Customer Story

DPD significantly reduces bad debt with real-time credit intelligence

Chapter 1

The Customer

DPD is a global parcel delivery service specialising in domestic and international shipping for businesses and consumers. One of the UK’s leading couriers, DPD delivered 364 million parcels in 2025 and has ranked top of the MoneySavingExpert.com Annual Parcel Delivery Service poll on nine occasions.

With such a large and diverse customer base, DPD requires tight control over credit risk to protect financial performance. 

DPD
Chapter 1

The Challenge

Complexity around assessing customer risk profiles became evident as DPD’s customer base and transaction volumes grew. Their existing process, which had worked efficiently in the past, was no longer sufficient at their scale. Data was becoming disjointed and difficult to manage, leading to the risk of blind spots emerging with the lack of real-time insights. 

The credit risk team had relied on a combination of news coverage and word of mouth to identify customers in distress. However, this made it challenging to keep up with DPD’s growing ledger, meaning opportunities for earlier intervention were sometimes missed. This left the business vulnerable to unexpected defaults.

Pressures on existing workflows continued to build as data sets multiplied, making the process slower and more resource-heavy. This increased exposure to human error in data entry and risk assessment highlighted the need for an automated credit risk process that scaled with DPD’s ongoing growth plans, without requiring additional resources.

To overcome these challenges, DPD needed:

  1. A centralised, ledger-wide view of their entire portfolio

  2. Real-time monitoring to spot risks as they emerge

  3. A way to embed credit data directly into their daily workflows

Chapter 1

The Solution

Creditsafe’s credit data was seamlessly integrated with DPD’s Salesforce database, allowing credit information to sit directly alongside their customer data. The credit risk team can now access up-to-date insights on their customers, such as financial health and director information, without having to switch between systems. 

As part of this, they also started using Company Monitoring, utilising bespoke datasets such as initial stay petition data to automate risk tracking across their entire ledger. DPD are now sent alerts when meaningful changes occur, including (but not limited to):

  • Credit score and limit changes
  • Name or address updates
  • County Court Judgments (CCJs)
  • Notices of Administration, Dissolution or Liquidation

This project presented the opportunity for DPD to clean up their existing data in Salesforce. Creditsafe undertook a large-scale data cleaning project, cleansing 250,000 records and refreshing the data to guarantee accuracy.

Integrated credit data and automated monitoring have given DPD the visibility needed to manage risk proactively, at scale. The results speak for themselves, with a stronger portfolio leading to an impressive reduction in bad debt.


Jordan Davis - Premier Account Manager
Creditsafe
Chapter 1

The Results

  1. Proactive risk management for earlier intervention

DPD can now identify and act early on signs of financial distress, enabling the business to mitigate issues before they escalate. Supported by the expertise of their credit risk team, DPD enjoys a significant year-on-year reduction in bad debt, maintaining levels under 1%. 

  1. Real-time credit decisons

The Salesforce integration is used on a daily basis to monitor the financial health of its customers throughout the entire lifecycle. With real-time data at their fingertips, the team can sanction accounts and adjust credit limits long before a customer defaults. Additionally, credit decisions are based not on the most current financial picture, not outdated records. 

  1. Better portfolio management

Risk management is now streamlined into a more manageable, ledger-style view, allowing the team to apply controls based on specific criteria, such as notice to appoint and key credit limit thresholds.  

  1. Improved data accuracy

The data cleaning project has also delivered major operational benefits. By removing the noise and correcting historical inaccuracies, the team at DPD now has better visibility over their database, allowing them to review any previously missed cases that had fallen through the gaps.  

The general layout and way data is displayed is very user-friendly, and fast responses through the portal make it easy to communicate. It's been great to see them evolve over the years.


Kali Page - Credit Risk Manager
DPD

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