What is intelligent automation and what does it mean for the financial services industry? What’s the role and application of artificial intelligence (AI) in this context?
Banks currently face a number of specific problems for which intelligent automation – and within this the capability of AI – may provide solutions. Far from becoming our new masters, our prediction is that thinking machines could become our most trusted assistants, enhancing our productivity through providing us deeper and more timely information, and perhaps even automating the business of generating insights and making considered decisions.
The current (re)emergence of AI, which is contributing to the broader intelligent automation trend, seems to be driven by several key factors. The availability of unprecedented amounts data (much of it unstructured), the exponential increase in computer processing power, the declining price and growing convenience of data storage solutions, and recent advances in machine learning algorithms, all provide a powerful toolset for making significant strides in intelligent automation.
AI will likely help banks create better client experiences through ever more personalized, on-demand services. Although they offer personalized services today, AI can help bankers better understand clients and their needs, as well as aggregate and evaluate more real-time information relevant to their clients’ specific situations. We think that AI will help banks better execute on their promises of service excellence. And in our view, AI will also allow banks to put better and more powerful financial and wealth management tools into their clients’ hands.
AI can also help make banks safer, significantly improving the means for combatting cyberattacks. And it has the potential to make banks smarter, too. By learning how markets behave, and providing improved market intelligence, more profound market insight and better assessments of risk, AI can help banks offer deeper, broader and altogether smarter investment advice.
Furthermore, AI offers the potential to reduce costs. Banks already spend a significant share of their development budgets on projects to automate routine processes. This is happening first in the ‘back office’, where we see intelligent software agents executing manual, easily defined administrative processes. As machines become more ‘intelligent’, they will be able to undertake more complex tasks, like credit scoring or automated report writing. Although it may seem expensive now, by helping to usher in truly intelligent automation, AI can help banks achieve significant economies of scale.
Last fall, UBS invited leaders and experts from the financial industry, fintechs, academia and regulators come together to discuss the future of Intelligent Automation and start to build a common understanding of what a successful approach would look like. I am grateful for being selected as one of the participants of the session.
The result of the discussions is presented in form of a white paper by UBS Innovation and can be found here.