The cloud and AI: why banks need to embrace the cloud to unleash the true power of artificial intelligence
David Vander,
Worldwide Industry Practice Leader,
Microsoft Enterprise Services,
Microsoft.
Whatever one makes of the debate on the question of artificial intelligence (AI) as a force for positive change in the world or the opposite, we at Microsoft are focused on putting the power of the intelligent cloud to work for, and even on behalf of, individuals and organizations across industries. Financial services institutions especially are set to reap the rewards and see its long-term potential for effecting transformation and driving innovation.
AI, properly understood
Properly understood, artificial intelligence is a cluster of capabilities, such as pattern recognition across large and evolving data sets, as well as a host of technologies such as deep learning, cognitive services, bots, intelligent agents, and more. Tying them all together is the cloud. The one is wholly dependent on the other: you cannot have the benefit of AI without the cloud. The elasticity and scale of the cloud offer organizations a platform for innovation and agility to respond to and—increasingly, with AI—anticipate the needs of business in constantly evolving, fast-paced marketplaces.
Cloud solutions that are pre-assembled, pre-integrated, and hyperscale offer financial institutions a host of intrinsic benefits, which become even more evident when you contrast them with the alternative: implementing piecemeal, on-premises solutions. In fact, if you attempt to implement AI in this manner, you may get some value, but you’ll miss the point. For example, you may be able to do batch processes, sync data, identify some trends, and so forth, but you simply won’t get the speed, integration, and roadmap that cloud computing affords—and, what’s more, you’ll miss the opportunity to simplify your technology infrastructure and reduce your IT costs considerably.
Understanding the potential
The business potential of AI is progressive: the further you go, the more value you will get out of it. It begins with using it to obtain a historical view, gathering data from diverse internal and external sources, consolidating it and giving it coherence to answer the fundamental question, “What happened?” Once you have a view of what happened, you can then take the next step and ask the question, “Why did it happen?” Here, AI will help you identify patterns, and trends, and permit the formulation of hypotheses about the past and present. The final step is the most interesting, and involves the application of machine learning algorithms and deep learning capabilities to postulate about what will happen and provide an answer to the business-critical question, “What should I do?”
This is where the real value of the technology lies: in determining what action may be needed, automating it—and then, once automated, adding predictive capabilities that will allow you to get ahead of market trends.
Consider the implications for investment banking and advisory services in particular. It will soon be possible for every person to have a personal financial manager—or, on the flip side, for every financial advisor to have a personal assistant offering support 24/7. The wealth advisory avatar would always be looking out for you. When a suspect transaction occurs through one of your accounts, it would automatically call or text your cellphone; when a payment is due, it would make sure you would stay current and avoid late fees.
And it could go beyond offering reactive services to provide proactive, personalized advice about what to invest in, what to watch out for, how to tune a portfolio for advantage—in real time. Private banking experiences thus become available to the masses. These are just a few of the scenarios being made real today at innovative financial institutions the world over, such as South Africa’s Nedbank.
Areas for AI innovation in financial services
To distill these notions a bit further, there are three major areas where AI is opening the door to innovation in the industry.
Personalization: AI can be used to help people get their needs met in real time, “remember” their histories of interactions, tune services to the specific banking relationships, and learn preferences over time.
Customer engagement: Closely related to personalization is the range of experiences all along the customer journey where AI can smooth the transitions and sustain coherence across channels, such that information doesn’t have to be repeated, and required services are delivered to the customer with minimal friction. In this way, financial institutions can provide more proactive and responsive customer engagement.
Advice and insight: As mentioned before, it’s not just about the products and services that the bank might propose—it’s also about better managing risk, whether in the form of fraud prevention measures, managing non-performing loans (NPLs), or identifying and containing systemic risk factors.
In these contexts, AI technology will prove truly differentiating, even if today, it’s mainly being used in the form of bots for the sake of cost reduction and efficiency gains. But as should be clear by now, the value will really kick in when AI is implemented for its predictive capabilities and its potential for acting on our behalf proactively. For that future—perhaps closer than many may realize—the cloud is an absolute prerequisite.
At Microsoft, our approach applies technology in unique ways—with a trusted cloud platform, tools, and services that deliver augmented intelligence capabilities and empower business agility. As your trusted technology partner, we offer both industry know-how and enterprise-grade solutions. We can help no matter where you are on your digital transformation roadmap.
