For financial institutions to thrive in the current economic clime, customer service delivery must adequately align with customer demands and expectations. Beyond seeking lightning fast responses and resolution of complaints, customers are beginning to tend towards banks and payment solutions that incorporate AI into their CS process to ensure excellence in service delivery to customers and also enable them (the organization) make the ultimate switch to cognitive banking.
With the massive influx of MVPs and product lines in the financial services space in the past 2 years, it is becoming glaringly apparent that beefing up CS staff strength in proportion to the volume of interactions received will not be sustainable in the long run as running that model means that companies must be ready to build stadiums to accommodate their growing staff strength at some point.
What companies need to start looking at is a solution that allows them rapidly conclude monotonous and repetitive tasks, provide cognitive banking services, and do so for up to a thousand customers simultaneously.
Consolidating the efforts of physical agents with AI and ML to support scaling ambitions will be the future of CS. With the present focus on financial services, AI will enable institutions effectively handle increasing interaction volumes, cater to dynamic customer needs and explore options that revolve around predicting the best value propositions for customers.
The need for human operators cannot be underplayed as some customers will still prefer the traditional methods of communication (email, telephone, SMS, walk-in etc) over chatbots to have their issues resolved. Over-reliance on AI is never a good idea and so the ideal mix of human intervention and AI must be concocted very carefully. Measures must be put in place to ensure that calls which can no longer be handled by AI are escalated to human operators. In handling email interactions, human operators will need to proofread responses drafted by AI until the system becomes foolproof. This will undoubtedly take some time as it will need to be trained with Nigerian/specific country peculiarities and contexts to ensure usability and relevance.
Added benefits to the financial services company that adopts AI will include reduced time and effort spent on training agents as AI requires one-off training, winning points on brand perception and maintaining consistent performance levels instead of the inevitable fluctuations that occur when a new set of agents are hurriedly recruited. Adopting AI also significantly lowers interaction abandonment rates, improves capacity for handling high traffic periods and ultimately ensures 24 hour real time support.
To properly launch into intuitive/cognitive banking services, AI will need to learn from transaction patterns, existing tickets logged on the organization’s CRM system, conversation histories, help content uploaded etc and leverage on these to provide spot-on recommendations for customers (after ensuring that their initial complaints/enquiries have been sorted out)
To optimally drive these initiatives, special attention needs to be placed on the data which AI will be feeding off. This is because the more specific, detailed and viable the data, the more intelligent the system becomes. If properly executed, we may well be on our way to breaking ground in mimicking the human thought process in providing financial services.