How can we create a data strategy that focuses on the needs of financial service customers?
Vishnu Teja Pallapolu
Building Scalable Solutions in Financial Services | Salesforce Architect | MBA Candidate at USC Marshall
In the past, "data quality" was mainly about ensuring the accuracy of business information. With the increasing complexity of the financial services industry, data quality now encompasses an approach that emphasizes the overall reliability of data. The financial service cloud by Salesforce, tailored for industries like banking, wealth management, and insurance, consolidates data from platforms to provide a customer-centric view. By leveraging data, we can enhance customer engagement through personalized automation driven by AI solutions designed for your sector. This article explores how the financial service cloud accelerates customer onboarding, boosts retention rates, offers insights for planning, and empowers customers to achieve financial success.
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The Role of Data Cloud in Financial Services Cloud
The Data Cloud serves as a platform that integrates all your enterprise data into Salesforce's Einstein Platform, enabling every team to have a view of customers for automation and analytics purposes. We achieve this unified customer perspective by transforming data sources into a reliable, easily accessible, and understandable model.
This involves a variety of datasets, such as telemetry data, online engagement data, and more, from within your organization or external data repositories. This comprehensive perspective supports your sales, customer service, and marketing teams in creating customer experiences, initiating data-driven actions and processes, and effectively implementing AI across all Salesforce applications.
?By utilizing the salesforce data cloud, your organization can consistently deliver customer experiences that lead to increased customer satisfaction, loyalty, and business expansion. Every team member can access the necessary information in real time to meet customer needs, thanks to the Data Cloud.
Salesforce Data Cloud for Financial Services Cloud. Data Cloud consolidates data from Salesforce and other external sources. Visualize insights within Salesforce through FlexCards. Integrate client data—such as interactions, behaviors, and transactions—across systems to create a client profile for financial institutions using salesforce Data Cloud for Financial Services Cloud.
Key strategic considerations
Through salesforce data cloud, teams can streamline data spread across the enterprise into an asset.
The Data Cloud simplifies the use of your data to create automated processes and business workflows. By connecting with Salesforce applications and various common platforms, such as telemetry data or purchase invoicing systems, teams can enable experiences powered by Data Cloud in any work environment.
Is customer data encrypted in Salesforce platform? Absolutely. Customers opt to utilize platform encryption to showcase their security protocols and add a layer of protection against data breaches. The new individual object feature can expedite GDPR compliance efforts.
We have the IndividualObject to connect an individual's preferences to various Salesforce records, such as contact leads, person accounts, and custom object records. An individual's varied roles within an organization are reflected in the IndividualObject.
Use data integration to boost loyalty through personalized services. Merge customer patterns with data for a comprehensive overview. The Salesforce Financial Services Cloud helps customers optimize their planning by providing a view of their financial goals.
Use insights to drive steps that help your customers achieve financial well-being. Combine your customers' financial, transactional, CRM, and behavioral data using Data Cloud to unify internal and external data in a lakehouse with a tailored data model for Financial Services Cloud.
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When it comes to scalability and performance, the Salesforce engineering team recently introduced an orchestration mechanism that dynamically manages workload distribution based on real-time signals. This approach optimizes resource usage. This approach reduces processing times, thereby enabling the handling of large data volumes.
By modernizing native workload management techniques through metadata analysis and leveraging table statistics to assess data volumes, our team has significantly boosted the efficiency and speed of data processing tasks. This strategic approach allows for workload categorization, empowering the platform to handle complex datasets with enhanced agility and accuracy.
To ensure scalability, the platform scales compute resources beyond an AWS account and auto-scales EKS clusters. Load balancing complements these features. We use request routing algorithms to adapt to the changing needs of Data Cloud Everywhere.
Real-World Applications Examples:
OTTB functionality limits user access to Residential Loan Application records and other mortgage objects, even if they’re members of an account team, using the Override Mortgage Custom Sharing with Standard Salesforce Sharing setting.
To keep Salesforce calendars and availability up to date, sales reps can use Einstein Activity Capture for Financial Services Cloud to sync events not organized by Salesforce users. Previously, Salesforce and connected accounts only synchronized events organized by Salesforce users.
Empower service agents with a comprehensive view of transaction details. When your agents process a dispute request, they can now see transactions enriched with important merchant-related details, such as merchant name, logo, and URL. Your agents can use these details to help your customers recognize their transactions more easily. Exclude recognized transactions from additional dispute investigations to reduce operational costs and enhance customer satisfaction.
Using intuitive intake forms, your service agents can efficiently collect data for various service requests. Each process features an OmniScript for request intake, available for both assisted and self-service channels. With a low-code approach, you can easily customize OmniScript to meet your specific business needs.
You can deploy the following service processes:
FSC seamlessly connects transactional and CRM data by supporting solutions ranging from off-the-shelf integrations to customized developments. These features ensure that customer data can be viewed and managed across platforms.
Conclusion
Assess your organization's existing data challenges. Consider how you can integrate data sources effectively.Discover ways to personalize experiences for your customers, as well as your marketing, sales, and service teams.
Personalizing interactions can provide insights from your data to enhance customer experiences on a larger scale. By assisting customers in achieving goals, you can boost loyalty. Drive tangible business benefits.
Financial organizations have the opportunity to combine their customers' financial information with CRM data. This allows them to leverage AI-driven insights, such as time-based financial well-being assessments and tailored financial service offerings.