Why waste your TPRM technology on poor vendor data

Most TPRM programmes optimise workflows but overlook the quality and structure of the data those workflows depend on. As a result, even well-designed processes struggle to deliver reliable insight. 

The reality: poor data in, poor insights out 

Much of the data used in TPRM today is:

• Secondary or self-reported without validation

• Scraped or inferred from external sources

• Fragmented across multiple systems

• Siloed across teams

This creates a fragmented, disconnected data foundation. 

You end up with:

• Teams working with duplicate records and conflicting vendor profiles

• Gaps in visibility across your vendor base

• Manual workarounds to fill missing information

• Outputs that can’t be fully trusted

No matter how advanced your tools are, poor input data limits what they can deliver.

Why this holds TPRM back 

When data is fragmented, siloed across teams and not validated at source:

• Risk visibility is incomplete

• Prioritisation becomes unreliable

• Reporting lacks confidence

• Automation fails to deliver expected gains

Siloed and disconnected datasets create friction across the vendor lifecycle - from onboarding through to ongoing monitoring.

This is why many transformation programmes struggle to move the needle.

What needs to change 

The shift isn’t about adding more tools.

It’s about improving how vendor data is collected and managed.

That means:

• Primary data collected directly from vendors, not inferred or scraped 

• Validated at source by humans

•  Connected across systems to remove data silos 
  
  

• Standardised across organisations and teams
  

• Maintained as a single, trusted dataset

When data is accurate, complete and consistent, your existing tools begin to work as intended. Workflows become more effective. Insights become more reliable. Decisions become clearer.

Some financial institutions are starting to address this by changing how vendor data is collected, connected and shared. 

What is FSQS? 

FSQS is a community-based supplier assurance model designed to improve how vendor data is collected, validated and shared.  

Financial institutions collaborate to define a single, comprehensive question set aligned to TPRM, cyber, operational resilience and regulatory requirements. 

Vendors submit their information once. Hellios validates, maintains and monitors that data, which is then shared across participating institutions.  

This creates a consistent, reusable dataset that reduces duplication and connects vendor data across teams, systems and across the industry. 

Three ways FSQS improves your data foundation 

1. One standard for vendor data across teams & systems
A single question set removes silos and variation across teams and institutions, creating a consistent dataset that can be used across procurement, risk and cyber functions.

2. Data you don’t have to fix internally
Information is validated by humans and maintained by Hellios, reducing manual effort, removing duplication and improving trust in the data.

3. Data that works beyond onboarding
A maintained, structured dataset supports ongoing monitoring, not just point-in-time assessments, enabling more consistent oversight over time.

What this looks like in practice 

The bottom line 

Advanced TPRM programmes don’t fail because of tools. 

They fail because the data behind them is fragmented, siloed and not intuitive. 

Fix the data, and everything built on top of it improves.