9Digital strategy
GO2bank (short for ‘Exploring Growth Opportunities and Brand Expansion) launched in 2021 and is expanding rapidly, becoming the focus of Green Dot’s direct-to-consumer initiative. The company aims to transform GO2bank into a significant brand in the paycheck-to-paycheck community, which includes over 100 million Americans. With its revenue surging by 40% in Q1 2023 compared to the same period last year, continuous investment is planned in GO2bank to fuel its growth. Enhancements will include digital upgrades, credit activities, distribution alternatives, and significant marketing investments to the tune of $40-$50 million annually. Walmart remains the largest distributor of Green Dot products, contributing 21% of Green Dot’s total operating revenue in 2022. Despite the launch of Walmart’s ONE Finance accounts which may compete with GO2Bank, Green Dot believes the Walmart relationship will continue to flourish.
Fraud
New account fraud is posing an increasing threat to financial institutions are facing an increasing threat from fraud. As criminals adapt to sophisticated authentication methods, banks need to harness what they know about their customers to detect unusual or suspicious activities across all banking channels. Fiserv suggests that AI and machine learning could help detect fraud faster by providing a comprehensive picture of account activities. The company’s VP of card risk solutions also highlighted the need for continuous education of account holders about common fraudulent tactics and encouraging them to enable transaction notifications. Despite advancements, financial institutions continue to struggle with balancing fraud protection and user experience.
Customer engagement
Offering support for female customers is a growing trend in banking, as a result of research that women generally feel less confident about managing their finances. A BMO Financial Group survey found that 79% of women would like more help improving their financial literacy. The report also outlines strategies by other banks, such as KeyBank and CNB Bank, to educate and empower female customers. One example of this is Traditions Bank in Pennsylvania which launched a 10-month high-yield CD combined with a monthly donation to a scholarship fund for girls. The initiative which aims to generate more deposits and support among female customers, managed to add over $1,000 to its scholarship fund within the first month.
AI/ML
Key strategies for effectively implementing AI projects in banking include finding a common language for discussing AI, fostering team building and managing expectations, and learning from both successes and failures. At Truist Bank, teams are encouraged to use ‘cognitive courtesy’ to communicate effectively with non-tech staff and are cautioned against ‘unconscious incompetence,’ or forgetting there are things one doesn’t know. They also offer realistic communication and timeframes in AI projects, given their complexity and the regulatory environment. Lastly, sharing and learning from project mishaps help to foster a supportive and growth-oriented culture.
Customer engagement
Customers are increasingly interacting with banks and credit unions across diverse channels like chatbots, social media, emails, mobile apps, websites, and traditional call centers. While these options offer flexibility, they also present a challenge for financial institutions to ensure consistent, high-quality customer support across all channels and often become a source of inefficiency and frustration due to fragmented and disjointed communications. This situation could erode trust and drive customers to look for other financial providers. To build a satisfying multichannel customer service experience, financial institutions are advised to
- Embrace technological integration using advanced customer relationship management (CRM) systems,
- Invest in advanced analytics to track customer interactions and generate actionable insights,
- Leverage automation and AI for handling routine inquiries and streamlining tasks,
- Empower all customer care employees with access to unified customer data and comprehensive training,
- Encourage and act upon customer feedback at every level to identify pain points and innovate, and
- Regularly monitor customer feedback and track key performance indicators (KPIs).
Customer experience
The shift towards digital and self-service solutions in retail banking continues with 41% of US customers identified as digital-only and 59% preferring self-service tools. However, only 31% of consumers believe financial services use technology effectively to create great customer experiences. To meet customer expectations, banks need to offer seamless, personalized services and easy access to transparent information, with a focus on customer-first practices. Consumers prefer friction-free interactions and expect financial institutions to understand their unique needs and offer personalized solutions. To enable better digital experiences, banks should leverage automation and AI to streamline processes, offer customized services, and deliver personalized advice. The customer experience is as critical as the products and services a company offers, making it essential for banks to focus on customer needs and expectations, and to invest in AI, data, and CRM tools to deliver high-quality service.
Human resources
The financial industry is facing a significant challenge in finding candidates with tech skills. A survey by Infosys revealed that a lack of digital skills among candidates is a primary concern for banks. This issue has been exacerbated by generational changes, rapid technological advancements, and the need for rigorous background checks and clearances. To close the digital skills gap, leaders in the financial industry are advised to encourage current employees to upskill, boost productivity and retention through feedback systems and personal development incentives, and understand job candidates’ priorities. Embracing diversity and inclusion in recruitment processes can also help tap into a wider talent pool. Offering unique perks, such as flexible work arrangements, can help attract and retain top talent.
Embedded finance
Embedded finance has become an integral part of the retail sector, creating a more unified customer journey. Companies like Nordstrom have embraced this approach, offering credit applications and payment vehicles across multiple channels to enhance the customer experience and improve conversion rates. The retailer also offers a rewards program and store-brand credit cards to increase customer loyalty. Nordstrom’s strategy includes leveraging consumer psychology, providing instant gratification through in-store pick-ups, and using augmented reality (AR) in its app for virtual try-ons. The retailer also uses Nordstrom’s TextStyle service to offer personalized shopping recommendations based on customer preferences and purchase history. Looking ahead, Nordstrom sees the future of embedded finance in retail as a mix of digitization, business management, and superior customer service, potentially evolving into embedded customer service. He also highlighted the importance of building a customer “trust score” using AI and user-permissioned data for personalized experiences while maintaining privacy.
Data/AI
Banking employees often struggle to find relevant and accurate information due to siloed data and outdated technology. Recent research shows that 16% of bank staff are required to sift through seven or more sources to accomplish their tasks, with 73% reporting unclear storage locations or lack of permission to access certain data. The banking industry is exploring Generative AI to streamline this process, by summarizing information and navigating through unstructured data forms. Notably, Morgan Stanley’s Wealth Management unit uses OpenAI’s Generative AI for an employee-facing chatbot and for automating notes to customer service agents. However, Generative AI’s occasional production of incorrect or nonfactual information is a challenge. OpenAI is developing a “process supervision” approach to counteract this issue, aiming to enhance logical reasoning in AI. Future AI implementations must consider who bears responsibility if the tool provides erroneous information and should likely include a fact-checking mechanism to ensure data accuracy.
