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By Babak Hodjat, VP of Evolutionary AI at Cognizant 

AI driven solutions are becoming a competitive differentiator for banks and other financial services — delivering a hyper-personalised customer experience, improving decision-making and boosting operational efficiency. Yet, many financial services institutions (FIs) remain in an experimental phase and will need to accelerate actual AI deployment. Otherwise, they risk being left behind by digitally native players.

AI is rapidly transforming every aspect of the financial world. This transformation has accelerated recently, thanks to evolutionary AI – a new breed of technologies that allows AI to automatically design itself with little need for explicit programming by humans. As it gradually becomes mainstream, evolutionary AI’s capability to innovatively create complex AI models, and to optimise decisions considering multiple scenarios, is set to reimagine the financial sector. It will enable every player in this field to spot novel strategies that would never have been identified by human data scientists, and, in turn, allow companies to take full advantage of today’s massive data sets.

The basics

Emerging technologies that enable AI algorithms to design themselves are allowing organisations to transcend human limitations. Evolutionary AI operates iteratively. Firstly, it randomly generates a set of potential solutions to form an initial population and assigns a score to each solution based on how well it performs relative to other solutions. In the second round, it retains the solutions that performed best, perhaps only 5% of the total, and recombines their components, sometimes “mutating” them to create a new population. This new population is then tested, and the process begins again. Over multiple generations, the appropriate components of the more successful solutions become increasingly prevalent in the population, and eventually a solution is discovered that yields the best outcomes.

Why organisations should consider adopting evolutionary AI

Compared to human design, evolutionary AI can be deployed far more quickly, avoids biases and preconceptions, and typically performs better. Furthermore, the chosen model will evolve and improve over time based on new data.

Evolutionary AI can be applied in a wide variety of areas at FIs. Some examples include designing quantitative trading strategies to maximise returns while minimising risk and loan underwriting. Rather than relying on human analysis, evolutionary AI solutions can quickly analyse all the combinations of relevant variables to create models that more accurately assess the risk of default by a potential borrower.

Steps to experiencing the full potential 

In order to reap the benefits of the technology, FIs should focus on the following:

As AI applications increasingly design and test themselves, the pace of innovation and the accuracy of predictions will vastly improve. It is inevitable that FIs will soon consider it irresponsible to make important business decisions without first consulting with an AI system. Robots will handle routine tasks while flagging exceptional cases for review and resolution by employees. Employees will spend their time on more complex decisions and sensitive interactions with customers, such as resolving complaints or providing sophisticated financial advice. In short, humans and AI robots will be working side by side, delivering more value in combination than either could on its own.

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