The network effect: harness the power of data

Have you ever signed up for an online service and felt like you were bombarded with service terms and conditions asking you to agree to share your personal data? It may seem invasive, but when it comes to the network effect, the general purpose is to harness the power of data to vastly improve the user experience companies can provide to their customers. Put simply, with too few users, a service may not be up to par with market competitors. But by increasing the no. of users, a service can grow and be greatly improved. But how is the service improved when it comes to fraud prevention? Thanks to open banking principles, the possibility to use data has a huge impact on how much more secure a service can become. Let’s see how the network effect can allow you to truly harness the power of data.

In the simplest terms, the network effect is where a product or service becomes more valuable as more people use it, therefore becoming more useful to each company and every individual user. The best example of the network effect is in the value of the internet itself, with a huge online catalogue of services and sites to enrich the overall experience. Social networking is perhaps the best example of a site, or more specifically a communication service, that can be greatly affected by the network effect. With more users, social networking sites increase in size and popularity, leading to an increase in the services they provide. As more people join the network, there are more people to connect with and more content to consume (a timeline consisting of 5 followed pages or friends is far less exciting than following or connecting with 50 or more). This can create a self-reinforcing cycle where the more people use a product or service, the more valuable it becomes, leading even more people to use it.

Apply the network effect to fraud prevention, and the value to customers is the improvement in service through enhanced fraud prevention capabilities. The result is a safer and more secure online payments and transactions environment, leading to happy customers, a positive online reputation, and potential for financial growth through an increase in users. Put simply, the more users who agree to share their data, the more efficient fraud-prevention models become.

Think of all of the world’s internet users - there are so many people out there with their own digital identities, combining hundreds of offline and online data elements. These data elements are used to indicate a set of behaviours, device setups, physical location and much more, quite unique to individuals, but also matching the behavioural profiles of types of users. A regular user will simply log on to a service using their computer or mobile device, with no attempts made to change device or location setups. Of course, when regular service customers use the internet, all of the aforementioned data can paint a picture of what a ‘norm’ may be - any deviation can be suspicious and indicative of fraud.

Not all behaviours flagged as suspicious are necessarily an attempt at fraud. For example, someone using a VPN or proxy service to mask their IP address due to privacy concerns is not bad behaviour - but couple this behaviour with other attempts to conceal a user’s true location, device setup, or deviation from regular browsing behaviour, and there may be enough to back-up initial suspicions. But all of these analyses can only become more effective and accurate in detecting fraudulent activities when the size of the dataset is more extensive and continues to grow. More on that later.

Although in the case of fraud prevention, the network effect can be a positive force, in other industries, there can be disadvantages as it can create a barrier to entry for competitors. Once a product or service has a large network of users, it can be difficult for new competitors to offer a competing product or service that is as valuable to users (again, think of major social networks).

This can lead to a lack of competition and innovation in the market as one company can effectively have a ‘network monopoly.’ This can be harmful to consumers, as the dominant company may have little incentive to improve its product or service or keep prices low. Unfortunately, major social network scandals have shown that vast databases of data can also be collected for the purposes of advertising products based on personal preferences, or worse, compromised and leaked by cybercriminals.

Privacy concerns have had a significant impact on the network effect, as more and more people are becoming aware of the importance of protecting their personal information online. This has led to an increasing number of people being wary of sharing their information with online services. This in turn has made it harder for those services to attract a critical mass of users and achieve a strong network effect.

Every industry is different, each taking a different approach to how user data is used, but with major services (mainly social networks) having experienced scandals in handling user data, and unscrupulous marketing companies harvesting data for financial gain, wider public distrust certainly has an impact on the effectiveness of the network effect. For those concerned about how companies such as Nethone use data to improve their service, such fears can be easily put to bed.

To give European Union (EU) citizens control over their own data, and have a say in how it can be used, the EU introduced the General Data Protection Regulation (GDPR) in 2016, which is the world’s toughest privacy and security law. GDPR imposes obligations not only onto organizations within the EU but anywhere in the world, so long as they target or collect data related to people in the EU.

It must be stressed that sharing data is always optional, even with a data-driven company like Nethone, in order to give businesses a choice, and control over their own, and their customers’ data. Building confidence in how companies can harness the power of data to the benefit of customers is therefore a crucial step forward - education, as always, is key.

Companies that offer advanced fraud solutions will use machine learning models that are continually evolving to fraud scenarios. Data is crucial in its evolution. As important as harnessing the power of data is, human input is also a factor in the effectiveness of fraud prevention, with darknet investigations carried out by fraud intelligence specialists also incorporated into fraud-fighting machine learning models.

The key takeaway is that every measure is taken to improve service - even if additional data sharing has not been granted by companies, this does not mean their service will be negatively impacted. What is certainly true is that the more data companies such as Nethone can use, the effectiveness and value of fraud-fighting capabilities increase immensely. Such capabilities are possible, and most importantly, they are GDPR compliant. It is therefore possible to harness the power of data and make sure the advantages of the network effect can be felt by all. And all while ensuring the customers understand that their private data is protected in the process.

If you wish to learn more about the network effect and how Nethone’s advanced fraud solution can help your company harness the power of data, let’s talk.