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Empowering customers with behavioral data and AI-driven personalization

Alok Benjwal
3 May 2024

In today’s competitive banking landscape, customers demand personalized experiences tailored to individual needs and preferences. However, the current generic interactions and misalignment with financial goals leads to dissatisfaction with the current state of customization offered by banks. A report by Blend found that 65% of consumers wanted banks to make it easier to shop and find tailored products, and 72% felt product offers to be more valuable when tailored to their personal needs. This illustrates the gap between customer expectations for personalized services and the reality of banking experiences.

Generative AI is a key tool that has emerged to drive personalization. Customers love it, with the Capgemini Research Institute’s 2023 survey revealing that 73% of 8500+ consumers trusted content written by it and 53% have faith in generative AI-assisted financial advice. With the scramble to develop such solutions for enhanced business outcomes, business leaders should know how this technology can drive personalization for their businesses.

Content creation at scale

Generative AI revolutionizes media creation, infusing personalization into every aspect from text to images. This approach ensures that tailored content resonates uniquely with each consumer, be it product descriptions, blogs, or video scripts. Replacing labor-intensive manual efforts, generative AI streamlines the process, delivering messaging and visuals based on individual preferences, demographics, and past behaviors.

AI algorithms swiftly analyze real-time consumer interactions and transactions, ensuring content remains relevant and effective across platforms. In contact centers, Generative AI addresses common queries, reducing agent costs and resolution times, elevating overall customer experience.

CRI’s survey highlights this approach’s significance, with 29% of executives extensively leveraging generative AI for content creation and another 26% embracing it to some extent. Ally Financial, a US all-digital bank, used generative AI to reduce marketers’ production time by up to 2-3 weeks, achieving average time savings of 34% with prompt accuracy of 81% (indicating users generally received relevant content output).

Hyper-personalized recommendations

Generative AI utilizes customer data to analyze past interactions, transactions, and preferences, generating tailored product and service recommendations. This fosters trust, and contributes to loyalty, retention, and revenue growth through repeat purchases and brand advocacy.

Detailed customer profiles enable targeted recommendations, such as credit cards and insurance, based on individual preferences. Real-time analysis suggests agent responses and identifies cross-selling opportunities, catering to specific consumer needs.

According to Capgemini’s research, 60% of executives use generative AI extensively for customized customer experiences, and 57% for creating personalized customer and brand avatars. Mastercard’s Dynamic Yield developed Shopping Muse, leveraging colloquial language to deliver customized product recommendations and predict shopping intents based on the past purchase data and behavior, enhancing shoppers’ discovery experience.

Dynamic and engaging interactions

Generative AI chatbots mimic human responses, providing round-the-clock support, engaging in natural conversations, and adapting to user mood or intent. This enhances service perception, offering personalized advice and support, ultimately boosting engagement and loyalty.

In a Capgemini survey, 83% of organizations deemed chatbots relevant for automating customer service and improving knowledge management. Wells Fargo’s chatbot, Fargo, manages 20 million interactions, offering banking services and financial advice via voice and text, powered by the Tachyon AI platform.

Tailored marketing and advertising

Generative AI transforms marketing with targeted campaigns, replacing generic ads with personalized content across different media formats. Historical data informs tailored messaging, optimizing clickthrough and conversion rates. Financial institutions leverage generative AI for personalized content, driving loyalty and engagement with instant cross-selling and up-selling offers.

Consumers embrace generative AI, with 62% comfortable with its use in marketing, per Capgemini Research Institute survey. For example, Square integrates this technology into its business software, streamlining email marketing with personalized content and supporting blog copywriting for SEO improvement and resource savings.

Towards individualization

Marketing strategies have used technology to shift from broad-based campaigns to targeted approaches using group-level data. With generative AI, we move to individualization, where AI platforms craft unique experiences tailored to each user’s specific needs and preferences. This can incorporate factors like real-time behavior, mood, preferences, goals, and health metrics. To illustrate, while personalization involves targeting segments with credit card campaigns based on transaction history, individualization takes it further. It allows credit card companies to monitor each customer’s financial actions, adjusting credit limits dynamically based on their creditworthiness and current financial situation using AI/ML. This ensures personalized, responsible credit management.

Deploying sophisticated generative AI operationalizes, at scale, the insights generated from AI/ML algorithms. This optimizes resource allocation, improves customer engagement, and growth and efficiency strategies. According to Capgemini, 58% of organizations integrate generative AI into marketing, and 50% of financial services firms allocate budget to it . How does this technology enhance business and customer outcomes for financial institutions?

Generative AI’s technological prowess and operational capabilities will lead to a paradigm shift in how businesses can be ran efficiently. To extract the maximum value out of generative AI applications, a leader must understand the technology and how it can enhance existing business processes, along with clarity on the outcomes it can create. Banks and financial institutions will need to rapidly adopt these technologies in a volatile, competitive environment to ensure that customers’ demands for greater personalization and convenience are met quickly and effectively.

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Alok Benjwal

Vice President, Insights and Data, Banking and Payments
Alok is a seasoned executive with more than 2 decades of experience in customer analytics, digital marketing, marketing and journey optimization, personalization and advanced data science