The use of mobile payments is expanding rapidly and this is set to cause major disruption to the Banking industry. N2 is helping a fast growing mobile commerce company design and develop a massively scalable ledger system that facilitates mobile payments, purchases, rewards and value transfer for mobile users.

The real time system integrates the analysis of transaction flow and value tracking from a growing list of payment services and integrations involving JPMorgan Chase,Dwolla, Admeris, eCheck, BAMS, Giftango, Google Wallet, Bitcoin, Connected Car, Clover and more.

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Cybercrime costs $118 billion annually and takes an average of 18 days to resolve at a cost of nearly $416,000 over those 18 days—and those figures are expected to grow as cyber attacks continue to increase.

The N2 team recently transformed the operations of a national cybersecurity integration and operations center by dramatically reducing the time for analysts to detect and respond to cyber-attacks. Prior to the engagement, intelligence analysts were using a plethora of tools and manual processes to query and sift through very large, disjointed sets of data representing IDS events, Netflow records, Passive DNS, WHOIS, Threat Feeds, etc. Analysts were spending most of their time writing low level database queries and scripts to generate even more disjointed data sets. There was no concept of a common reference model or workflow to manage the design, testing and execution of queries and scripts. Neither the queries nor the results could be easily shared with other analyst or decision makers. Queries were taking very long to return results and sometimes never. Analysts were simply spending too much time working around system constraints and not enough time applying their domain skills to identify and respond to attacks. The N2 team was brought in to engineer an innovative solution. After interviews with analysts and studying day to day workflows, the need for an analytic framework was established. The goals were simple:

     • Enable sharing and re-use of algorithms
     • Shield analysts from unnecessary data complexity
     • Increase the Performance and Execution Scale
     • Facilitate design/scripting of complex algorithmic steps

The N2 Team implemented an analytic framework which enables analysts to easily develop and test a sequence of complex algorithmic steps that can be saved and shared as a simple “Analytic”. The Analytic Framework manages creation, orchestration and parallel execution of Analytic jobs using best of breed distributed processing systems (e.g. Hadoop / YARN). An Analytic Catalog was established by porting and developing over 50 Analytic(s) using the framework. Examples include Beaconing, Exfiltration, and Domain Generation Algorithm (DGA) detection. Many of the Analytic(s) were simply not possible using the legacy systems and tools. The Analytic Framework allows output from Analytic(s) to be chained to the input of other Analytic(s) to perform further analysis or enrichment (e.g. WHOIS or Geo-IP include darknet markets urls).

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A major Hedge Fund engaged the N2 team to design a system to detect (in real-time) Unscheduled news events (e.g. acquisition announcements, geopolitical turmoil, management changes, factory explosions etc.) reported through both social media and mainstream media.

The solution ingested real time feeds from sources such as Twitter, TV captions, Thomson Reuters, Dow Jones, Associated Press etc... Ingesting billions of news items daily, the data was organized into shards of highly specialized (All-in-Memory) semantic indexes running in a massive array of distributed computers. With nearly 20 years of news from hundreds of sources all in memory, as real-time news was streaming, temporal (semantic) patterns were correlated and analyzed against 10's of thousands of trading instruments in real time to identify statistical patterns and trends. Statistical signals and correlations with market trading volatility were generated within milliseconds of events occurring and Algorithmic Trading strategies were developed to identify trading entry and exit points. The N2 team has been a leading pioneer in social media news and market data analytics. Exploration and innovation in this area will continue as trading firms explore new ways of generating alpha.

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In the advertising world Real-time bidding (RTB) refers to the means by which ad inventory is bought and sold on a per-impression basis, via programmatic instantaneous auction, similar to financial markets.

The N2 team worked with a major Digital Media company, specializing in next generation Search Engine Marketing (SEM) services, to deliver more relevant search ads that factor in the flow and analysis of real-time current and future events, sentiment, and other factors that affect the pricing of ads and how campaigns are delivered. Often times, companies are slow to adapt advertising campaigns because they don't have real-time visibility into news and events that are impacting buying decisions. The N2 team provided a real time intelligence platform - capable of monitoring and analyzing mainstream media, television and social media to improve results.

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