Embedded finance is positioned to become the number one distribution channel for financial services within the next 10-20 years, which means the time to start preparing for the revolution is now.Today’s customers want seamless, digitally-enabled buying and lending experiences. Embedded finance has emerged as a convenient solution to meet these needs. With its buy-now-pay-later (BNPL) method of financing that eliminates the customer’s trip to the bank, embedded finance has quickly grown in popularity as a way for customers to finance items at the time of purchase.
“Banks must find a way to deliver an exceptional customer experience, and establish lasting, loyal relationships, without relying on their branches and face-to-face interaction.” – Nathan Snell, Co-founder and former Director of Product Management at nCino
In the past, the financial services industry was slow to change. Due to the COVID-19 pandemic and consumers’ shifting preferences, however, financial institutions are rapidly adopting digital capabilities and other technologies to support quick, seamless and automated processes and better serve their customers. As the industry embraces change, emerging cognitive technologies like artificial intelligence (AI), natural language processing and machine learning are transitioning from a “nice-to-have” to established key business drivers.
While banks begin to truly understand the importance of cognitive technologies, it’s imperative to understand how to fully leverage these technologies to see true business value. The time has come to transform the Agile Enterprise into the Intelligent Enterprise by fully harnessing the power of cognitive technologies to capture deeper customer insights, make informed, data-driven decisions, manage risk and increase efficiencies.
Agility is the Launchpad
Any discussion of the Intelligent Enterprise begins with an understanding of the Agile Enterprise as the necessary foundation. The Agile Enterprise centers around the idea of turning every core banking function into a systematic, fast and seamless process. It is powered by a configurable and flexible platform that allows multiple users –including executives, staff and customers –to collaborate in real time, with full transparency and visibility into every step of the process. To fully leverage the Intelligent Enterprise, it is essential to first enable the Agile Enterprise. It would be incredibly difficult for a bank to make the leap into AI without first establishing a strong foundation to support its myriad of back-office processes. Once a bank has established a foundation of agility through an end-to-end platform, it can begin the journey toward becoming an Intelligent Enterprise.
AI is the Rocket Fuel
AI and related technologies, including machine learning, natural language processing and cognitive computing, serve as the foundation of the Intelligent Enterprise. The potential use cases for AI and related technologies can range from robo-advice and next-product recommendations to anti-money laundering (AML) compliance and credit card fraud protection. Within the Intelligent Enterprise, cognitive technology can be utilized to bring a true return on investment to the institution. Banks need actionable insights to maintain competitiveness and serve their customers’ needs. The successful deployment of the Intelligent Enterprise checks one or more of these boxes to varying degrees, depending on the specific use case: increasing revenue, growing profitability, improving efficiency, reducing costs and mitigating risk. Embedding cognitive technologies into core banking processes can present banks with measurable results, a positive ROI and benefits that continue to increase over time.
Challenges on the Flightpath
Widespread transformation to the Intelligent Enterprise will most likely come with a few hurdles. Banks of all sizes may be burdened with long-held processes and systems that can act as barriers to change. The financial services industry also faces a number of challenges, including slow adoption rates, talent acquisition, regulatory overreach and connecting the prediction with the customer.
The key is to focus on seamlessly incorporating cognitive technologies into existing processes while also building AI solutions that engage employees and put the customer first. The most effective way to achieve this is through the deployment of a single platform, a system of engagement that seamlessly integrates and analyzes data from all customer channels and across the organization. Only with the foundation of an end-to-end platform, which allows every employee to have access to the same information, can the Intelligent Enterprise truly begin to take flight.