Banks in the Corona Crisis – Focus on Customer Experience and Increased Efficiency

How Artificial Intelligence Accompanies Banks Through and After the Crisis

Many companies as well as banks are facing many challenges but also opportunities in this crisis. Continued rising customer expectations are juxtaposed with the need for efficiency improvements as well as the establishment of flexible operating models to ensure business continuity.

In each of these areas, Artificial Intelligence is a key component to establish tools and services that meet customer expectations while driving efficiencies and enabling dynamic and flexible operating models through automation or tailored information delivery to the advisor or service center agent.

New technologies may not solve all banks’ problems, but they are critical to success. Especially in today’s environment, where customers are demanding improved customer experiences and banks need to optimize efficiencies and costs at the same time.

Financial institutions also have high expectations when it comes to artificial intelligence (AI), and COVID-19 raises them even higher.

AI technology supports companies in numerous use cases

80 percent of data in an organization today is unstructured data. Unstructured data can be found in emails, word processing documents, PDF files, image, audio and video files, social media articles or mobile text messages. These masses of data often hide business-critical or personal information that is essential for process automations.

The ability of AI systems to analyze and contextualize unstructured data enables organizations to explore a wide range of applications, including visual perception, speech recognition and generation, reasoning, decision-making and action, and, in general, adaptability to changing environments.

Expectations on the part of banks are correspondingly high. A study by the consulting firm Eurogroup Consulting and htw saar showed that banks expect competitive advantages and efficiency gains (including cost savings) from the use of AI.

In the context of COVID-19, these expectations are now significantly increased.

After all, in response to the crisis, most banks need to meaningfully transform their customer outreach and communication, as well as their operating models, to meet pressing needs – while increasing efficiency. AI offers many opportunities in this regard.

Improve experiences in a way that also considers efficiency

While in normal times many customers struggle with the transition to digital, in the current environment the adoption of digital tools is increasing rapidly – and so are customer expectations.

In the current uncertain environment, many customers are relying on the stabilizing power of established banks. Many financial start-ups have already seen a downward trend in new account openings. As a result, many financial startups will try to entice customers with even more new and additional features and services, thus continuing to fuel customer expectations and service demands on the part of established banks as well.

The economic impact of the coronavirus will thus increase the need for banks to simultaneously improve efficiency and the customer experience. How can financial institutions achieve this?

Banks can do this by improving digital self-service (“self-service”), but also by making operational tradeoffs. Virtual assistants, intelligent search capabilities, or even email automation, reduce incoming inquiries at the service center or directly to advisors.

Digital service and sales are more cost-effective than branch and phone-based approaches. By intelligently merging customer, market and process information, banks can enable personalized, digital services for their customers and also help their advisors serve their existing customers as well as tap into new customer segments via dynamic 360° customer views.

In the wealth management space, for example, features such as automated delivery of advisory solutions ranging from house-based investment recommendations to providing a daily summary of relevant information tailored to the customer’s portfolio can be offered. Of course, always with the ability to receive further support on demand, as well as schedule a phone or video call. Affinity models determine for the sales staff which customer has an affinity for which product and why, and how best to address them. Consultations that take place can be recorded automatically if required and analyzed for further insights or simply for filing.

Implementation of a dynamic and flexible operating model

Banks around the world are transforming their operating models to ensure business continuity. Still, many employees or call center agents work out of the office because the infrastructure and processes do not support remote working. While not all employees are able to work optimally, the burdens are increasing, such as in the credit sector due to the special loans requested or the threat of loan defaults due to insolvent customers.

In addition to optimizing remote work in general, this means, first, that banks should continue to invest in promoting digital engagement and digital sales, as well as digitally transforming and executing mass and core banking processes.

Increased use of digital capabilities will lead to increased customer engagement. I believe the pandemic will be a catalyst for the use of digital banking tools and will also change the way customers interact with their banks.

Many Chinese banks have already led the way by introducing new services during the pandemic that allow customers to easily complete a variety of financial services transactions such as basic banking, insurance, foreign exchange and asset management.

However, data analytics also helps retain customers by predicting customer churn early and providing advisors with recommendations for action.

An AI-based omni-channel strategy that gives customers access via various digital channels (such as via the Internet, a virtual assistant, live chat or telephone) and then bundles this information for automated processing or subsequent data analysis also pays off when customer inquiries increase. With the appropriate strategy, customer satisfaction can be ensured, efficiencies can be increased through further automation, and processes can additionally be made more flexible.

However, not only customer inquiries and sales activities can be (partially) automated using artificial intelligence, but also entire process routes in the back office area. By combining, analyzing and processing structured and unstructured information, documents such as contract papers, balance sheets or e-mails can be processed automatically, and credit default probabilities or risk assessments can be calculated. This also allows the immense number of special loans to be processed better and more securely.

Conclusion

Many companies as well as banks are facing many challenges but also opportunities in this crisis. Continued rising customer expectations are juxtaposed with the need for efficiency improvements as well as the establishment of flexible operating models to ensure business continuity.

In each of these areas, Artificial Intelligence is a key component to establish tools and services that meet customer expectations while driving efficiencies and enabling dynamic and flexible operating models through automation or tailored information delivery to the advisor or service center agent.

As the "Head of Data Strategy & Data Culture" at O2 Telefónica, Britta champions data-driven business transformation. She is also the founder of "dy.no," a platform dedicated to empowering change-makers in the corporate and business sectors. Before her current role, Britta established an Artificial Intelligence department at IBM, where she spearheaded the implementation of AI programs for various corporations. She is the author of "The Disruption DNA" (2021), a book that motivates individuals to take an active role in digital transformation.

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