This discovery framework is designed to help facilitate a collaborative conversation regarding Salesforce Shield. By exploring these operational scenarios, marine insurance organizations can accurately assess internal workflows and identify how specific Salesforce Shield capabilities can support their unique compliance, security, and administrative needs, starting with areas of highest impact to practice revenue and client care.
How is the organization currently guaranteeing the immutable history of high-value cargo policy modifications to satisfy international regulatory compliance and avoid strict financial penalties?
Scenario A: Failed International Audit
"We failed a strict international maritime audit because we could not definitively prove who altered the declared freight values on a multi-million dollar policy prior to a major vessel loss."
Scenario B: Manual Forensic Reconstruction
"We keep periodic system backups of all policy alterations, but it takes our IT department weeks of manual database querying to reconstruct a historical timeline when a regulatory body requests proof."
What real-time mechanisms are in place to detect and halt unauthorized mass exports of proprietary client shipping manifests and underwriting criteria by internal users?
Scenario A: Intellectual Property Theft
"We recently discovered that a departing underwriter exported thousands of sensitive client routing schedules to a personal drive, resulting in lost accounts to a direct competitor."
Scenario B: Blind Spots in Access Patterns
"We heavily restrict export permissions based on profiles, but we lack visibility into whether active staff are manually viewing an unusual and unnecessary amount of high-value cargo manifests daily."
How does the organization ensure that highly sensitive financial data and international shipping routes remain encrypted at rest without breaking critical underwriting search workflows?
Scenario A: Functionality Loss Due to Encryption
"We were forced to choose between encrypting our client bank details or maintaining our ability to run essential risk calculation algorithms, as our previous encryption method completely broke system search functions."
Scenario B: Vulnerable Database Layers
"We heavily utilize standard field-level security to hide fields from users, but the raw data for international freight values is still technically unencrypted at the backend database layer."
In the event of a highly contested maritime loss, how do adjusters verify the exact state of a policy record at the precise moment the incident occurred?
Scenario A: Lost Dispute Resolutions
"When a severe cargo loss is disputed in court, we often struggle to prove what the stated liability limits were on the exact day of the vessel sinking because the digital record was modified by another user days later."
Scenario B: Reliance on Manual Notes
"Our adjusters rely on typing out system notes to track chronological policy changes, but these notes are manually entered and highly prone to human error during complex freight disputes."
How are misclassified sensitive details, such as client identification numbers entered into free-text claim description fields, currently identified and remediated?
Scenario A: Hidden Compliance Violations
"Adjusters constantly paste sensitive client bank routing details into the open description text boxes of claims, and we have zero visibility into this data until an external compliance audit flags it."
Scenario B: Unverifiable Data Hygiene
"We rely heavily on mandatory user training to keep sensitive financial data out of unstructured fields, but we lack an automated method to actually verify this compliance across thousands of daily cargo logs."
What level of visibility exists into which internal users are accessing proprietary risk pricing algorithms and vessel rating matrices?
Scenario A: Suspected Insider Activity
"We suspect unauthorized junior staff are viewing our most proprietary hull pricing formulas to bypass standard approval channels, but our basic access logs do not tell us what specific internal records were viewed."
Scenario B: Unmeasured System Querying
"We carefully lock down object permissions, but we are completely unable to track the frequency at which approved underwriters are aggressively querying the master vessel rating database."
How is the retention of complex marine liability policies managed to meet long-tail compliance requirements that far exceed standard data storage limits?
Scenario A: Lost Historical Data
"Because severe environmental liability claims can arise a decade after a spill, our standard data archiving processes result in the permanent deletion of vital historical policy data after just a few years."
Scenario B: Sluggish Offline Archives
"We extract older policy data into a separate offline database server to save primary space, but querying that disconnected database during a sudden compliance audit is slow and cumbersome."
How are slow page load times and sluggish integrations affecting the speed at which brokers can quote and bind international freight policies?
Scenario A: Quoting System Timeouts
"Brokers complain daily that the quoting system frequently times out during peak business hours, and we lack the diagnostic data to identify which specific component is causing the bottleneck."
Scenario B: Anecdotal Troubleshooting
"We know the application feels slow to end users, but we rely entirely on anecdotal broker feedback rather than concrete telemetry to prioritize our IT optimization roadmap."
How is malicious or accidental download activity involving extensive lists of broker commissions and client renewals tracked and neutralized?
Scenario A: Compromised Broker Data
"A compromised user account was successfully used to download our entire internal registry of broker commissions and renewal dates, leading to a massive loss of competitive advantage."
Scenario B: Missing Behavioral Baselines
"We can easily see when a user logs into the system, but we have no automated alerts to notify us if they suddenly export a significantly higher volume of broker data than their normal baseline."
During a suspected insider data leak, how quickly can the organization reconstruct the exact sequence of user clicks, searches, and record views?
Scenario A: Inconclusive Leak Investigations
"When a leak was reported to the board, it took our forensics team weeks to piece together scattered server logs, and we still could not definitively prove what specific keywords the user searched for."
Scenario B: Insufficient Audit Trails
"We use basic login history to investigate suspicious activity, but it completely lacks the depth needed to determine if the user actually clicked into and accessed sensitive cargo manifests."