By Eran Shirazi, CTO and Co-Founder, EasySend.
Across every industry, artificial intelligence technology will usher in new efficiencies, unlock substantialvalue, and enable a new generation of innovative products and services. Banking is no exception.
How significant of an opportunity does AI present the global banking industry? McKinsey & Company pegs it at up to $1 trillion in new value each year.
But while AI holds immense promise as a tool for helping financial institutions streamline key business processes, enhance customer service, and make more intelligent, data-driven decisions, and most banks have introduced at least one AI feature to realize these benefits, not all banks have developed an AI strategy.
Among banks with more than $100 billion in assets, 75% have crafted an AI strategy, but that figure drops to 46% among banks with less than $100 billion in assets. While it’s all well and good to launch a customer service chatbot here and a personalized recommendation engine there, AI success will require banks to anchor their initiatives in a coherent strategy. What that looks like will differ from institution to institution, but here are a few key considerations that should guide banks’ planning for an AI-driven future.
Achieving New Efficiencies
When it comes to the future of work, commentators often discuss AI as a threat to jobs.
But those who have been in the banking industry long enough will remember that the ATM was supposed to wipe out most bank tellers’ jobs – yet half a century after the first ATM was introduced in the U.S., the country actually has more bank tellers than it did then. Rather than eliminating the role, the ATM augmented it, as bank tellers began focusing more on customer relationship management as opposed to the more mundane tasks that ATMs took on.
That experience offers an instructive lesson as banks think about AI and how it will impact their workforces. ATMs helped banks save labor costs by reducing the number of tellers needed at each branch, but that in turn lowered the cost of operating a branch, leading to an overall increase in the number of both branches and tellers. Similarly, AI is enabling banks to offload basic customer service tasks onto chatbots and voice assistants, while human professionals handle more complex tasks and requests. This allows banks to provide round-the-clock customer service without having to pay round-the-clock staff.
What’s more, AI minimizes the security and data risks associated with human error, and system maintenance can be outsourced to third-party AI platform providers – eliminating the need for costly new IT hires.
Meanwhile, anti-fraud and risk management specialists can now harness AI to speed investigations and Know-Your-Customer (KYC) procedures, with algorithms that efficiently flag potential signs of trouble. This will allow for a much more efficient allocation of specialists’ time and resources, as they will be able to focus on the toughest and most urgent investigations.
Armed with robust customer data, banks can also automate much of their credit underwriting and contract-writing processes, alleviating back-end employees’ workloads. As AI streamlines functions and processes across organizations, it is on pace to help banks save $447 billion in costs by 2023, per a Business Insider Intelligence forecast.
Of course, the fact smaller banks have been slower to adopt AI strategies suggests that for some institutions, cost concerns have been a deterrent, not a spur, to AI innovation. But thanks to the availability of no-code platforms – which allow even non-specialists to build customized AI applications – AI is becoming more accessible and scalable for organizations of all sizes.
AI is the engine of transformative new applications, and data is the fuel that powers it. With rich data and customer insights, banks can provide relevant, personalized offers, recommendations, and advice, thereby nurturing customer relationships and building loyalty.
For seamless integration of data-driven offerings and processes, it’s crucial for banks to have a strong digital core, underpinned by AI technology. Sticking with legacy infrastructures and processes makes it more challenging to effectively gather, understand, and ultimately leverage data.
At both the customer and the organizational levels, data analytics can help banks identify gaps and opportunities, providing a solid empirical basis for assessing and fine-tuning their operations and customer outreach.
Digital Banking: Go Mobile or Go Home
Foremost among the reasons for banks to embrace digitization and AI is the imperative to meet customers where they are. In today’s digital economy, customers expect all their banking needs to be available at their fingertips – an expectation that has been reinforced during the COVID-19 pandemic, as consumers have grown more reliant on digital platforms in all aspects of their lives.
According to a Business Insider survey, 61% of customers would change banks if faced with a subpar mobile banking experience. How can banks avoid that fate? The answer lies in AI, which is essential to providing customized, friction-free digital banking journeys – from the offers, reminders, and notifications customers receive to the financial planning guidance and security protections mobile banking platforms provide.
As AI assumes a greater role in banking operations, it will be vital for institutions to ensure that they maintain the human touch that sustains customer relationships, inspires innovation, and offers an intuitive, real-world understanding of industry trends.
AI will transform a lot – but it won’t change the fact that banking is fundamentally about human relationships. With an unwavering commitment to harnessing technology to enhance those relationships and meticulous attention to detail in plotting their innovation strategies, banks can pave the path to a future that’s less artificial, but plenty intelligent.