accuracy over time .
The main use case in which banks are currently seeing the biggest impact from AI-powered predictive insights is in forecasting consumer behaviour . For example , using AI to analyse decades of historical data around consumers ’ banking habits in the context of certain economic climates , banks can use the resulting insights to decide on
188 November 2024