Data Analytics in Banking: How to Use Data for Financial Services Marketing

Leveraging data analytics in bankingand the insights it produces has become an effective strategy for financial services marketingby creating relevant engagements and personalized banking experiences for account holders. Recent researchcommissioned by Alkami, in partnership withThe Center for Generational Kineticsfound that digital banking Americans who are satisfied with a financial provider's capabilities to use their data to make relevant product and transaction recommendations are most likely to engage with other products at the company. Bank and credit union leaders are poised to be pacesetters in the industry by transforming digital banking solutionsfrom a historical service channel into a digital sales and service platform, where the data-informed digital banker can deliver relevant campaigns and personalized bankingat scale on product offers, financial wellness support and education, channel utilization benefits and more.

Data Strategy Can Lead to Digital Maturity

Data creation on the internet is expected to rise to 147 zettabytesby the end of 2024. With the U.S. having over 2,700 data centers, as of June 2024, estimates suggest that 402.74 million terabytesof data are being created every day including content that is newly generated, captured, copied, or consumed.

Big data has been a buzzword throughout the financial services industry - but historically, data has been used as a method to measure key performance indicators, and used in very tactical ways to accomplish strategic goals in areas such as, but not limited to:

• Risk Management
• Consumer and Business Loan Underwriting and Processing
• Marketing Targeting and Analysis
• Product Innovation
• Fraud Detection
• Business Operations and Report Generation

With technological advancements around digital banking solutions, artificial intelligence in banking(AI) and the focus on extracting insights to make data actionable, financial institutions need to embrace a mindset shift that will create the path to use data for strategic planning and decisions, leading the institution to data-driven command.

The utilization and integration of data into overall business practices has accelerated financial institutions into being leaders in digital maturity. With consumers demanding that their bank or credit union "know them personally" and be able to deliver communications that resonate with them.

Alkami's recent research report, Digital Sales & Service Maturity Model, reveals that the most digitally mature institutions have a culture immersed in data, and a sharp focus on data-proven results, not intuition, to make nearly every decision throughout the organization. These banks and credit unions prioritize returns on their investments and differentiate themselves by their ability to maximize the data they have, and extract its value.

The commitment to data modernization and having fully-deployed solutions such as data lakes, integration, enrichment, AI and predictive models(uses data to predict or forecast future behaviors) can close the competitive gap for financial institutions throughout different areas of the business operations.

A component of the data pool is transaction data, already found in a financial institution's ecosystem. A transaction happens when funds move in or out of an account. What makes this data a critical asset to bank and credit union leaders is the intel buried inside the transaction - date, time, location, purchase type, merchant type, total spent, payment type used, channel used, and more. The data can then go through a transaction enrichmentprocess, where analysis can derive insights around behavior and spend patterns. It has no biases, and provides the behaviors of account holders across the history of the relationship with the financial institution.

Recommendations for Regional Community Financial Institutions (RCFIs) To Build a Data-Driven Organization

The 2024 Alkami Telemetry Data Reporthighlights the importance of integrating strategies based on the behavioral intelligence derived from transaction data. To become data-informed digital bankers, financial institutions should focus on the following actions:

• Invest in Data Infrastructure:Develop a data infrastructure that supports the collection, analysis, and utilization of data across all digital channels.
• Develop a Data Strategy:Define the goals and objectives of your data strategy, focusing on how data can improve account holder experiences and drive business growth.
• Partner with a Vendor for Transaction Enrichment: Engage with a partner that has shown success with taking account holder transactions and cleansing them to provide additional information and insights around that occurrence.
• Use Transaction Data: The richest data already in a bank or credit union's ecosystem, it provides insights into spend patterns and behavioral trends.
• Enhance Digital Tools:Invest in digital tools that provide personalized insights, automated alerts, and customized recommendations to enhance account holder engagement.
• Foster a Data-Driven Culture:Make a commitment to setting up your financial institutions to have a culture of data-driven decision-making with a cascade approach that includes training and collaboration from all staff.
• Align with Technology Partners:Partner with technology providers to leverage advanced analytics and artificial intelligence capabilities.

Along with a data strategy that will cross all departments within a financial institution, security plays an important role in protecting both the organization and the account holders it serves. The same researchabove also found that 56% of digital banking Americans are "okay" with their financial data being used to help inform and improve their financial provider's privacy and security, including 61% of millennials, the highest of any generation.

Activating Artificial Intelligence In Banking for Financial Services Marketing

Banks and credit unions, in order to remain relevant and efficient, will need to navigate the many use cases that AI presents in financial services, and build a strategy around gaining expertise, experimentation and implementation. The digital banking experience continues to be a focus for leaders in order to meet the ever growing demands for an exceptional platform, powerful enough to deliver both sales and service within the same channel.In the research mentioned above, 45% of digital banking Americans are also "okay" with their financial data being processed by AI if it gives them a better banking experience, including 52% of younger millennials compared to 42% of baby boomers.

Additionally, data plays a key factor in AI predictive models, which thoroughly analyzes a financial institution's comprehensive account holder transaction data. This distinctive data is the fuel that powers the models, delivering insights that forecast future behaviors and identify trends to make messaging and engagement with account holders more relevant and individualized. Eighty-three% of digital banking Americans say they would not be hesitant if their financial provider would use AI for marketing, such as receiving relevant offers for new deposits, loans and/or credit card accounts based on financial account history. AI predictive models are a key factor in the AI toolbox that can anticipate the account holder's financial journey with efficiency and speed.

Financial institutions can take a few key steps to jump start their AI strategy:

1. Get educated and build AI literacy across the organization.
2. Establish key performance indicators, or clear results that the bank or credit union would deem successes.
3. Use transaction enrichment to make sure all data is clean, analyzed and in order
4. Develop a framework to prevent biases in AI.
5. Ensure there is a proactive approach to be able to monitor the progress and use cases, and then shift direction if needed.

AI is set to transform banking processes, and its use cases will continue to define the strategic approach that financial institutions adopt inside their organization. Banks and credit unions need to engage with their account holders and communicate AI's role in interactions, gaining intel into their perspectives.

A Distinction to Strive For: The Data-Informed Digital Banker

Becoming a data-informed digital banker will empower bank and credit union leaders with the insights and intelligence to continue building their account holders' product portfolios and capture share of wallet from the competition. By leveraging transaction data, enhancing digital banking solutions, and prioritizing account holder engagement, financial institutions are poised to deliver personalized banking at scale driving business growth and building stronger, more resilient account holder relationships.

FAQ's

Q1: Why is leveraging data important for financial institutions? Leveraging data allows financial institutions to create personalized banking experiences for their account holders. By using insights from data, banks and credit unions can provide relevant product recommendations and enhance engagement, which increases account holder satisfaction and loyalty.

Q2: What benefits do financial institutions gain from transforming digital banking into a digital sales and service platform? By transforming digital banking into a digital sales and service platform, financial institutions can deliver personalized campaigns and banking services at scale. This approach enhances product offers, financial wellness support, educational resources, and channel utilization benefits, leading to improved account holder experiences and increased business growth.

Q3: How does data creation and usage impact financial institutions?With the massive amount of data generated daily, financial institutions can harness this information to improve various aspects of their operations, including risk management, loan processing, marketing, product innovation, fraud detection, and business operations. This data-driven approach leads to better decision-making and strategic planning.

Q4: What role does transaction data play in financial institutions?Transaction data is a critical asset for financial institutions as it provides detailed insights into account holder behaviors and spending patterns. By analyzing transaction data, banks and credit unions can offer personalized banking, and gain intel into the account holder's entire financial history from the start of the relationship.

Q5: What steps can regional community financial institutions (RCFIs) take to build a data-driven organization?RCFIs can build a data-driven organization by:

• Investing in data infrastructure
• Developing a comprehensive data strategy
• Partnering with vendors for transaction enrichment
• Using transaction data to gain insights
• Enhancing digital tools for personalized engagement
• Fostering a data-driven culture within the organization
• Aligning with technology partners for advanced analytics and AI capabilities

Q6: How does AI contribute to financial services? AI helps financial institutions remain relevant and efficient by enhancing digital banking experiences, improving sales and service channels, and providing predictive insights through data analysis. AI predictive models can forecast account holder behaviors, identify trends, and deliver personalized marketing messages, making interactions more relevant and individualized.

Q7: What steps should financial institutions take to implement AI effectively?To implement AI effectively, financial institutions should:

• Build AI literacy across the organization
• Establish clear key performance indicators
• Ensure transaction data is clean and analyzed
• Develop a framework to prevent biases in AI
• Monitor AI progress and use cases, adjusting strategies as needed

Q8: How can financial institutions ensure data security while using it for personalization?Financial institutions can ensure data security by integrating clear and consistent security measures into their data strategies, protecting both the organization and their account holders. Transparency with customers or members about how their data is used and focusing on improving privacy and security can build trust and alleviate concerns.

Q9: What is the significance of becoming a data-informed digital banker? Becoming a data-informed digital banker empowers financial institution leaders to leverage transaction data and deliver personalized banking services at scale. It also is a mindset which transforms decisioning around banking and marketing strategy from hunch-based to metrics-based.