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N. R. Narayana Murthy was born on 20 August 1946 in Sidlaghatta, a city in India's south-western state of Karnataka [20] into a Kannada- speaking middle-class Brahmin family. [21] After completing his school education, he went to the National Institute of Engineering and graduated in 1967 with a bachelor's degree in electrical engineering .
Murthy started Infosys with six engineers with $250 in 1981, and took advantage of Western tech companies hoping to outsource IT operations to lower-cost India. He stepped down as the company's ...
The investors were rattled as news of the arrests broke in Mumbai. The share of the LIC Housing Finance, Central Bank of India, Punjab National Bank, Bank of India as well as other banking and real-estate stock declined. [2] [6] The Union finance ministry initially claimed that the case was a bribery incident, and not a large-scale scam.
The ICICI-Videocon loan scam is about a criminal conspiracy by Chanda Kochhar as Managing Director of ICICI Bank who abused her position by sanctioning a ₹ 3,250 crore (US$696.34 million) loan to Venugopal Dhoot's Videocon International Electronics Limited (VIEL) between June 2009 and October 2011 to cheat the bank in lieu of illegal gratification and undue benefit received in NuPower ...
But the program, which tasked banks and other private lenders with processing applications, was beset by fraud from its earliest days in the spring of 2020, with some recent estimates suggesting ...
Longtime Infosys CEO N.R. Narayana Murthy has returned to the company he founded in 1981 as its new executive chairman of the board, Infosys recently announced. The Infosys board approved the ...
Hunter Fraud Score is a rating score in India prepared by the credit information company Experian to help detect fraud in credit applications through analytical approach. The score was launched in 2016 and is used by Indian banks and insurance companies to help them lower their losses.
Fraud detection is a knowledge-intensive activity. The main AI techniques used for fraud detection include: Data mining to classify, cluster, and segment the data and automatically find associations and rules in the data that may signify interesting patterns, including those related to fraud.