STOP FRAUD by tracking your Customer behaviour to
Spot Out-of-character Financial Transactions

As digital channels have multiplied, so have the routes that fraudsters can use. And their options are about to expand again with the implementation of Open Banking and the coming into effect of Payment Services Directive (PSD2). Fraudsters are devising new ways to exploit loopholes in technology systems and processes.

In case of frauds involving lower amounts, they employ hostile software programs or malware attacks, phishing, SMSishing and whaling (phishing targeting high net worth individuals) apart from stealing confidential data.

Around 65% of the total fraud cases reported by banks were technology-related frauds (covering frauds committed through/ at an internet banking channel, ATMs and other payment channels like credit/debit/prepaid cards), whereas advance-related fraud accounted for a major proportion (64%) of the total amount involved in fraud. With traditional methods and rule-based solutions in the market, too many hits are generated, and fraud detection is reactive. What is needed is a proactive solution that efficiently manages fraud and unlocks new fraud types.


We are different:
We don’t stop fraud by focusing on the fraudsters. We stop it by getting to know the habits and behaviour’s of banks’ customers and staff so we can spot out-of-character financial transactions. While fraudsters constantly change their behaviour to avoid detection, real customers form habits.

By learning these habits and building up customer and staff profiles we can accurately spot suspicious activity and stop it – before any money has left the bank.

Leveraging on smarter AI, BANKiQ IFRM detects fraud with fewer false positives. Using pre-defined AI risk models, banks can tackle digital banking fraud challenges related to eBanking/mBanking sessions redirected by malwares, hijacked by hackers, taken over by identity theft and others.

Use Cases

Redirected e-Banking sessions due to Malware
Hijacked e-Banking sessions
SIM swaps
Identity theft from phishing
Fake Mobile Banking Apps