Cognitive computing makes it possible to anticipate patterns in user behavior in order to offer them their ideal product – and at the best moment
Knowledge is the new “gold” of the banking industry. But for information to be translated into tangible products and services, it must first be processed and converted into traceable patterns that allow users’ needs to be anticipated.
Cognitive banking is a concept that uses the benefits of Artificial Intelligence (AI), automation and analytics, and puts them at the users’ disposal, to offer them personalized solutions – which can go from financial advice to a credit or a savings account with better terms – all with the intention of improving the user’s experience and achieving their loyalty.
This 360° understanding of data gives banks the potential to stay ahead of competitors and disruptors in the marketplace, such as big tech and fintech, which have already proven to be agile in their developments within the field.
Exponential technologies such as machine learning and big data will be increasingly relevant in transforming the value chains in the financial system. Some 63% of executives in management positions considered that AI and analytical tools are fundamental to the success of any business, according to a survey conducted by Deloitte in 2019, in different industry sectors.
Cognitive Banking: Greater Accuracy
Cognitive banking allows for more accurate predictions on a client’s decision-making process and the flow of operations, while automating operations that tend to be repetitive helps to improve the responsiveness of the business, saving time and increasing efficiency.
To date, we have seen cognitive banking used in virtual financial assistants and chatbots or in biometric security configurations, to offer new products and improve the existing ones.
But these are just a few steps in the great disruption expected from cognitive banking tools. Lending and credit decisions are set to be a major area for this technology, where it is increasingly common to apply machine learning. As the computer obtains more data, it learns more about the client, increasing accuracy and minimizing errors in financing selection, according to the Deloitte study.
For banks that do not have ready-to-use structures to incorporate technologies such as AI, it is likely that the potential of cognitive banking will be realized through partnerships with external providers, who will provide them with tried-and-trusted platforms.
While traditional marketing tools still have a place in understanding customer journeys, through branch contact or surveys, AI and dense data analysis are more accurate in creating user personas, which must be at the center of any business strategy.
Some technology providers even aim to capture data from social networks to know when a customer is going to start a new venture and offer a small business loan, or when a user will become a new parent to show her deals from retail partners, with everything she may need.
The key is to take advantage of new and stored data and process it with the best technology, including machine learning, robotics and even blockchain, to continue to customize the experience between the bank and the user.
Experts say that banks should not wait too long to start dabbling in cognitive technologies and start building the bank of the future, where the priority will be the distribution of data in real time, with computers that will stop processing to start learning.