CLOZE TEST 2 FOR IBPS (Based on New Pattern)

Directions: In the passage given below there are 10 blanks, each followed by a word given in bold. Every blank has four alternative words given in options (A),(B),(C) and (D). You have to tell which word will best suit the respective blank. Mark (E) as your answer if the work given in bold after the blank is your answer i.e “No change required”.

Joining “Hamilton”, a Broadway show, and concerts by Adele, a British soul diva, on the list of tickets-to-kill-for in New York is a screening in an ugly new office building that recently _1_(vacillant) in the East Village, a place best known for _2_(ramble) culture. There is a ten-week-long queue to see simulations by Watson, IBM’s _3_(clash) artificial-intelligence platform. Initially known for stunts such as beating human contestants on “Jeopardy!”, a quiz show, Watson has been seeking a wider audience. It has found a vast potential one in the world of financial regulation. Rules have become so _4_(desultory) and mysterious that even regulators have begun asking for a map. In response, a market is springing up: for “regtech”, fintech’s nerdy new offspring. On September 29th, IBM announced the purchase of Promontory, a 600-strong consultancy whose senior staff include former officials from the Federal Reserve, the World Bank, the Securities and Exchange Commission and other regulators. The hope is that person and machine will combine into a vast business. Promontory was founded in 2001 by Eugene Ludwig, who had headed one of America’s primary bank-supervisory agencies. It grew first because of the _5_(fuzzy) of new rules during the previous, Bush administration and then prospered, says Mr Ludwig, as this process expanded under Barack Obama. Promontory has recently dabbled in software, but is best known for its employees’ background and their capacity to provide expertise (its contention), contacts (its critics’) or both. Either way, it is a profoundly human business. Watson, for all its charms, is not. Automation of financial institutions_6_(coherent) a core business for IBM. It played a central role in the development of the ATM; its systems keep many banks and insurance companies around the world humming along. Aware that annual expenditure on regulation and compliance is vast—it reckons in excess of $270 billion, of which $20 billion is spent simply on understanding the requirements—it began work on adding this business to Watson in early 2015. Chief compliance officers and lawyers were interviewed to break down their tasks and needs.

The first area of focus was trading, which has the virtue of being both discrete and wildly complex. A pilot programme with half a dozen banks and three exchanges began in July, providing surveillance. A library of possible illicit schemes is fed into Watson, which can then evaluate trading patterns and communications ranging from overt messages to social media (voice analysis will be added in November). Scrutiny can extend to the network of people on the other end of trades in order to untangle complex relationships. The next area is to provide clarity about rules. They are sorted by jurisdictions, institutional divisions, products and so forth, and then further broken down between rules and guidance. Watson is getting better at categorizing the various regulations and matching them with the appropriate enforcement mechanisms. Its conclusions are vetted, giving it an education that should improve its effectiveness in the future. Promontory’s experts are expected to help Watson learn. A dozen rules are now being _7_(spotty) weekly. Thousands are still to go but it is hoped the process will speed up as the system evolves. Ultimately, IBM hopes speeches by influential figures, court verdicts and other such sources will be automatically uploaded into Watson’s cloud-based brain. They can play a role in determining what regulations matter, and how they will be enforced. Global financial institutions provide an _8_(odds) market for these services, but so too do small, local ones that lack the scale to justify the cost of a team of legal experts. A third group is the regulators themselves, who often privately _9_(liminal) about being bewildered by their own remit and distrust other regulators with overlapping briefs. To some extent Watson’s success depends on whether the rules are _10_(stringent), make sense and are fairly applied. At the very least, it will be able to highlight anomalies. If successful, Watson could shift legal authority from individuals to laws. That, of course, may be its greatest virtue.

1.A) bloopered
B) booked-up
C) popped-up
D) drop-down
E) No Correction Required

2.A) wild
B) offbeat
C) quaint
D) usual
E) No Correction Required

3.A) judicious
B) deductive
C) cognitive
D) likely
E) No Correction Required

4.A) rambling
B) spreading
C) growling
D) sprawling
E) No Correction Required

5.A) scattering
B) slathering
C) dissipating
D) dabbing
E)  No Correction Required

6.A) has been long
B) has long been
C) had been long
D) had long been
E) No Correction Required

7.A) assimilated
B) adopted
C) separated
D) rejected
E) No Correction Required

8.A) conspicuous
B) mysterious
C) steep
D) obvious
E) No Correction Required

9.A) adoration
B) grouse
C) approval
D) award
E) No Correction Required

10.A) steady
B) stiff
C) consistent
D) contradictory
E) No Correction Required



Answers

1. C 
2. B
3. C 
4. D
5. B 
6. B 
7. A 
8. D
9. B 
10. C