5 ways AI is revolutionizing consumer banking

Arnold Koudijs,

Banking customers today want personalized experiences, accurate information, frictionless processes, and prompt service – and they want it all now. To help respond to customer needs, some banks are relying on new channels, apps, or digital tools, like web self-service and automated chatbots. But these digital technologies are not inherently “intelligent” nor do they automatically improve the customer experience or relationship. To build relationships over time that establish trust with each customer, create personalized experiences, and increase loyalty and profitability for the organization, banks need to be able to understand the context of a customer’s current situation as well as the history of that customer’s journey. AI-based decisioning tools can help.

How are banks best utilizing sophisticated AI to support interactions between their organizations and customers, as well as between their customers and agents?

To provide some guidance, Scott Andrick, Pega’s senior director of global retail banking, joined Annette Kerlin of partner Adqura in a recent webinar to discuss how AI is being used by financial services organizations to personalize consumer experiences at scale and improve both speed-to-market and response rates. As the Chief Customer Experience Officer at Adqura, Annette brings to the conversation first-hand experience in the creation and delivery of AI-based customer engagement. From their discussions, we’ve highlighted for you below the five most results-based uses for AI in the financial industry.

5 ways consumer banking is being revolutionized with AI

1. Digital Services

Traditional channels like call centers and basic digital tools like IVR, chatbots, and self-service websites, are unlikely to ever go out of use, but they can be enhanced with AI to provide more individualized and consistent service. Machines are now sophisticated enough to understand a person’s emotions and gather information to best assist the customer or representative on the other end. With that data, an AI-based, centralized decisioning tool can then analyze context and recommend a range of next best actions to representatives and customers, such as proposing new products, providing educational information, or simply tweaking the current services and products.

AI-based decisioning can also help banks expedite workflow across existing digital services. For example, intelligent virtual assistants may be used to provide support for simple banking needs, while inquiries identified by the AI as more complex and subjective may be referred to agents. This approach not only ensures efficiency but also increases the time specialists have to work with customers on more challenging questions. A real-world example of where this approach is working well is Bank of America’s intelligent virtual assistant, Erica®. Launched in 2018, the AI-driven tool has helped Bank of America connect with over 4 million users.

2. Personalization

Personalization is what everyone seems to be talking about these days but getting personalization right is the key. There is a fine line between utilizing a customer’s preferences and needs to deliver real-time, relevant information and making the person feel as though they’re being followed online. AI can be used to create a smarter, personalized user experience – it just has to be done properly. For example, tracking data like a customer’s spending and purchase history over the course of a few months may create an opportunity for outreach regarding budgeting and saving. By presenting a customer with relevant information at the right times, banks can provide a very individualized service. When personalized AI is used appropriately, it increases customer satisfaction and retention, creating mutual value for the customer and the organization.

3. Customer Value Management

While many banks have moved past completely separate channel silos (the worst case), they are often only in a semi-connected environment. This still limits visibility into the customer’s history, preventing banks from fully understanding the context of a customer’s actions and their overall journey. For consistent experiences, banks need an integrated enterprise system that can consolidate a customer’s data from all sources (history, channels, apps, real-time context, APIs to third-parties) and can then use AI to provide real-time recommendations to increase loyalty, retention, and value. This combination of AI and omni-channel decisioning can create massive value across the customer experience.

When a central brain is used to analyze structured and unstructured data, such as all of a customer’s interactions, organizations can plug that data into a larger view of each customer’s end-to-end journey. AI can then help generate a response that is tailored for both the customer’s immediate need and bank’s lifetime value. Omni-channel capability allows for these messages to be delivered in the customer’s preferred channel, making channels the message bearers for relevant and timely outreach. By using data collected from customers and pairing that with predictive analytics, banks can reach customers and create value in ways they haven’t been able to before.

4. Bundled Offers

As people begin to expect more customization and personalization in their lives and products, curated financial services and advice will become more popular. AI is essential for knowing what services or offers to provide the customer – it allows banks to take a holistic approach to customer service. Using AI-based decisioning that is informed by customer profiles and preferences, consumer banks can dynamically package products and services together based on personalized needs. The benefits of this approach are many. For the bank, more products are associated with greater customer loyalty and lifetime value. On the customer’s end, there is value in the convenience of working with a trusted organization that understands their personal needs. As the adoption of AI-based decisioning tools grow, relationship managers will be able to more accurately and consistently assist a customer with the best products and services for their financial needs.

5. Actionable Insight

While content may be king, we live in an oversaturated world where people ignore and block out whatever they are no longer interested in. In short, just because you can post a whole lot of digital ads doesn’t necessarily mean you should – ads that are irrelevant become nothing more than wallpaper.

How can banks determine what message is right for each customer? By using AI to understand a person’s patterns, behaviors, and needs at a particular moment, then applying predictive modeling to determine the best action to take, offer to make, or message to send, banks can create offers and determine actions that are most relevant. This next-best-action approach leverages AI-based information to help guide an organization’s marketers to understand the best time for sharing content and the most appropriate channels for growing customer relationships. It can also advise service reps on a personalized conversation they may want to have with a customer, such as an upcoming bill payment or an alert regarding a low account balance.

Even with the regulatory complexities that accompany financial industry products and services, there are huge opportunities to improve customer engagement through personalized experiences.

With more than 85% of customer interactions starting in digital channels, AI is driving massive changes in personalized customer engagement. Watch the full webinar replay for a deeper dive by Scott and Annette into the nuts and bolts of how AI is being used to impact long-term relationships with financial consumers plus practical how-to advice to providing consistent, one-to-one, always-on experiences.

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Tags

  • Industry Group: 金融サービス
  • トピック: 人工知能
  • 課題: カスタマー エンゲージメント
  • 課題: One to One マーケティング

About the Author

As Pega’s Director and Industry Principal for Financial Services, Arnold Koudijs helps some of the world’s most recognizable financial institutions leverage real-time decisioning to manage risk, improve customer engagement, increase revenue, and achieve digital transformation.