1 / 10

Case Study: Apama helps Estonian bank to detect Fraud

Case Study: Apama helps Estonian bank to detect Fraud. Moscow, 11.11.2010 Kristi Pool, Helmes. Helmes – the expert of e-services. internet banking solutions self-care environments mobile banking solutions etc. 97%. of all transactions in Estonia are made in electronic channels.

toril
Download Presentation

Case Study: Apama helps Estonian bank to detect Fraud

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Case Study: Apama helps Estonian bank to detect Fraud Moscow, 11.11.2010 Kristi Pool, Helmes

  2. Helmes – the expert of e-services • internet banking solutions • self-care environments • mobile banking solutions • etc. 97% of all transactions in Estonia are made in electronic channels

  3. SEB – Estonian 2nd largest bank • universal bank for private and business clients • more than 820 000 clients • more than 500 000 cards • ¾ of clients use regularly internet bank

  4. SEB facing challenge – detecting FRAUD • It took 4-5 hours to detect whether activity had fraudulent nature • Business rules were difficult to modify • Performance of the system was an issue

  5. Cyber crime and fraud –rising global challenges • fraud in payments • cards fraud • money laundry • security of internet banking • etc. 50% yearly growth in cyber crime

  6. The tool SEB needed in war against fraud Set and change the business rules to detect the fraudulent event patterns Alert and act based on detected patterns NOW Monitor events in REAL TIME

  7. Apama helps to react on time Apama Event Streams detect patterns in real time Traditional Processing analyzes past events Monitor events in REAL TIME Monitor events “If a credit card was used in Tallinn and then after 5 minutes in Moscow, block the card and send an alert” “How much fraud was happening 5 hours ago?”

  8. Various events are monitored in real time • Analysis of transactions coming in • Debit Card vs Credit Card • Swipe of Magnet or Pin via Chip • ATM or at a counter • Internet payments “Our previous system had performance problems and any change in business rules was a headache” Rein Rüüsak (SEB)

  9. Set the rules and act automatically on alerts • Formulate alert rules • Based on value thresholds (for example amount, or nr of transactions) • Based on temporal constraints (example nr. of transactionswithin a time period) • Based on location of ATM or IP address of PC etc • Act on alerts • Informing account owner • Blocking account

  10. Thank you! Kristi Pool Head of Progress Solutions Kristi.Pool@helmes.ee

More Related