Customers want banking to be fast, simple and affordable, providing seamless secure digital experiences across multiple channels. On the other hand, fraudsters are devising increasingly sophisticated tools and techniques, benefiting from the large quantity of breached identity data flooding the web.
The chosen solution should be able to recognise and respond to a wide range of fraud scenarios and react to unknown and perhaps unexpected fraud cases.
Today customers are becoming more attentive, but many of them sometimes still exhibit risky behaviour: keeping PIN codes in their wallet together with bank cards, leaving e-wallets unlocked on their phones, conducting transactions using public WiFi, etc. Today fraud detection systems should be able to protect customers even when their personal data or access codes are compromised.
So, the protection system should capture the required customer authentication data throughout the customer lifecycle – not just at the moment of payment. The anti-fraud system should provide a universal set of functions for collecting and analysing data. To draw the correct conclusion and identify fraudulent or suspicious behavior, progressive anti-fraud solutions use and evaluate behavioural information. Artificial intelligence is a popular technology, which provides adaptive fraud rules based on an analysis of customer activity data. The majority of fraud attempts can be identified and blocked in real time, while customers are provided a warning the moment a fraudulent action is detected.
This question has to be asked when choosing a fraud prevention system. It should be customisable to your own needs and data. Once a threat is detected an anti-fraud solution can take various actions depending on the company’s path and strategy.
2019 brings changes as the rollout of the Open Banking and PSD2 rules brought data sharing to a whole new level. Also, the Strong Customer Authentication (SCA) mandated by PSD2 add friction to the user experience unless companies choose anti-fraud solutions that can offer risk-based assessments for each transaction and powerful reporting capabilities. Receiving comprehensive reports helps to maintain a complete picture of the situation as a whole and important information about fraudulent activity.
When it comes to technology, anti-fraud solutions use rule-based or machine-learning approaches to data collection. The most advanced use both, as well as unsupervised techniques, with an industry focus and an adaptation to the business’s individual characteristics and requirements. Detect a wider range of fraudulent activity by combining machine learning with an advanced rule engine. This makes fraud detection accuracy very high.
Speed of verification is certainly very important since the faster fraudulent behaviour is identified the less harm is caused to customers.
Increasing fraud detection speed with no loss of quality for customer activities through all channels – this is what software developers should strive for. If not – many of the fraudulent activities might be just missed.
TO SECURE BUSINESSES AND STOP FRAUD BEFORE IT TAKES PLACE, SOLANTEQ OFFERS THE NEWEST STAND-ALONE SOLUTION. SOLAR FRAUD PREVENTION DELIVERS THE LATEST TECHNOLOGIES AND IS DESIGNED TO PROVIDE SOLID PROTECTION FOR ISSUERS, ACQUIRERS AND PROCESSORS.
The deep and accurate analysis gives a complete picture of processed traffic. It also helps to reduce costs by automating operations and improve quality by determining the typical operations from the bank's remote channels and providing recommendations for adjusting the fraud rules setup.
Like other SOLAR products, SOLAR Fraud Prevention is horizontally scalable, which ensures a smooth and redundant operation at all times and provides the flexibility to manage the performance of the solution with an increase in processing volume.