Financial services companies are entering the future thoroughly: it is one of the segments that is adopting artificial intelligence (AI) in a fast way to generate better experiences for their clients, launch new products and services, reduce risks and redefine business models.

The consulting firm, McKinsey, estimates that the additional value that can be obtained by banks that apply strategies linked to AI, rises to US$1,000 million per year.

Smart automation

Intelligent automation, supported by machine learning, is one of the busiest applications in the industry to date. Banks handle huge amounts of data on transactions, investments, market indices and the behavior of their own clients. Combining all this information manually or with basic computer tools to obtain useful knowledge for decision making is not only a tedious task, but also highly prone to errors.

Automation with machine learning allows us to explore big data in search of patterns, deviations or anomalies and apply the results to analyze customer behavior, reduce costs or anticipate risks, among other functions.

Tax, legal and fraud managers find in intelligent automation an opportunity to put aside repetitive tasks and dedicate their time to delivering greater added value to the organization.

Personalized investments

From the point of view of the customer experience, AI has been operating in banks for some time: we see it in those virtual assistants that appear on the website when we have a question while browsing or in chatbots that simulate and process human conversation.

Now it’s time to take a new step: AI-supported, data-driven financial guidance services allow those same bots, properly trained, to process various sources of investment data in seconds and deliver to each client an optimal and highly efficient solution according to their needs, their profile and their financial capacity.

The customer experience can be enhanced and personalized in even simpler but just as important ways: systematic collection and subsequent classification of data on all customer interactions across all service channels, for example, enables targeted promotions to be delivered, relevant information on their mobile phone or referral to an advisor with whom they may have a greater probability of success in the exchange. The result? A higher degree of satisfaction and fidelity.

Risks under control

One of the advantages of AI as a predictive technology is that it allows credit risk models to be generated based on the customer’s history, their general consumption, their income or their behavior in reference to loans, among others. This is an advantage for both parties: the client does not need to wait for approvals or fill out endless forms, and the bank reduces the risk with each loan provided. It can even offer a more accessible interest rate in cases where said risk is really low.

In addition, AI is very useful for monitoring behavioral patterns in order to detect suspicious actions and prevent frauds.

Deep analysis

One of the functionalities of AI is to study all the data to provide results on the actual and potential profitability of each of the services, identify market trends, outline appropriate strategies or establish new performance models.

The limits in the capabilities of analyzing what is happening in the market literally disappear. For example, with natural language processing (NLP), banks can dive not only into traditional data sources, but also into news, videos, research or any type of material to explore trends that may impact finances.

Obstacles and drivers

What obstacles exist for a broader adoption of AI in the banking sector? The main one is the existence of legacy systems with old architectures, which prevent the incorporation of new technologies.

However, the acceleration of digital transformation, the pressure exerted by fintech companies that are digitally native and data driven, and the direction that the market is taking do not leave many alternatives: the time has come to modernize, reinvent the business and commit to the fact that financial services are getting smarter.