As we become more and more interconnected, we are able to access more products and services with greater ease and carry out many tasks from a mobile device in a matter of seconds. There is no question that technology has made a lot of people’s daily lives much easier. But concerns about security have also increased, in almost direct proportion to the growth in the incidence of on-line fraud.
In the fintech sector, it is new financial technologies that have most benefitted from advances in on-line security: they not only reduce the vast losses suffered every year in the banking sector, but also provide their clients with the security and confidence they need to be able to continue using that channel.
As a result, the financial sector is continually seeking new technology advances in order to prevent and detect digital identity fraud. One of the technologies gaining the greatest momentum in 2017 is social network analysis for detecting, among other things, identity theft and impersonation.
Although many people and companies still see social networks as a means of entertainment or superficial communication, it was discovered some time ago that they are a potential source for compiling information and carrying out a predictive analysis of a person’s digital identity. In addition, new technology advances now make it possible to take advantage of information on the Internet with even greater efficiency.
SNA (Social Network Analysis) makes it possible, for example, to detect fraudulent connections, unreliable data patterns or irregular activities. The latest applications also make it possible to identify a trust level for a given user, that is, how likely they are to repay a loan or if they are who they say they are, based on a holistic approach to the individual’s data on the Internet.
Put simply, the new on-line verification procedures incorporate a process that validates the email provided by the individual for an onboarding process or other transactions. Based on this email, information is tracked on associated social media and evidence is collected by means of an algorithm in order to provide more reliable validation, including a fraud score.
This new functionality, together with those already implemented such as testing of document security measures, liveness testing, and biometric facial recognition, make it increasingly difficult for scammers to steal identities, while ensuring security levels that benefit both companies and users.