Advances in analytics and data Modelling have given Financial Institutes access to vast amounts of data about customer behaviour and preferences. This offers an extraordinary opportunity to develop products that meet or even anticipate customer needs. Artificial intelligence (AI), machine learning, and customer analytics will drive client engagement and product development over the next decade; basically, every Financial Institute offering is a form of AI software now. But before banks and other FI’s can deliver services that customers want, they will have to gather, interpret, and draw product strategies out of torrents of data in many versions and forms. Few financial-services companies are ready to use their masses of data to full advantage. In a reorganized model, each business unit can share data with others but apply it in ways that connect directly to its customers.
Unstructured data in the financial services can be identified as an area where there is a vast amount of un-exploited business value. Financial institutes needs to build more powerful and more accurate predicting models to better analyse financial data, predict revenues and costs, measure risks and justify critical business decisions.
This year’s event will encompass discussions including; Data Modelling in the Age of Big Data, Steps to consider when building a successful Data Warehouses, Business Benefits of utilising BI reporting solutions, Building a Data Governance Program with Data Modelling, outlining characteristics of a successful data Lake Implementation and Machine Learning processes that can assist with automated data modelling and other aspects of Data management
The purpose of this year conference is to change the processes of data modelling and to keep pace with the rapidly evolving world of data.