Customers typically wants to automate the process of loans underwriting by using applicants personal data & underwriters comments data of past applications. Thus Clients want an automated solution for processing loans on the go for onboarding new customers
We analyse the demographics, various scores of applicants & textual comments & identify most important factors which will help in the rejection or approval of applications.… Continue reading
1) Eight Analytics Trends for the Intelligent Enterprise identified in a report by Microstrategy:
- AI will reshape analytic and business innovation
- Competition for data science and analytics talent
- Convergence of real-time and Batch-based analytics
- Voice and natural language interfaces become mainstream
- Emergence of augmented analytics
- Machine learning, AI and edge and video analytics
- Access vs.
Applications of Text mining in G-Square’s Bigdator
G-Square Solutions applies Text Analytics in its Flagship product ‘Bigdator’. Bigdator uses Latent Dirichlet Allocation Model for Topic Modelling, Latent Semantic Analysis Model for summarizing a long article or comments and Support Vector Machine (SVM) model for sentiment analysis.… Continue reading
HAPPENINGS IN THE ANALYTICS, FINTECH & AI WORLD
- Emerging technology got prominent mention in the India Union Budget 2018-19. Federal policy think tank NITI Aayog will initiate a national program on artificial intelligence, and the Department of Science & Technology will launch a mission to support investments in research and training in robotics, artificial intelligence, digital manufacturing, big data analytics, quantum communication and internet of things.
Text Mining Analytics
The term text analytics describes a set of linguistic, statistical, and machine learning techniques that model and structure the information content of textual sources for business intelligence, exploratory data analysis, research, or investigation.… Continue reading
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.… Continue reading
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.
- Stock Exchanges in India are exploring the opportunity to venture beyond the current businesses to create data repository services, Artificial Intelligence or a big data analytics eco-system. Last week, the Bombay Stock Exchange and the National Stock Exchange sought Securities and Exchange Board of India (SEBI)’s permission to form a separate entity to take on these businesses.
Let’s say I want to build a financial market prediction model based on news flow. The current way to do this is:
- Collect lot of news articles
- Collect financial market movement data
- Use machine learning models (black-box or otherwise) to predict markets from news
This is not a scalable model of operation for building AI/ML solutions.… Continue reading
‘In God we trust, all other must bring data’ said late William Edward Deming – the famous American statistician and professor. Gut based decision making is out, subjectivity is out, generic experience based decisions are out – Data driven decisions are in.… Continue reading
Many businesses use data insights to support their decisions instead of driving their actions. After all, data is only valuable if you can translate it into actionable insights. Your organization might be sitting on the world’s largest data pile, but it is useless unless you have the means to translate it into insights that drives your business.… Continue reading