A quick preview of developments in Analytics and AI space in India in 2017
- Amazon Web Services adds AI to cloud by adding services such as image analysis, visual search, speech recognition among others
- Google is upping its stake in India big time on AI and ML with Cloud India Region by announcing setting up its first cloud region in Mumbai within this year.
- Indian cops plan on using big data to prevent crimes
- With an aim to monetize the available data Indian Railways embrace data analytics
- NASSCOM announced that India has formed a policy group to study the new technologies of AI and also recommend a framework for its adoption.
- Indian Prime Minister Mr. Modi asks tax officials to use data analytics to track undeclared wealth.
Key statistics to watch for in 2018 & years beyond
- 75% of developers will include AI functionality in one or more business applications or services by 2018 — IDC
- 100% of IoT initiatives will be supported by AI capabilities by 2019 — IDC
- 30% of companies will employ AI to increase at least one primary sales processes by 2020 — Gartner
- Algorithms will positively alter the behaviour of billions of workers globally by 2020 — Gartner
- The artificial intelligence market will surpass $40 billion by 2020. — Constellation Research
- AI will drive 95% of customer interactions by 2025 — Servion
Source: Various research reports
Best of G-Square Finalytica-2017
Financial Markets Analytics coverage
There are a number of reasons an investor would use options. These include speculation, hedging, spreading, and creating synthetic positions. Some of them are described below:
Market risk refers to the risk of losses in an organisations trading book due to changes in equity prices, interest rates, credit spreads, foreign-exchange rates, commodity prices, and other indicators whose values are set in a public market. To manage market risk, organizations deploy a number of highly sophisticated mathematical and statistical techniques. Chief among these is value-at-risk (VAR) analysis, which over the past 15 years has become established as the industry and regulatory standard in measuring market risk. more…
A Funds transfer pricing (FTP) is the process through which banks and other financial institutes allocate their earnings to the various lines of businesses in which they are engaged.
With the increased no. of business lines in an organizations, it is crucial to determine the profitability of each. Measuring profits on each level allows an internal comparison of effectiveness. more…
AI and Analytics Related Coverage
Machine learning: what is and what is not
Artificial Intelligence and machine learning are two different things. For a 19th century man even a simple calculating machine could constitute AI. But we all now agree that even more advanced computer algorithms are not machine learning but human intelligence codified into machine. So what is machine learning (ML)? Of course everyone will have her own way of defining ML, but overtime I have defined my own thumb-rules for detecting what is ML. more…
Out of Core Analytics using MonetDB
Most often than not, the amount of data one needs to analyse will fit in a hard disc. It may not fit in memory though. That’s where databases trump over in-memory solutions like R or Pandas (Python) for analytics. For sometime we have been arguing that column stores/columnar databases will be ideal for analytics (https://www.linkedin.com/pulse/column-stores-future-analytics-gopi-suvanam). Most powerful of these columnar solutions is a nifty database called MonetDb (https://www.monetdb.org/). more…
Imagine you are an organization sitting on a tons of transactional and other business data which is stored in structured database. Now, you have to analyse it on a daily basis to get vital insights about sales, customers, channels and many other business parameters, what will be your approach? more…
Use Cases & Case Studies
Trending data-driven consulting
Data Science is the buzzword these days in most of the organisations. Business units which drive sales, marketing, finance or manage risk drives the CXOs through the huge amount of data they are collecting and processing. Data in its purest form may not drive any decision but data analytics based advice and those solutions are driving decisions. Data to analytics to insights to action is the typical decision making cycle in these data driven organisations. In the Indian context, while the top two consulting & the Big four continue to drive the strategic and advisory business for the bigger corporate groups on the strategic consulting and decisions, boutique data driven consulting and analytics firm continue to capture the share from them on data driven decisions. more…
Sales Analytics is a process to understand and predict the sales channel trends, potential productivity & predicted results and likely attrition behaviour. It will help to determine success of past and forecast how the future will fare. more…
Customer Life Time Value (CLTV)
Customer lifetime value analysis is a method to predict how much an organization can benefit from a customer in their entire future relationship. In technical terms it is the “discounted value of future profits generated by a customer. more…
