Reimagining customer engagement for the AI bank of the future

AI banking

From instantaneous translation to conversational interfaces, AI technologies are making ever more evident impacts on our lives. This is particularly true in the financial-services sector, where challengers are already launching disruptive AI-powered innovations.

To remain competitive, incumbent banks must become “AI first” in vision and execution.

If fully integrated, these capabilities can strengthen engagement significantly, supporting customers’ financial activities across diverse online and physical contexts with intelligent, highly personalised solutions delivered through an interface that is intuitive, seamless, and fast.

These are the baseline expectations for an AI bank– specifically when it comes to customer engagement.

By reimagining customer engagement, banks can unlock new value through better efficiency, expanded market access, and greater customer lifetime value.

Despite big investments, banks still lag behind

In recent years, many financial institutions have devoted significant capital to digital-and-analytics transformations, aiming to improve customer journeys across mobile and web channels.

Despite these big investments, most banks still lag well behind consumer-tech companies in their efforts to engage customers with superior service and experiences. The prevailing models for bank customer acquisition and service delivery are beset by missed cues: incumbents often fail to recognise and decipher the signals customers leave behind in their digital journeys.

Across sectors, however, leaders in delivering positive experiences are not just making their journeys easy to access and use but also personalising core journeys to match an individual’s present context, direction of movement, and aspiration.

Creating a superior experience can generate significant value. A McKinsey survey of US retail banking customers found that at the banks with the highest degree of reported customer satisfaction, deposits grew 84 per cent faster than at the banks with the lowest satisfaction ratings.

Also Read: Beyond marketplaces and motorcycles: Digital banks need to formalise ASEAN’s informal economies

Rising customer expectations

Accustomed to the service standards set by consumer internet companies, today’s customers have come to expect the same degree of consistency, convenience, and personalisation from their financial-services institutions.

For example, Netflix has been able to raise the bar in customer experience by doing well on three crucial attributes: consistency of experience across channels (mobile app, laptop, TV), convenient access to a vast reserve of content with a single click, and recommendations finely tailored to each profile within a single account.

Improving websites and online portals for a seamless experience is one of the top three areas where customers desire support from banks. Innovation leaders are already executing transactions and loan approvals and resolving service inquiries in near real time.

Non-bank disintermediation

Non-bank providers are dis intermediating banks from the most valuable services, leaving less profitable links in the value chain to traditional banks. Big-tech companies are providing access to financial products within their non-banking ecosystems.

Messaging app WeChat allows users in China to make a payment within the chat window. Google has partnered with eight US banks to offer cobranded accounts that will be mobile first and focus on creating an intuitive user experience and new ways to manage money with financial insights and budgeting tools.

Beyond access, non-bank innovators are also dis intermediating parts of the value chain that were once considered core capabilities of financial institutions, including underwriting. Indian agtech company Cropin uses advanced analytics and machine learning to analyse historical data on crop performance, weather patterns, land usage, and more to develop underwriting models that predict a customer’s creditworthiness much more accurately than traditional risk models.

Increasingly human-like formats

Conversational interfaces are becoming the new standard for customer engagement. With approximately one third of adult Americans owning a smart speaker, voice commands are gaining traction, and adoption of both voice and video interfaces will likely expand as in-person interactions continue to decline. Several banks have already launched voice-activated assistants, including Bank of America with Erica and ICICI bank in India with iPal.

If reimagined customer engagement is properly aligned with the other layers of the AI-and-analytics capability stack, it can strengthen a bank’s competitive position and financial performance by increasing efficiency, access and scale, and customer lifetime value.

Also read: AI and data will be the future of the M&A banking industry (Why I decided to merge with Finquest)

Successful integration across customer touch points

For banks, successfully integrating core personalisation elements across the range of touch points with customers will be critical to delivering a superior experience and better outcomes.

The reimagined engagement layer should provide the AI bank with a deeper and more accurate understanding of each customer’s context, behaviour, needs, and preferences. This understanding, in turn, enables the bank to craft an intelligent, personalised offering.

To craft and deliver intelligent propositions, banks must take an entirely new approach to innovation. First and foremost, they need to free themselves from a product-centric view, where they develop new products and features and “push” them to customers through product bundles and discounted pricing. Instead, they should adopt a customer-centric view, which starts with understanding customer needs.

Achieving this close alignment between bank capabilities and customer needs requires time and capital to develop a realistic, evidence-based understanding of actual customers’ time-critical needs.

The capability to gauge customers’ expressed needs and anticipate latent needs in real time requires that AI and analytics capabilities be integrated with diverse core systems and delivery platforms across the enterprise.

Customer propositions can no longer be one-size-fits-all

These days, customer propositions should be intelligent and tailored, and go beyond banking to address customer needs that may involve both banking and non-banking products and services.

The full report, Reimagining customer engagement for the AI bank of the future, demonstrates how a combination of intelligent propositions, seamless embedding within partner ecosystems, and smart servicing and experiences underpins an overall experience that sets the AI bank apart from traditional incumbents.

Also Read: How Bangkok Bank worked with Pand.ai to develop a conversational AI engine to better service customers

There are five capabilities that banks will need to develop in order to design and implement their customer engagement layer to become AI-first, so read on to learn more.

Editor’s note: e27 aims to foster thought leadership by publishing contributions from the community. This season we are seeking op-eds, analysis and articles on food tech and sustainability. Share your opinion and earn a byline by submitting a post.

Join our e27 Telegram group, FB community or like the e27 Facebook page

Image credit: Karolina Grabowska from Pexels

The post Reimagining customer engagement for the AI bank of the future appeared first on e27.

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AI banking

From instantaneous translation to conversational interfaces, AI technologies are making ever more evident impacts on our lives. This is particularly true in the financial-services sector, where challengers are already launching disruptive AI-powered innovations.

To remain competitive, incumbent banks must become “AI first” in vision and execution.

If fully integrated, these capabilities can strengthen engagement significantly, supporting customers’ financial activities across diverse online and physical contexts with intelligent, highly personalised solutions delivered through an interface that is intuitive, seamless, and fast.

These are the baseline expectations for an AI bank– specifically when it comes to customer engagement.

By reimagining customer engagement, banks can unlock new value through better efficiency, expanded market access, and greater customer lifetime value.

Despite big investments, banks still lag behind

In recent years, many financial institutions have devoted significant capital to digital-and-analytics transformations, aiming to improve customer journeys across mobile and web channels.

Despite these big investments, most banks still lag well behind consumer-tech companies in their efforts to engage customers with superior service and experiences. The prevailing models for bank customer acquisition and service delivery are beset by missed cues: incumbents often fail to recognise and decipher the signals customers leave behind in their digital journeys.

Across sectors, however, leaders in delivering positive experiences are not just making their journeys easy to access and use but also personalising core journeys to match an individual’s present context, direction of movement, and aspiration.

Creating a superior experience can generate significant value. A McKinsey survey of US retail banking customers found that at the banks with the highest degree of reported customer satisfaction, deposits grew 84 per cent faster than at the banks with the lowest satisfaction ratings.

Also Read: Beyond marketplaces and motorcycles: Digital banks need to formalise ASEAN’s informal economies

Rising customer expectations

Accustomed to the service standards set by consumer internet companies, today’s customers have come to expect the same degree of consistency, convenience, and personalisation from their financial-services institutions.

For example, Netflix has been able to raise the bar in customer experience by doing well on three crucial attributes: consistency of experience across channels (mobile app, laptop, TV), convenient access to a vast reserve of content with a single click, and recommendations finely tailored to each profile within a single account.

Improving websites and online portals for a seamless experience is one of the top three areas where customers desire support from banks. Innovation leaders are already executing transactions and loan approvals and resolving service inquiries in near real time.

Non-bank disintermediation

Non-bank providers are dis intermediating banks from the most valuable services, leaving less profitable links in the value chain to traditional banks. Big-tech companies are providing access to financial products within their non-banking ecosystems.

Messaging app WeChat allows users in China to make a payment within the chat window. Google has partnered with eight US banks to offer cobranded accounts that will be mobile first and focus on creating an intuitive user experience and new ways to manage money with financial insights and budgeting tools.

Beyond access, non-bank innovators are also dis intermediating parts of the value chain that were once considered core capabilities of financial institutions, including underwriting. Indian agtech company Cropin uses advanced analytics and machine learning to analyse historical data on crop performance, weather patterns, land usage, and more to develop underwriting models that predict a customer’s creditworthiness much more accurately than traditional risk models.

Increasingly human-like formats

Conversational interfaces are becoming the new standard for customer engagement. With approximately one third of adult Americans owning a smart speaker, voice commands are gaining traction, and adoption of both voice and video interfaces will likely expand as in-person interactions continue to decline. Several banks have already launched voice-activated assistants, including Bank of America with Erica and ICICI bank in India with iPal.

If reimagined customer engagement is properly aligned with the other layers of the AI-and-analytics capability stack, it can strengthen a bank’s competitive position and financial performance by increasing efficiency, access and scale, and customer lifetime value.

Also read: AI and data will be the future of the M&A banking industry (Why I decided to merge with Finquest)

Successful integration across customer touch points

For banks, successfully integrating core personalisation elements across the range of touch points with customers will be critical to delivering a superior experience and better outcomes.

The reimagined engagement layer should provide the AI bank with a deeper and more accurate understanding of each customer’s context, behaviour, needs, and preferences. This understanding, in turn, enables the bank to craft an intelligent, personalised offering.

To craft and deliver intelligent propositions, banks must take an entirely new approach to innovation. First and foremost, they need to free themselves from a product-centric view, where they develop new products and features and “push” them to customers through product bundles and discounted pricing. Instead, they should adopt a customer-centric view, which starts with understanding customer needs.

Achieving this close alignment between bank capabilities and customer needs requires time and capital to develop a realistic, evidence-based understanding of actual customers’ time-critical needs.

The capability to gauge customers’ expressed needs and anticipate latent needs in real time requires that AI and analytics capabilities be integrated with diverse core systems and delivery platforms across the enterprise.

Customer propositions can no longer be one-size-fits-all

These days, customer propositions should be intelligent and tailored, and go beyond banking to address customer needs that may involve both banking and non-banking products and services.

The full report, Reimagining customer engagement for the AI bank of the future, demonstrates how a combination of intelligent propositions, seamless embedding within partner ecosystems, and smart servicing and experiences underpins an overall experience that sets the AI bank apart from traditional incumbents.

Also Read: How Bangkok Bank worked with Pand.ai to develop a conversational AI engine to better service customers

There are five capabilities that banks will need to develop in order to design and implement their customer engagement layer to become AI-first, so read on to learn more.

Editor’s note: e27 aims to foster thought leadership by publishing contributions from the community. This season we are seeking op-eds, analysis and articles on food tech and sustainability. Share your opinion and earn a byline by submitting a post.

Join our e27 Telegram group, FB community or like the e27 Facebook page

Image credit: Karolina Grabowska from Pexels

The post Reimagining customer engagement for the AI bank of the future appeared first on e27.

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