Impressively, banking only comes second to the high-tech sector when considering generative AI’s potential productivity impacts. The technology is predicted to deliver up to $340 billion in additional revenue to banks annually, with strong business use cases ranging from marketing and sales, customer service, software engineering, and risk and legal.
Given the potential upsides, banks of the future are set to integrate AI into every operation, from risk assessment to customer service. This end-to-end integration and digital transformation will pave the way for more agile, personalised, and secure customer experiences worldwide.
The implementation of AI in banking isn’t just a future project – it’s already well underway. In the Future of Banking with Trusted Generative AI report, Philip Benton, Principal Fintech Analyst at Omdia, shared, “In our recent annual global survey of around 2,750 banks, 93% of the respondents said they are looking to adopt AI in some form. Over half of them have already implemented AI to some extent.”
AI Has Changed Banking Forever
Discover how to build a secure, responsible AI strategy in the Future of Banking with Trusted Generative AI report.
What’s Standing in the Way of AI Adoption in Banking?
At World Tour New York, Cory Haynes, VP, Financial Services Marketing at Salesforce, said, “Financial services is changing rapidly, and we’re not just doing AI for AI’s sake. There are four main reasons businesses are adopting AI: hyper-personalisation, doing more with less, turning insight into action and revenue growth.”
That first point, hyper-personalisation, is particularly salient when we consider how quickly customer expectations for speed, personalisation and convenience continue to grow. Today, 75% of your customers would switch companies if a competitor was more convenient.
As customer expectations rise, AI also stands as the solution to meeting them. However, 76% of executives are struggling to deploy AI effectively to keep up with these growing demands. Two main challenges are getting in the way of an AI-first digital transformation in banking and beyond.
The first is that they’ve got too much data spread far and wide across disconnected systems and departments.
The second challenge is a trust gap between the potential of AI and the fear of ending up on the news because of a security breach.
Despite this, we’re seeing a strong shift in financial institutions towards AI adoption and innovation. Banks are upskilling for AI and embracing a culture of innovation, recognising the need to keep up to retain talent and customers. And the good news is that technology now exists to make those two challenges redundant.
The Einstein 1 Platform, deeply integrated with Data Cloud, is an AI solution that brings your data together across the organisation and customer lifecycle. It underpins all your core applications, including the Financial Services Cloud. And with Einstein Trust Layer on top, you can overcome the trust gap challenge as your data is masked and protected every step of the way.
AI Copilots Redefine Customer Service and Compliance
AI is no longer just an operational tool but a strategic imperative that is forever changing how banks operate and engage with their customers. It’s often said good service is a trade-off between intimacy and efficiency. With AI, that’s no longer true. AI assistants like Einstein Copilot can help banks deliver personalised interactions at scale, an advantage that is especially powerful when applied to customer service.
Take the example of the contact centre. With the average business cost for 100 agents sitting at $5.5 million, the opportunity to increase contact centre productivity and boost self-service with conversational AI can lead to significant savings for the business. When digital service is done right, you can reduce service costs by 25%.
AI assistants can provide more consistent and efficient service experiences for both customers and agents. Einstein Copilot speeds up case resolution with AI-powered capabilities including call transcriptions, recommended next-best actions based on customer sentiment, and a guided complaint process.
The self-service experience is also made more effective by AI-powered search. Smarter than keyword search, generative AI can surface insights from across articles and ensure they’re relevant to the question posed. With a strong, AI-powered knowledge base, you can increase the chance of deflection to reduce the volume of calls to your contact centre.
As well as increasing service productivity, AI is playing a crucial role in enhancing compliance, automating regulatory processes, and reducing the risk of human error in the banking sector.
It improves auditing processes by analysing vast datasets for anomalies and flagging potential instances of fraud far more efficiently and accurately than humans can. Furthermore, Einstein Copilot can automate call summaries and facilitate thorough identity checks for agents. These tangible use cases all add up to a more compliant and secure way of working.
Laying the Groundwork for AI in Banking: Renovate, Evolve, Transcend
Implementing AI in your financial institution begins with adopting one of three mindsets: renovate, evolve, and transcend. While most institutions are currently exploring the ‘renovate’ mindset, it’s essential to consider all three as you embark on your AI journey — from testing an AI copilot for workflow automation to thinking strategically about how AI can position your organisation as a leader and disruptor in financial services.
Explored in detail in the June 2024 whitepaper, A Guide Generative AI in Financial Services for Australia and New Zealand, these mindsets can be summarised as follows:
- Renovate: Start by enhancing and refining your current operations with an AI copilot to boost efficiency and build trust.
- Evolve: Expand AI’s role to redefine core processes and shift AI from a supportive tool to a pivotal element of your business strategy, enhancing customer interactions and operational agility.
- Transcend: Though largely aspirational today, consider the transformative potential of AI to create entirely new business models and customer experiences.
From ‘renovate’ and beyond, the rollout of generative AI capabilities in financial services institutions is simpler and more effective when implemented within existing enterprise solutions and tailored to the unique challenges specific to financial services institutions.
The industry-specific, out-of-the-box capabilities of the Einstein 1 Platform are our response. Einstein 1 makes it faster and easier to integrate AI in your existing environment, while always grounding it in the context of customer and institutional data. With trusted AI, the future of banking will be more secure and customer-centric than ever before.
Visit Salesforce at the 2024 COBA Convention
Discover how to help your community bank thrive at COBA24, 22–24 September. For now, get AI-ready and read the new report, A Guide to Generative AI in Financial Services.
