The part about the in-memory analytics reminds me a lot of the SAP HANA spiel: Transaction Database --> copy --> analytics db = slow In-memory transactions with built-in analytics = fast I totally understand the value of analytics and BI applications, but does it all have to be realtime? And what "mobile analytics" are they going to compute exactly? Forget analytics, I can tell you what mobile users are doing right n…
My bank recently alerted me because I swiped my credit card at one gas station away from home but did not buy gas (the pump was out of gas) and then swiped again at another gas station in a 3mi radius within 30 minutes (obviously since I needed gas).
Their system picked up these two transactions, figured out they were both gas stations, geo-located them to be out of my area, calculated the distance to be close enough to reason it was just one person (and not my wife using her card elsewhere), and triggered an alert because the first transaction was really just a $1 pre-auth with no actual charge.
While none of this is really that complex if you built a fraud-detection system from ground up with these requirements, imagine running this rule on a few hundred million transactions per day. Now add in a thousand more fraud-detection rules, scoring algorithms, and pattern recognition for uncommon usage. Then hook it up to the mobile app to further reduce chances of fraudulent usage by tracking user's location, businesses silently checked-in, and alert preferences. IBM is targeting companies that need this.