The forces of change in banking have seldom been stronger. The recent rise in interest rates is pushing consumers to overcome their inertia, and to open themselves up to new choices. Digitalization has lowered the barriers to market entry, creating intense competition for niche services and generating new business models. Regulatory pressures, environmental sustainability commitments and cyber security risk are all demanding an enterprise re-think and ongoing transformation. If your bank wants to lead the pack, it’s going to need a comprehensive artificial intelligence (AI) strategy.
Growing market share will require banks to out-innovate their peers and provide a superior experience across all facets of their business. Banks must continue to consolidate service offerings to satisfy customer intentions, not just to address their immediate needs. Achieving improved cost ratios and shareholder returns, requires advanced technologies to be deployed to replace antiquated, labor-intensive and siloed processes. Thanks to the celebrity status of generative AI tools, like ChatGPT, it’s easy to think that the adoption of large language models is all that’s required. In truth, AI needs to become ingrained into every aspect of banking infrastructure.
Steps to ingrain AI
Executive leadership needs to recognize that an advanced technology infrastructure is essential to their institution’s future success. Just as COVID catalyzed and accelerated the development of new applications and models to support remote services, integrating machine learning (ML) and AI models into the fabric of the enterprise must become pervasive. The rationale and economic justification for these investments are many. Whether it’s to address critical skills gaps in IT staffing, improve resiliency, strengthen cyber security or to support agility and innovation – to name just a few – the business cases are limitless.
Incorporating AI into your organizational strategy is only the beginning. Execution, aligned to clearly defined, articulated and measurable outcomes, at every level of the organization, will be needed for success and sustainability. Starting with the core technology infrastructure, there is a need to get off the conventional treadmill, whereby the bulk of IT resources are consumed in just “keeping the lights on”. Working groups, starting at the operational level, should be formed to identify the areas that consume the most resources with the lowest returns. Opportunities to incorporate advanced tooling, backed by AI, that go far beyond standard forms of scripted automation, should be explored and adopted, as quickly as possible. Done properly, this will not only provide immediate benefits in compliance, currency and stability, it will also free up resources to address higher value challenges.
Finally, there needs to be a recognition that this isn’t something that any organization can accomplish on its own. Partnerships with advanced technology organizations that have the financial resources, scale and a responsible AI mandate, must be forged and maintained for the long term. To be effective, AI models must be self-learning, to provide continuous improvements to the environments they service. It also means that the AI model must have access to not only your organization’s data but also to an ongoing and extremely large stream of diverse data from other customers, managed through a responsible AI framework. This responsible AI framework is necessary to protect the security and privacy of each customer and to ensure the ongoing efficacy of the models.
Cisco knows AI
At Cisco, we have been investing in AI for years. At the core, we have our AI Cloud Platform. This provides data and compute services that support the AI/ML engines underlying products like Catalyst Center (formerly DNA Center) to improve the performance of our Catalyst routing and switching products. It’s also behind products like our ThousandEyes, ISE, and SD-WAN technologies. Our development path on all these products is clear. We start with information gathering – observing and understanding – and move quickly to diagnosing, triaging and automating root cause analysis. As we build a history of each customer and combine it with anonymized peer data taken from other customers, the models become more predictive about expected behaviors and, finally, pre-emptive in prescribing what needs to be done to prevent issues. To be successful, one of the prerequisites is access to massive amounts of data, literally billions of data points, continuously streamed to our cloud. The result is that, properly deployed, these capabilities are true game changers for our customers.
As a Cisco customer success executive, I work with a couple of large banks, and I see the potential that AI has for changing their current reality. The biggest obstacle is finding a way to make new things happen while not impeding the progress of existing, committed projects. That’s where Cisco’s customer experience (CX) group can help. Our mandate is to accelerate the time to value of our customers’ investments. Through understanding desired business and technical outcomes, and aligning our programs and services to support them, we work to ensure that our customers are adopting the full range of capabilities available to them. Whether that’s through Cisco professional services, our programmatic offerings or working in conjunction with our technology partners, our aim is to help you to meet your goals, in measurable terms, and to maximize the value you receive from your Cisco investments. As a financial institution, if you’re not doing it already, I strongly encourage you to engage your Cisco CX team to explore the possibilities.
Future technologies
What lies ahead? Imagine, for example, the potential benefits of a digital twin of your current network. Creating an exact replica of your environment, virtually, would allow you to confidently model everything from simple change windows to capacity increases to changes in traffic flows, without impacting your production environment. Less risk, less downtime, fewer errors, better outcomes. Maybe a metaverse experience that allows your avatar to walk through a simulation of your data center, updating the design and replacing aging equipment, whilst the system provides a real-time analysis of potential power savings, reduction in CO2 emissions and highlights additional areas for performance optimization. Switching back to a consumer focus, financial institutions will need to have a platform in place that can support the delivery of virtual reality experiences for their employees and customers, if they are to capitalize on the multi-trillion-dollar market opportunity that will develop around this technology in the next few years. I’m certainly not going to tell you that these are on Cisco’s roadmap, but the possibilities don’t seem too far-fetched. After all, the network is at the heart of everything digital.
Do you want your bank to position itself for sustainable growth that exceeds market performance? If so, talk to Cisco. We’ll get you started. And don’t forget to check out all of our latest Cisco AI blog posts. There’s a lot going on over here.
For more information, please reach out to your account team or visit Cisco Financial Services Solutions.
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