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As the demand for personalized financial services continues to rise, customers expect no less than exclusive experiences. However, a recent report highlights several challenges that customers face when dealing with financial service institutions (FSIs).
- 39% of customers struggle with chatbots
- 29% find it difficult to locate the information they need
- 28% report challenges with customer support
- 24% experience a lack of personalization in services, revealing the necessity for more tailored interactions.
- 20% encounter issues with integration across platforms
- 20% face difficulties when using mobile platforms
- 20% find website navigation challenging
- 17% are frustrated by digital activities not being synced across channels
- 17% find website accessibility lacking
AI can address these pain points through more personalized and user-friendly interactions, but the challenges still exist.
According to the same Salesforce’s survey, 62% of banking customers would switch FSIs if they felt treated like a number, not a person. 53% of customers would switch FSIs if services felt impersonal.
As fintech companies exert increasing competitive pressure, incumbent organizations have to step up their game in personalization efforts. However, two-thirds remain incapable of assessing the customer’s situation beyond a single point in time, according to Deloitte. This results in increased costs and poor customer experience.
Failing to achieve AI personalization in financial services can have significant bank-wide consequences. The top impacts include increased costs (62%) and slowed business agility (60%). Poor customer experience (56%) and loss of operational resilience (54%) further highlight the risks. Revenue loss (53%) and hampered brand influence (48%) are also key concerns, demonstrating the critical need for effective personalization strategies (Fair Isaac Corporate report, March 2023).
To address this demand, banking and financial services need to work with each client as for the segment of one according to Deloitte ‘s 2024 banking and capital markets overview.
15 use cases to keep in mind
- Personalized financial advisory
- Customizable banking interfaces
- Automated loan personalization
- Personalized investment portfolios
- Dynamic customer segmentation
- Behavioral biometrics for authentication
- AI-powered savings goals
- Proactive fraud alerts
- Custom rewards programs
- Chatbot-driven personalized support
- Personalized financial health insights
- Tailored credit card offers
- Personalized retirement planning
- Adaptive financial literacy programs
- Predictive analytics for future spending
Key metrics to track in personalized banking initiatives
Common metrics like Net Promoter Score (NPS) are often used, but additional metrics are essential to accurately assess personalized banking strategies, such as:
Customer satisfaction score: Measures customer satisfaction with the services.
Customer retention rate: Tracks the number of clients continuing to use personalized banking solutions over time.
Customer lifetime value: Assesses how long a customer stays with the bank and the total revenue they generate.
Service usage frequency: Measures how often clients use the bank’s services and personalized features.
Feature adoption rate: Identifies the percentage of clients who have adopted personalized features.
Cross-selling and upselling metrics: Evaluates if personalized offers helped sell additional products.
Sentiment analysis: Analyzes customer feelings about the bank from social media, reviews, and other platforms.
Surveys and feedback forms: Gathers direct responses from clients on their banking experience.
Tracking these metrics is vital for successfully implementing and improving personalized banking strategies.
Before working on personalization…
The vast majority of customers – 91 % – want personalized recommendations. Banks must focus on understanding the customer journey by monitoring:
- Buying patterns
- Preferred communication channels
- Information they seek
There are banks that, following the principles of personalization, propose individual features based on their customers’ age. As seen with the young and social networking personalities who are likely to use such services, for instance, Monzo provides splitting of the restaurant bill.
Banks can create more effective marketing strategies when they know more about their customers.
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