Implementing generative AI
The arrival of GenAI has significantly increased the pressure on legacy financial services brands to become adept at handling unstructured data. Overcoming this learning curve was already critical to being able to shape products and services around customers and being able to compete directly with digital-by-default rivals who can personalize at scale.
But now, it is equally imperative for the successful implementation of GenAI. The technology’s ability to deliver real long-term business-wide benefits is dependent on the veracity and volumes of available data.
Because, let’s be clear, even in an off-the-shelf format, generative AI has clear business use cases that could be instrumental in boosting productivity, unlocking efficiencies and improving the overall customer experience.
For instance, it can be trained to automate and accelerate the approval process for certain financial products. It can be positioned as a customer-facing chatbot for providing detailed but no-nonsense advice and support on a host of financial topics and for taking the first steps towards prequalifying a customer for certain products and services.
Within the contact center, GenAI can serve as an agent-facing smart database that can build tailored products and services based on prompts that describe an individual customer’s specific needs. This, in turn, can help organizations move away from the traditional approach to selling products and services as siloed individual lines of business — an approach that in many markets enabled fintechs to get a foothold.
As such, banking and financial services organizations recognize they must adopt this new technology. But of course, to unlock GenAI’s full potential means access to talent and resources, even if taking a partnership approach, and that means having the available funds for investment. When options for business growth are constrained, increases in efficiency and productivity, not to mention overall lowering of operating costs (without a negative impact on service or performance levels), becomes the clearest path to create the financial breathing space required to make investments in other business areas focused on long-term performance.
In the current economic environment, outsourcing non-core business operations does more than simply release funds for such investments. If that outsourcer is a genuine leader in financial services CX delivery, the partnership simultaneously elevates performance relative to customer expectations and can, of course, open the door to accessing an ecosystem of complementary services and solutions, including the capabilities needed to master unstructured data.
Crucially, they can do all this while actively complying with all existing regulatory frameworks in all geographical territories and not simply in terms of banking and financial services. Genuine BPO leaders are already preparing the groundwork for regulations on the horizon related to the ethical use and application of generative AI and customer data relative to the technology.
Key takeaways
There's no doubt about generative AI’s potential to revolutionize the banking and financial services sector.
How much your business can benefit from the technology will be decided by the quality and volumes of your data.