Leveraging accurate data for a deeper insight on merchants, consumers and customers
Alethea Avatara, SVP, Product Management Director, Wells Fargo
Below is an insight into what can be expected from Alethea’s session at Digital Banking 2023.
The views and opinions expressed in this article are those of the thought leader as an individual, and are not attributed to CeFPro or any particular organization.
How can real-time data be leveraged to enhance a financial institution’s strategy?
Real-time data enables the most up-to-date information to be available to the bank and its customers. By leveraging real-time data, banks can make more informed, data-driven decisions, improve customer experiences, manage risks effectively, and optimize operational efficiency. However, to effectively use real-time data, banks need to invest in a robust data analytics infrastructure, cyber security measures, and skilled data scientists to interpret and act upon the insights obtained from the data. When real-time data is used in conjunction with data science, machine learning, and AI, it has the potential to help banks gain a competitive edge as well as increase revenue and customer satisfaction. It can also help reduce fraud losses and operating expenses.
Here are a few examples of how the use of real-time data can address key opportunities facing financial institutions today:
- Improved Customer Insights: Banks can gain deeper insights into customer behaviors and preferences by analyzing transaction data, online interactions, and social media sentiments in real time. These insights can be used to tailor personalized offers, optimize marketing campaigns, improve customer service, and deepen relationships with customers.
- Fraud Detection and Prevention: Leveraging real-time data along with advanced analytics and machine learning algorithms can quickly analyze large amounts of data to spot unusual patterns and take immediate action to prevent fraudulent transactions.
- Optimized Operational Efficiency: Real-time data can be used to make operational processes more efficient and reduce customer contacts. It can support resource allocation, inventory management, and supply chain logistics. Consider how critical it is for banks to get a credit or debit card into their customer’s hands to enable them to use their account. Real-time data allows operations teams to quickly spot trends, such as fulfillment delays, and respond proactively.
- Improved Customer Service: Integrating real-time data into bank hosted digital experiences – online and via mobile – can enable customers to self-serve. Real-time data can also improve the Customer Service agent experience by enabling first-contact resolution through the most up-to-date information available.
How can financial institutions ensure client data is effectively protected?
Protecting client data is critically important for financial institutions to maintain trust with their customers and comply with regulatory requirements. There are many steps that banks must take to ensure data security. For example, establishing comprehensive data governance policies that clearly outline the procedures for data collection, storage, access, and sharing. It is also critical to implement robust encryption techniques to protect sensitive data both in transit and at rest. Encryption helps safeguard data from unauthorized access even if the data is intercepted or stolen.
Banks must also maintain a secure network infrastructure with firewalls, intrusion detection and prevention systems (IDPS), and secure access controls. Most banks have implemented multi-factor authentication for user logins to add an extra layer of security. This helps prevent unauthorized access, even if login credentials are compromised. Conducting regular security audits and penetration testing helps banks identify vulnerabilities in their systems and applications so they can address weaknesses promptly. A continuous monitoring and incident response plan is a vital tool for banks to mitigate the impact of a security breach by responding appropriately and promptly.
Many banks work with third parties to augment their software solutions and or to fulfill certain components of the customer experience. When working with vendors, it is important for the bank to conduct a vendor and third-party security assessment to ensure that the vendor also adheres to robust security standards. An effective vendor oversight program includes regular security assessments to verify the vendor’s compliance with data protection requirements.
There are other steps the bank must take to ensure data security such as ensuring secure data disposal, data backups and disaster recovery, and limiting data access to only authorized individuals. As a regulated entity, banks must take special care to stay updated with relevant data protection and privacy regulations, such as GDPR (General Data Protection Regulation), CCPA (California Consumer Privacy Act), or any other applicable laws in the jurisdiction where the financial institution operates. By implementing these measures and continuously monitoring and updating security practices, financial institutions can effectively protect client data and mitigate the risk of data breaches.
In what ways can AI & technology enhance the management of data for financial institutions?
There are many ways that AI and technology can have a positive impact on the management of data. A predominant use case is in the form of data processing and analytics. AI-powered algorithms can process and analyze vast amounts of information much faster and more accurately than humans. This capability allows banks to derive valuable insights from large datasets, identify patterns, and make data-driven decisions. Banks can benefit from this technology by using it to identify and reduce fraudulent transactions, perform more proactive risk management, and gain deeper insights into customer preferences.
AI can also help financial institutions stay compliant with ever-changing regulations by automating compliance monitoring and reporting. By analyzing data and transactions in real time, AI systems can flag potential compliance issues, therefore reducing the risk of penalties and legal consequences. Data Security is another area where AI and technology can be used to identify and respond to potential threats in real time. AI-powered cyber security systems can detect and mitigate security breaches, protecting sensitive customer data.
From an operations perspective, AI can automate manual processes, reducing operational costs and improving efficiency. An important use case for banks in this area is related to credit scoring and underwriting. AI-powered credit scoring models can assess creditworthiness more accurately by considering a broader range of data points beyond traditional credit history. This enables banks to offer loans to a more diverse set of customers and expand financial inclusion.
Why is it important for financial institutions to develop a harmonized data platform?
A harmonized data platform is essential for banks to unlock the full potential of their data assets. It enables better decision-making, improved customer experiences, compliance with regulations, and overall operational efficiency. Investing in such platforms allows banks to better navigate the complexities of the modern financial landscape and drive sustainable growth.
Here are some of the benefits that a harmonized data platform can deliver:
- Seamless integration of disparate data sources; eliminates data silos and ensures that decision makers have access to a comprehensive and consistent set of information
- A single, holistic view of the bank’s customers; consolidating customer information allows for deeper insights, personalized experiences, and targeted marketing campaigns
- Real-time data analysis; enables more informed, data-driven decisions that lead to improved business outcomes
- Enhanced regulatory compliance; manages data in a more consistent and compliant manner by having a unified view of the data
- Streamlined data management and governance processes; reduces operational complexities and ensures the data is accurate, up-to-date, and secure
- Centralized data storage and processing; leads to cost efficiencies and increased scalability
- Simplified data security management; enhances protection against data breaches and unauthorized access to sensitive information
- Innovation and agility; a unified data infrastructure makes it easier to experiment with new technologies, implement AI and machine learning
- Competitive advantage; better adapt to rapidly changing market conditions
How can re-engineering systems improve a financial institution’s management of its data?
Making the investment to re-engineer systems can improve the management of data by modernizing and optimizing data-related processes. The return on investment can be significant. As shared in the question above, there are many benefits to be derived from developing a harmonized data platform. Enabling the seamless integration of disparate data sources, including legacy systems, databases, and external data feeds (e.g., third parties/vendors) is a critical first step to unlocking those benefits. Data integration enables a holistic view of the organization’s data, which is essential for enabling real-time data as well as enhanced analytics and insights.
Re-engineering systems provides an opportunity to implement robust data quality and data cleansing processes, which are foundational to an organization’s successful use of its data. Implementing new processes can ensure the data is accurate, consistent, and free from errors. It enhances the reliability of decision-making and reporting. Modern systems also leverage technologies that allow real-time data processing and analytics. These capabilities can help banks access up-to-date insights, allowing them to respond quickly to market changes, emerging risks, and make data-driven decisions in real time.
Other valuable improvements that can be experienced through re-engineering are:
- Scalability and Flexibility — accommodate growing data needs of the organization without compromising performance
- Automated Workflows — streamline data related processes such as data entry, data validation, and data transformation
- Data Security and Compliance – incorporate modern security protocols to safeguard sensitive data and meet regulatory requirements
- Advanced Analytics and Business Intelligence — enable integration with advanced tools to derive deeper insights from the data
- Cloud Adoption – facilitate the migration of data to a cloud-based platform offering cost-effective scalability and accessibility
- Data Privacy and Consent Management — ensure compliance with data protection regulations
In summary, by adopting modern technologies and best practices, financial institutions can improve data quality, accessibility, security, and analytics, leading to better decision making and customer experiences.