Assessing the Impact of the new Financial Service Cloud (FSC) Data Model
In an era of costly deposits and interest margin compression, financial institutions (FIs) can still flourish by increasing efficiencies.
The New FSC data model is a game changer for banks, credit unions, and insurance companies looking to leverage AI tools like Agentforce, Einstein, and Data Cloud. But it’s easy to get overwhelmed by the chaos of artificial intelligence through the lens of data compliance.
There is a lot to consider. Regardless of your starting point, you’ll have to organize customer data and implement a robust data governance plan. In partnership with your data readiness plan, your team will also consider the cost of delay and what it means for your institution not to consider these types of opportunities.
The New FSC data model is a game changer for banks, credit unions, and insurance companies looking to leverage AI tools like Agentforce, Einstein, and Data Cloud. But it’s easy to get overwhelmed by the chaos of artificial intelligence through the lens of data compliance.
There is a lot to consider. Regardless of your starting point, you’ll have to organize customer data and implement a robust data governance plan. In partnership with your data readiness plan, your team will also consider the cost of delay and what it means for your institution not to consider these types of opportunities.
For current Salesforce customers:
- What’s the cost of delay?
- Am I building more technical debt?
- How long will the old model be supported?
- Can I leverage new AI features if I don’t migrate?
If you’re new to Salesforce FSC:
- Is it time for a data transformation?
- Can you take advantage of stop gaps?
- Do we start cleaning the process using the new FSC data model?
- Will this help reconcile disparate technology?
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