AI In Financial Services | DreamQuark Innovative Solutions

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The Close Link Between AI and Financial Services 

AI in financial services is occupying an increasingly important place. Some may even argue that artificial intelligence is at the heart of a true financial revolution. FinTech has the potential to transform various models in the finance industry globally as more of their decision-making processes already revolve around data. Gradually, artificial intelligence is leaving its role as a convenient solution to facilitate payments and transactions to assume that of a full-fledge business configuration. 

Innovation: A Driving Force 

As the world as a whole continues to evolve, AI in financial services naturally progresses if only to keep up with expectations, be it for B2B or B2C products and services. 

Hardware capabilities are leaps ahead of what they were even as little as five years ago. The smartphone revolution, for one, has constituted an invitation for FinTech developers to bring the financial world up to speed in a race to meet the growing demand for compatible services. 

The advances of back-end tools have also been promoting growth in the sector, with actors such as DreamQuark developing AI-based solutions aimed at industry professionals (banks and insurance companies). Their software, Brain to Train, has enabled these organisations to deploy AI financial services on a large scale, thus encouraging their adoption. 

To put it simply, as the finance industry is implementing artificial intelligence into their business models and end-users have tools at their disposal to take advantage of new functionalities, the demand for AI solutions continues to rise. Similarly, the finance industry depends on it more and more. 

Towards Meeting An Ever-Evolving Demand 

One of the main roles of AI in financial services is to collect, analyse and interpret big data in order to provide finance organisations with tailored recommendations based on their short and long-term goals. New technologies allow the finance industry to adapt to the changes in regulatory compliance requirements and to align with customer demands. Three major areas stand out in how deeply they have come to depend on AI. 

Financial Crime And Fraud 

Machine learning – a subset of AI – is at the heart of the models used to fight fraud and financial criminality. Deep learning allows irregular activities to be detected in real time and is a scalable solution which provides more accuracy than traditional methods. This use of AI in financial services inscribes it as a highly dependable asset the industry has come to rely on. 

Credit Risk Management 

AI in financial services is also becoming more prevalent in credit risk management, another area where data plays an important role, especially in probability of default and early warning signals. Artificial intelligence allows for the implementation of monitoring measures thanks to which risk is assessed on a constant basis. 

Customer Experience 

The digital era has led many industries to experience heightened customers’ expectations. Encouraging a culture where instant gratification is the norm, new technologies create a cycle where industry standards need to follow the same trend. Any complacency would cause them to be left behind as consumers continue to embrace progress. Chatbots are a good example of how banks can use AI in financial services through which they can both provide customers with a more seamless experience and collect valuable data. Their clients get immediate answers to their queries and can interact with their accounts straight from their smartphone. They can also receive insights and recommendations. 

While these interactions take place, artificial intelligence gathers data and analyses which digital experiences the consumers favour, which options generate the best conversion rate, etc. Banks want to cultivate a relationship with their customers. They want to understand them and to provide them with an experience that will encourage their loyalty. AI can help them to just that!

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