The banking and finance sector can learn from the online dating industry, particularly in using graph databases to model social relationships and detect fraud. Graph databases are better at identifying connections between multiple data points than relational databases, making them ideal for analyzing complex data such as those involved in financial transactions. By applying social network analysis, financial institutions can identify potential fraud rings and flag advanced scenarios in real-time, saving time and money while offering a competitive advantage. The same graph database technology used to find matches on dating sites can also be applied to other business applications, such as recommendation engines and customer relationship management tools, providing a unique ability to discover new patterns within complex data volumes.