The Union Bank of India had reported a case of cyber attack on one of its nostro accounts last year on the 21st of July. At that point , the amount remained undisclosed and the breach was said to have happened from an email attachment opened by one of its employees.It was a phishing attack. An email with the handle @rbi.org.in had an attachment -a zip file with a .xer file.While one employee fell pray, some were smart to report it as suspicious. However, it was too late.The malware had entered the bank.
A sum of $171 million had been debited from its nostro account with Citibank New York .Since Swift recon happens only the next day once the nostro statement comes in , the bank’s treasury department realised only the next day.
The money by then had been moved to accounts in two banks in Cambodia—the Canadia Bank Plc and RHB IndoChina Bank Ltd, besides the Siam Commercial Bank in Thailand, Bank Sinopac in Taiwan, and a bank in Australia. These funds were routed by Citibank New York and JP Morgan Chase New York, which hold UBI’s foreign exchange accounts.
SWIFT maintains a neutral stand in the investigation primarily initiated by UBI and insists no breach at its end.However , it is high time that SWIFT looks at its loopholes -recon delays , lack of built in fraud early warning mechanism and an AI poweredneural network enabled clustering system that can track such suspicious activity.
With blockchain heralding a new age of cryptographic security and unit level transparency the bank’s must also look for alternatives to the wire transfer monopoly and it’s inherent loopholes.
The futurists of the world are besotted by the science that simulates the engagement , decision and the discovery process of the human brain -in other words Artificial Intelligence(AI) or Cognitive Sciences. Cognitive systems quickly identify patterns similar to a way our brain identifies situations and responds to it. Within AI , there are a number of different technologies and they lie at different points in the curve of adoption with virtual assistants and robo-advisors riding the crest of adoption. This post talks about the merits of the lesser known yet immensely intriguing Semantic Technology .
Semantic Technology , as Forrester predicts is still a good 5 to 10 years away from mainstream adoption but some companies such as the Vienna based Cortical IO and Cambridge Semantics are few of those who are braving the first wave.
Semantic Maps – Vocabulary Building Tools
Semantic Maps or Networks have been around for more than a decade where words are understood under the context they are used , very similar to how the human brain understands and processes words, phrases or a language. This technique is used as a teaching method for children learning a language and has been seen as a very powerful vocabulary building tool.
The same terminology takes on a far more complex computing context .Semantic Mapping can be used for dimensionality reduction of a set of multi-dimensional vectors to retain main data characteristics. The original properties are clustered to generate an extracted feature. This technology has typically been explored for text mining and information retrieval.
Semantic fingerprinting is a new method whose manner of processing text is modeled on that of the human neocortex . Semantic fingerprinting has the potential to be more powerful in document comparisons than are word list-based analyses. The leading proponent of semantic fingerprinting is Cortical (www.cortical.io).This technique to identify similarities , identify context and also arrive conclusions.
Since semantics are heavily dependent on context , the fingerprint for ‘Apple’ would have strong connections with the computer brand. Words, Sentences and whole texts amounting to terabytes can be compared against each other.
Big Data + Semantics = Endless Possibilities
Big Data Semantics is where the technology is applied to reduce the stream of unstructured data to understand , predict , categorize or sort just as much as one would with any form of data once reduced to an understandable , identifiable form.
The system ingests data in any unstructured form – emails , faxes , documents , sms , social media or data from internal systems and then runs it through a semantic engine. The semantic engine generates smart binary vectors with minimal memory footprint represented in boolean. This helps to compare aggregated or atomic representations of words .
Some ways in which it is being leveraged are seen in the table below
With the rise of AI startups receiving funding across the globe , disruptive technology and their use cases are only to rise . We can only wait to watch the treasures it unlocks.
If you have an interesting use case you would like to share , please leave a comment or get in touch with us,
In a country of 1.32 billion people where 48.26 million are unemployed , any kind of automation till recently , was unwelcome .With the government , taking a strong stance on digital technologies , a floodgate of investments seem to have opened up. AI is the latest muse for investors , large corporates and fintechs alike. A few weeks ago a list of the top 100 AI Startups was compiled and published by the very credible CB Insights and to our utmost dismay , not a single Indian startup figured in the list.
In a very recent research by Quartz , the talent crunch in India’s AI circuit was revealed as extreme. Only 4% of the talent pool has actually worked on deep learning or neural networks. Belong Research quotes that only 17 % of AI talent works around Financial Services and the demand to supply ratio for AI talent has a severe shortfall as seen below.
This week spelled some good news for a lot of companies toying with a roadmap around AI , startups as well as the developer community as two very big corporates announced investments to boost AI in India.
Intel announced heavy investment to groom local AI talent and Intel South Asia Managing Director Praksh Mallya said “Our developer education program will educate 15,000 scientists, developers, analysts and engineers on AI technologies, including Deep Learning and Machine Learning in India.Our collaboration with the industry and the academia will help democratize AI, by reducing entry barriers for developers, data scientists and students,”
Through 60 programs in a year, the initiatives will empower the community with the know-how for AI adoption with ready-to-deploy platforms and tools for solution development. “As India undergoes digital transformation, the data centre and the intelligence behind the data collected will enable the government and industry to make quick decisions based on algorithms,” said Mallya on the margins of Intel’s ‘AI Day 2017′. The company’s Indian subsidiary is collaborating with Hewlett Packard Enterprise, Wipro, Julia Computing and Calligo Technologies for using AI in the country.
Ernst and Young announced its plans to enhance its suite of automation and artificial intelligence offerings with the opening of its first Artificial Intelligence (AI) Center in India. Artificial intelligence is already being deployed across industries such as automotive, telecom and technology . EY’s AI Center will bring together teams of multi-disciplinary practitioners, combining expertise in AI, Robotics etc. along with domain experience in sectors.
“The launch of the AI Center,aims to lead the next step of this transformation journey by helping enterprises combine AI’s autonomous reasoning with systemized learning opportunities.” said Milan Sheth, Partner – Advisory Services and Technology Sector Leader, EY India.
Intel’s developer education program will educate 15,000 scientists, developers, analysts and engineers on AI technologies, including Deep Learning and Machine Learning in India.