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5 Quick Wins for Data Analytics in Banking

Joan Clark, Director of Product Management & John Redmond, Product Manager

Financial institutions have a huge amount of data from their account holders just waiting to be activated. By leveraging data analytics in banking effectively, banks and credit unions can enhance account holder satisfaction, reduce fraud, grow share-of-wallet and increase revenue. However, after implementing a data strategy, financial institutions may struggle to quickly gain tangible benefits from their infrastructure. Multiple data sources, uncategorized data, and the lack of one source of truth all contribute to delayed outcomes for data analytics in banking. However, executive teams expect results fast, and their teams should strive to achieve some goals within the first several months of implementing a new data strategy at their institution. Here are five wins your financial institution can accomplish in the first 90 days of implementing a well-executed data strategy.

 

1. Fraud Detection and Prevention

Fraud detection and prevention are paramount for protecting both the financial institution and its account holders. By analyzing transaction patterns, geographic locations, and other data points, financial institutions can identify anomalies that indicate fraudulent activity to feed this data to their fraud detection and prevention solution. 

Implementing a data feed to a third-party fraud detection system can lead to:

  • Minimized losses: Early detection of fraud reduces financial losses for both the financial institution and its account holders.
  • Increased account holder trust: Proactively preventing fraud boosts account holder confidence in the institution’s security measures.

 

For instance, if small transactions start appearing in an unusual location, this could be a precursor to larger fraudulent transactions. Detecting these early on helps prevent more significant breaches.

 

 2. Account Holder Segmentation

Effective account holder segmentation allows banks and credit unions to tailor their services and financial services marketing efforts more precisely. By segmenting account holders based on product usage, transactions with other institutions and lifestyle indicators, financial institutions can create more personalized experiences. 

This segmentation can include:

  • Young families: Offering products like savings accounts for children.
  • International travelers: Recommend a credit card with travel rewards.
  • Retirees: Providing retirement savings plans or reverse mortgages.

 

Segmenting account holders in this way ensures that marketing efforts are relevant and impactful, improving account holder engagement and satisfaction.

 

3. Cross-Sell and Upsell Opportunities

Using data to identify cross-sell and upsell opportunities can significantly increase revenue. By analyzing current product holdings and account holder behavior, financial institutions can predict and recommend the next best product for each account holder. 

This could involve:

  • Artificial intelligence (AI) models: Using AI to suggest products based on account holders’ life stages, such as offering a home equity line of credit (HELOC) to parents with children going to college.
  • Product recommendations: Targeting account holders who hold certain products with complementary ones, like travel credit cards for frequent travelers.

 

This strategy not only boosts sales but also enhances account holder satisfaction by meeting their evolving needs.

 

4. Churn Prevention

Identifying account holders at risk of leaving and implementing retention strategies is vital for maintaining a stable account holder base. 

Data analytics in banking can help in:

  • Monitoring transaction patterns: Noticing when account holders start moving their deposits or making fewer transactions can be a sign of potential churn.
  • Proactive campaigns: Engaging at-risk account holders with special offers or personalized services to win them back.

 

For example, if an account holder stops making direct deposits or their mobile banking activity decreases, it’s a signal for the financial institution to intervene and re-engage the account holder.

 

5. Proactive Alerts

Providing proactive alerts based on account holder data can enhance account holder experience and loyalty. 

These alerts can help account holders manage their finances by notifying them of:

  • Unusual spending patterns: Alerting account holders if they have multiple subscription services, which they might want to consolidate to save money.
  • Financial health tips: Sending reminders to save or invest based on their spending habits.

 

Such personalized alerts not only add value to the account holder’s banking experience but also position the financial institution as a helpful financial partner.

 

Bonus Win for Data Analytics in Banking: Rewards Programs that Drive Loyalty

Instituting rewards programs based on transaction data can drive account holder loyalty. For example, offering discounts with local merchants for using the financial institution’s debit card can incentivize account holders to use the card more frequently, thereby increasing transaction volume and account holder satisfaction.

 

Leverage Data Analytics in Banking to Speed Results

By implementing these data-driven strategies, financial institutions can achieve quick wins that enhance account holder trust, improve operational efficiency, and drive revenue growth. A well-executed data strategy not only helps in retaining account holders but also positions banks and credit unions as proactive and account holder-centric institutions.

Learn more about data analytics in banking.
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Alkami Technology Digital Banking Solutions
Alkami Technology, Inc. is a leading cloud-based digital banking solutions provider for financial institutions in the United States that enables clients to grow confidently, adapt quickly and build thriving digital communities.
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