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: