• Automating processes and customer interactions

• Introducing digital business models

• Reducing operational costs

• Enabling greater personalisation of product portfolios

• Meeting regulatory requirements and helping to detect fraud

• Improving decision support for customers and employees

Automated data analysis and processing is a key focus for banks and financial services companies :

Research shows that 39 % of BTI 2023 financial sector respondents expect to add Machine Learning ( ML ) and Artificial Intelligence ( AI ) to their organisation ’ s transformation plans over the next one to two years .

Using data , not just collecting it driven data strategy . Unlike humans , machines leverage increasing amounts of information . Hence , the greater the information available , the more optimal the results . The data strategy that a bank implements should take this into account , as the BTI 20231 shows .

Some of the BIGGEST CHALLENGES for the use of data in financial organisations :

• 64 % – Keeping up to date

• 63 % – Sharing of data between systems and departments

• 67 % – Data accuracy

• 69 % – Making full use of AI and Machine Learning

• 65 % – Using data to create new revenue-generating services

• 63 % – Data science / analytical skills

AI and data analytics will fundamentally change the banking world of tomorrow

One of the most important customer interaction points , and where AI becomes truly tangible to the customer , is the chatbot . Modern conversational chatbots will lead to a revolution in communication , as these machines differ from traditional FAQ-based bots in that customers can formulate their questions in

Comprehensive data preparation and processing is fundamental to a businessdescriptive terms . The AI-powered chatbot understands the query and responds accordingly . Thanks to a range of new offthe-shelf products , customised solutions can be developed quickly and efficiently using open-source technologies . Banking chatbots outperform human operators in terms of speed , precision , and seamless automation , driving enhanced efficiency and cost reduction . A new generation of bots is also capable of providing tailored financial advice .

Case study

We helped one of the world ’ s largest FinTechs build data models to interpret and present to a non-technical audience . To do this , Expleo built a data pipeline that uses Big Data systems to prepare , cleanse and transform data . It also enabled the automation of repeatable analysis and the creation of self-service tools for business users .

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