This discovery framework is designed to help facilitate a collaborative conversation regarding Salesforce Shield. By exploring these operational scenarios, Insurtech Startups can accurately assess internal workflows and identify how specific Salesforce Shield capabilities can support their unique security, compliance, and administrative needs, starting with areas of highest impact to operational scalability and data protection.
How does the executive team ensure that rapid geographical expansion and new market entries do not expose the business to catastrophic regulatory fines regarding policyholder data?
Scenario A: Stalled Market Expansion
"Every time we try to launch into a new state, our legal counsel halts the rollout because we cannot guarantee that our underlying database architecture complies with localized privacy mandates."
Scenario B: Reactive Risk Assessment
"We rely on quarterly manual audits to check if sensitive client data is exposed. It keeps us somewhat safe but creates massive anxiety whenever we scale up our broker network."
What visibility does leadership have into potential data leaks involving proprietary underwriting algorithms and customer financials before they impact market valuation and investor confidence?
Scenario A: Blind Spots in Data Movement
"We had a situation where an outgoing executive exported thousands of proprietary risk models and client lists to a personal drive. We only found out after they joined a competitor."
Scenario B: Delayed Incident Reporting
"Our IT team can eventually figure out who downloaded what, but it takes them weeks to comb through server logs, leaving the leadership team in the dark during critical investor meetings."
How is the security team identifying abnormal user behavior, such as unauthorized internal views of high-profile customer policies?
Scenario A: Undetected Insider Threats
"We have zero visibility if a claims adjuster decides to look up the life insurance details of a celebrity or a local politician. If a leak happens, we have no way to trace the source."
Scenario B: Noisy Log Environments
"We get login histories, but it doesn't tell us what the user actually did during their session. It is just a sea of IP addresses with no context regarding which policies were accessed."
In the event of a state insurance commission audit, how quickly can the compliance team produce historical records of changes made to premium calculations or policy status?
Scenario A: Failed State Audits
"We were recently penalized because we could not provide a five-year history of a commercial policy's rate changes. Our current system purged the data after eighteen months."
Scenario B: Manual Backup Extraction
"We technically have the data on cold storage backups, but asking IT to unearth who changed a deductible three years ago takes weeks of back-and-forth."
How is the engineering team securing sensitive policyholder information at rest without breaking core platform functionality like global search and automated workflow rules?
Scenario A: Broken System Workflows
"We tried implementing classic encryption on Social Security Numbers, but it immediately broke our automated underwriting routing rules and prevented our brokers from searching for existing clients."
Scenario B: UI-Only Obfuscation
"We use field-level security to hide sensitive banking details from standard users on the screen. However, we know the data still sits in plain text on the backend servers."
With numerous third-party integrations feeding data into the underwriting engine, how is API consumption tracked to prevent unauthorized data extraction via compromised credentials?
Scenario A: Silent API Scraping
"A vendor's integration key was compromised, and someone quietly siphoned off 50,000 policyholder records over a weekend. We had no alarms in place to catch the unusual traffic volume."
Scenario B: Hitting Unexplained Limits
"Our integrations frequently hit API limits, but we spend hours trying to figure out which connected app is causing the spike. It disrupts our real-time quoting engine."
When policy terms or risk scores are adjusted, how is the specific timeline and attribution of those changes retained for post-claim dispute resolution?
Scenario A: Unresolvable Claim Disputes
"A client filed a massive claim, arguing their coverage limit was higher than what is currently in the system. Because the change happened two years ago, the history was deleted, and we had to settle out of court."
Scenario B: Overcrowded History Related Lists
"We track history, but the standard view limits us. We cannot easily filter or query the massive volume of minor updates to find the specific underwriting change we actually care about."
How is customer personally identifiable information handled to meet strict data residency and localized privacy regulations during cloud processing?
Scenario A: Regulatory Non-Compliance
"We are failing our privacy audits because we cannot mathematically prove to European regulators that EU citizen health data is encrypted using keys that our company controls."
Scenario B: Incomplete Encryption Strategy
"We secure the actual database fields, but we recently realized that user uploaded files like driver licenses and medical forms are still sitting unencrypted in our file storage."
During a suspected security incident, what is the forensic process to determine exactly which records a compromised user viewed or downloaded?
Scenario A: Forced Full Disclosures
"A broker's account was compromised. Because we couldn't pinpoint exactly which accounts they accessed, legal forced us to issue a breach notification to our entire customer base."
Scenario B: Slow Investigation Times
"We eventually find the answers during an investigation, but mapping generic login timestamps to user activities takes days of manual correlation by my engineers."
How does the organization maintain absolute control over encryption keys, particularly regarding the ability to instantly destroy keys and revoke access to encrypted data?
Scenario A: Vendor Lock-In on Key Management
"Our internal infosec policy strictly dictates that no SaaS vendor can solely hold the encryption keys for our financial databases, which prevents us from moving sensitive workloads to the cloud."
Scenario B: Cumbersome Key Rotation
"We manage our own keys, but rotating them annually requires scheduling significant system downtime to re-encrypt data, which frustrates the business side."