Housing fraud is a persistent problem in larger cities, where the demand for social housing far exceeds the supply. In 2018, we conducted an in-depth investigation into housing fraud in Amsterdam, revealing that the issue was more widespread than initially thought. This example shows that data science provides many insights, but significant measures are needed to achieve real improvements.
Research on Housing Fraud
An Amsterdam housing corporation suspected housing fraud but could not identify specific cases. Over several months, we gathered data from various rental websites and discovered that housing fraud was indeed occurring. However, our findings met with resistance; housing corporations were reluctant to invest time and money into the issue. Eventually, our analyses were verified by the Financial Times, which published a major article on the matter, leading to a roundtable session in the Dutch Parliament a month later.
How Can You Determine the Risk of Housing Fraud?
The extent of housing fraud is difficult to determine without very detailed information. During our research, we identified several “system failures” that make illegal subletting highly attractive:
- Ease: Offering homes for rent through websites is straightforward.
- Profit Potential: Comparing the rent of a social housing unit with the market rental price can show a difference of €700 to €1000 per month.
- Chance of Getting Caught: Reports from corporations indicate a low likelihood of being caught.
- Consequences: If caught, earned profits usually do not need to be repaid.
These “system failures” are politically inconvenient. High potential profits without significant consequences in social housing are not something you want to publicize.
Major Benefits of Tackling Housing Fraud
In a 2018 news article, housing corporation directors estimated that 10% of their properties could be affected by fraud. This seems like a very high percentage. If only 2.5% of social housing capacity is occupied by ineligible tenants, this still involves 60,000 homes in the Netherlands. Given the enormous waiting lists for social housing, this issue should be taken seriously.
Practical Dilemmas Hindering Solutions
During the investigation, numerous legal and practical dilemmas surrounding housing fraud emerged. What exactly constitutes housing fraud? Are you allowed to keep your social housing if you go on a world trip? How long can you spend winters abroad without losing your social housing? Can you keep your social rental if you move in with a partner but are unsure about the relationship?
Many of these issues are not clearly defined in rental contracts or the law. If tenants contest accusations, cases end up in court, where judges evaluate on a case-by-case basis whether the home should be returned to the housing corporation. Proving fraud is complex, and privacy laws hinder information sharing with municipalities, the tax office, and welfare agencies. Additionally, legal proceedings are time-consuming and costly, and court rulings can sometimes be frustrating for housing corporation enforcers. If tenants do not contest, they simply return the keys while keeping their illicit profits, as recovering illegal earnings is legally complex and time-consuming.
Many housing corporation employees find it uncomfortable to address this issue. They serve a socio-economically disadvantaged target group and dislike placing them under suspicion. Board members and affiliated organizations in the social sector are not eager to uncover insights that could damage the sector’s image or cause unrest.
Translating Data Science into Organizational Practice
Facts are friendly, some say, meaning that insights offer opportunities for improvement. While this is true, insights are not friendly if you are unwilling or unable to address underlying problems. In that case, it is easier to ignore the facts.
Data science is crucial in organizations to gain deeper insights into issues. Good analyses can pinpoint problem areas down to the smallest detail. These bottlenecks are often recognized by practitioners who have long sought attention for the same issues. However, data science can conflict with maintaining a positive image, clinging to pet projects, or avoiding uncomfortable truths.
Of course, housing fraud is a highly complex societal problem with many facets. But most organizations face similar issues that need to be addressed but are often overlooked. When data scientists do their jobs well, these problems come to light.
See this as an opportunity and engage in the conversation. It fosters a culture of dialogue, knowledge sharing, and collaboration, enabling you to serve your (potential) customers better. By acknowledging and addressing these problems, your organization can operate more efficiently and effectively while taking a leading role in innovation and customer orientation. Embrace the insights, make the necessary changes, and watch your organization thrive.