Conversational Agents: The Imperatives in Investment Banking

Conversational Banking

Conversational Banking

Why financial services providers today must invest in conversational banking?

The relentlessly increasing demand of financial services from customers is putting massive pressure on investment banking firms. They typically consent new debt and equity securities for all types of corporations, support in the sale of securities, assist in facilitating mergers and acquisitions, and broker trades for both institutions and private investors. However, higher capital charges, market electrification and digitalization, inflexible and layered technology with increased complexity of regulation and reporting are creating a set of challenges to the investment banking industry.

The sudden outbreak of the COVID-19 pandemic is also impacting investment banks as it has significantly halted economic activity across the world. To curb this uncertainty, many large investment banking systems are turning to technology to assist corporations, governments, and other groups plan and manage large projects during the crisis. Many banks have begun creating their potential use cases and strategies, budgeting innovation funds, and developing proof of concept systems.

They also need to make a transition of their communication with advances of AI and start having conversations with their digital customers. In this context, they must embrace a conversational agent that not only conducts natural language processing (NLP), but also responds to customers using human language without any human agent interface or automatically.

Today, financial institutions and payments companies are experimenting with AI-powered bots that can computable both live in their mobile apps and ones that exist on messaging platforms. These rule-based chatbots have the potential to handle only simple, routine queries and FAQs. They lack self-learning and adaptive abilities and may not be appropriate for every interaction or use case.

Meanwhile, considering intelligent chatbots powered by cognitive technologies can simulate human-like conversation as they equipped with continuous learning and adaptive abilities, offering higher efficiency, precision and personalized conversations to customers. Conversational agents that involve voice recognition with cognitive technologies can represent the practical implementation of computational linguistics, typically employed as chatbots over the internet or as portable device assistants.

For instance, a leader in the U.S. banking industry Bank of America introduced an AI-enabled virtual financial assistant, named Erica. This chatbot effectively catered to the bank’s customer service requirements by sending notifications to customers, giving balance information, sharing money-saving tips, providing credit report updates, and assisting customers with simple transactions, among others. 

The investment banking industry is also at the forefront of adopting conversational AI. This has been driven by a rise in conversational interfaces and NLP, enabling financial services providers to engage, transact, and collaborate using natural chat. With conversational interfaces representing the crucial shifts in banking user interfaces and are transforming how banks acquire and retain customers and developing brand identity, the likes of messaging apps like Facebook Messenger, Slack, Microsoft Teams and others, and the adoption of voice-activated assistants including Alexa, Google Home, and Siri are bringing conversations back into the banking experiences.