How Big Data and Analytics Can Improve Bank Fraud Detection
Interaction with Big Data has become a part of our everyday life long time ago. We are regularly confronted with the collection of all available information. This is a common practice of many structures, including banks. Your bankcard knows everything about you: what kind of food you prefer, what magazines do you like to read, what are you buying in online stores and so on. But this information can be used not only for ruining your privacy but also for useful purposes, including IT security.
Judging by the number of cyber attacks in 2016, banks need to have a universal method of protection. At the moment, a whole division working on the study of actual problem was established. It is not a secret that, according to the credit cards accounts, data scientists determine the user’s ability to dispose his/her money at all. Now we need to find out the way how to determine the feasibility of users’ actions and data acquisition.
Stated another way, bank’s customers often sue bank application installed on their smartphones. The sensor? like Google does, indicates user’s location from where he/she uses the app. If the system receives a request to use an account from another gadget, or any other locality, it can be recognized as a fraudulent one. If somebody is trying to access your Gmail account that is obviously carried out from another device, you receive a message on a connected phone number about probability of hacking. However, when it comes to bank accounts and money application security works more closely and carefully.
The modern system of protection against bank fraudulent actions can recognize a “handwriting” to find criminals. If there is a gang or already known by its crook thief the collected information allows bank to track it and suggests certain system helping thieves to choose their victims.
For another thing, banking services that interact with insurance companies can use the data to analyze possible fraudulent schemes for insurance premiums payment. A similar system is applied to the issuance of loans: bank’s financial protection automatically increases the interest rate on loans for those who spend large sums on well-known brands, or, on the contrary, unnecessary things.
To summarize it all, the age of technology proves data confidentiality to be a misguiding thinking. What we can do is to make this data available for processing and many banks offer their customers total data protection programs, and those who refuse from it in the name of “privacy of information” make a mistake. A disadvantage of any cyberattack is that it schemes everything that should be tracked. Giving permission to monitor, collecting and returning your data as a segment of Big Data, you destroy your privacy’s little hut, but by putting it in a common warehouse instead, it is preserved by means of far more reliable mechanism.