Saturday, July 6, 2013

Ethical banking in Italy

Banca Etica


A bank that takes its name seriously



ANOTHER Italy was on display this month at Florence’s 16th-century Fortezza da Basso, where Banca Etica, an ethical bank, held its annual meeting. Outside, stands were selling all sorts of bio foods. Inside, casually dressed shareholders discussed weighty subjects such as social responsibility and the economic crisis.
Until a few months ago Banca Etica was known only to insiders. But then the new parliamentarians of the anti-establishment Five Star Movement, which won more than 25% of the vote at the general election in February (but flopped at local polls on May 26th and 27th), queued to open accounts when parliament convened. That helped spread the word. Now people are curious.

Such ideas may explain why Banca Etica is small: it has only 17 branches, around 230 staff and loans of less than €1 billion ($1.3 billion), and made a profit of €1.6m in 2012. The firm provides mainly credit to the non-profit sector and green businesses. It was, for instance, the first Italian bank to lend to co-operatives of young people who farm land confiscated from the Mafia.
Ethical banks are nothing new, but Banca Etica takes its name seriously. Its annual report calls for a citizens’ revolt against casino finance, the use of tax havens and speculation in commodities. Executive pay is not allowed to exceed six times the lowest wage at the bank. And it does not want to get involved with anything having to do with pornography, oil or arms (a rule that even applies to shareholders: the directors’ report raised concerns that two, Banca Popolare di Milano and Banca Popolare dell’Emilia Romagna, are now on a list of banks related to arms production and sales).
Yet Banca Etica has attracted a broad range of shareholders. They number 38,400, of which 5,900 are firms, including 83 financial institutions. By some measures, it is among Italy’s best-run banks: only 0.4% of loans are in default and only 4.9% of loans are classified as “problematic”. And its managers seems inventive. They have set up a platoon of 24 travelling bankers to drum up business in areas far from its branches.
Can Banca Etica grow beyond its niche? That probably depends less on the firm itself than on Italy’s established banks. If there are more scandals such as the one surrounding Monte dei Paschi di Siena, the world’s oldest bank, which lost billions in dubious derivatives deals, Banca Etica may attract more business than it can deal with.

Thursday, July 4, 2013

Smart Phones Help Kill Mosquitoes

Jun 1st 2013 |From the print edition

LIVE in a crowded South Asian city and a host of problems—smog, contagious disease, corruption—may plague you. Each winter, the air grows foul. The monsoon season brings mosquitoes, bloodsuckers capable of carrying nasties such as dengue and malaria. As cities expand and people are packed closer, they are more likely to pass on infections. Overwhelmed municipalities, especially if weakened by corruption, offer a weak response. In Lahore, Pakistan’s second-most populous city, there were 21,292 confirmed dengue patients in 2011, a particularly dire year. At least 350 of them died, victims of associated haemorrhages or shock.
The usual response is to send out fogging lorries to spray a choking mixture of insecticide (such as DDT) and kerosene to kill mosquitoes. Public officials also advise residents to drain every reservoir of water near their homes. Mosquito larvae flourish in puddles, even inside old tyres or old flower pots. But foggers sometimes spread their helpful poison too liberally, where no dengue-infected mosquitoes are present, or too rarely, perhaps neglecting poor neighbourhoods. Municipal workers skip puddle-hunting, or fail to tip chemicals into ponds to kill the larvae. Crooked workers sell their insecticides or refuse to spray without bribes from residents.
    After their especially grim spell, Lahore’s authorities last year looked for ways to use technology—in particular cheap, widely available smartphones—to help them put up a better fight against the mosquitoes. They equipped 1,500 city workers with $100 smartphones and asked them to take “before and after” photographs of their anti-dengue tasks and to upload images, tagged by location, so that they could be plotted on an online map, made available to the public. They also recorded where larvae were spotted (usually in traps), and reported the locations of known dengue patients.
    The resulting data were then analysed to create a visualisation showing where and when dengue was infecting people. It was then possible to predict where dengue-infected mosquitoes would buzz up next, so that fogging and larvae-hunts could be targeted appropriately. The use of smartphones also had more subtle effects. Knowing they were being monitored and tracked in public, municipal workers also applied themselves more assiduously to their tasks. Anyone looking at the online map could see if the work being done in a particular area was adequate—and complain if it was not.
    All this seems to have worked. Last year Lahore suffered just 255 dengue cases, and no deaths, says Umar Saif, a computer scientist seconded to the Punjab provincial government who oversaw the tracking side of the project. Strong political interest helped, too. The chief minister of Punjab, Shahbaz Sharif, who was re-elected in May, led daily meetings on the anti-dengue fight. Of course, 2012 might simply have been a milder year for dengue than 2011, so the effectiveness of the new approach will become apparent only after a few more years. Already, however, the Punjab government is extending the use of mobile phones to gather data and improve broader public services.
    Other officials, such as veterinarians who are paid to travel to farms to deworm cows, have to take smartphones to record themselves at work and upload geotagged self-portraits to an official website. This makes it possible to check that they are actually turning up for work. They are also required to record the phone numbers of farmers they visit, some of whom are randomly called afterwards to be asked if the service was up to scratch.
    Mr Saif is also trying out a model devised by Zubair Bhatti, a former Pakistani local-government official who now works for the World Bank. It involves making random calls to users of public services—including the police, health services and administrative services such as registering property—to inquire about the quality of service and whether they were asked to pay a bribe. Anyone who volunteers his mobile-phone number (so far, more than 1.3m people have signed up) will get a two-minute robocall from Mr Sharif, the chief minister. He explains that they will shortly receive a text message reviewing their encounter with a local official.
    Even among the poorest fifth of households, 80% now use phones, so the technology can reach almost everyone. Illiteracy is a problem, but the chief minister’s call alerts a recipient to get help, if needed, with reading the text message when it arrives. It contains a specific question: did the police respond, as required, within 15 minutes of your emergency call? Were you asked for a bribe at the hospital, or when registering property? By collating the responses it is possible to spot problem departments and crooked officials.
    Around 25,000-30,000 automated calls are now being made each day, and “we are gathering remarkable data on who is corrupt and where,” says Mr Saif. It is heartening that in the first two months after the scheme began, 60% of respondents said they were happy with their recent experiences of public services. That could help put anger over corruption into perspective. It is striking, too, that many complaints were over unclean offices, unclear fees for official services and petty frustrations, rather than corruption alone.
    Either fight, against dengue or shoddy public services, could yet be reversed in Lahore. Smartphones, geo
    ​​
    tagged photos and canvassing for public feedback only help if the data gathered are acted upon. But phones are letting sunlight shine brighter on the workings of public services in Lahore. If they work as a disinfectant there, others may follow its lead.

    Wednesday, July 3, 2013

    Brig Usman

    This article was published in Outlook in 2012, the centenary year of Brigadier Usman.

    A Lion, To The Last 
    Martyred on the front, Brigadier Usman’s story is an ode to honour
    Outlook July 09 2012
     
    Naushera ka Sher’ (July 15, 1912 - July 3, 1948)
    No military commander in independent India, except one, has received a state funeral. But so overwhelmed was a nascent nation at the supreme courage and sacrifice of Brigadier Mohammad Usman 66 years ago that Prime Minister Jawaharlal Nehru and his cabinet colleagues turned up at the funeral of the hero—the “highest ranking military commander till date” to lay down his life in the battlefield—who was laid to rest with full state honours on the premises of Jamia Millia Islamia in New Delhi.
    Two memorials, one at Jamia Millia Islamia, the other at Naushera, stand as silent reminders of the man today—as the nation prepares to observe his one hundredth birth anniversary.

    Brig Usman leading a parade in Multan
    It was 5.45 pm on July 3, 1948. Jhangar near Naushera (Jammu). The sun was about to set and the brigadier, having offered his evening prayers, was holding the routine, daily meeting with his staff officers at his command post—actually, a makeshift structure rigged with the help of a few tents. A sudden burst of shelling sent them all scurrying for cover behind a rock formation.
    The brigadier sized up the situation and saw the enemy’s field guns to be too well-entrenched. Spotting an enemy observation post sited on an elevation, he shouted instructions for his field guns to engage the fortification while he himself attempted a dash, presumably in an effort to alert others. But as he stepped out, a shell from a 25-pounder landed almost next to him—its splinters killing him on the spot. Usman died 12 days short of his 36th birthday.
    Hailing from a modest, middle-class family in Azamgarh, Uttar Pradesh, Usman had steel in his spine. At the tender age of 12, they still remember of him, he had jumped into a well to rescue a drowning child. He had a stammering problem in childhood, but overcame the handicap by sheer willpower. One of the ten Indian boys to secure admission to the Royal Military Academy (RMA) at Sandhurst, England, in 1932—the last batch of Indians to do so—the feat made no less remarkable by that distinction. Usman was commissioned in the storied Baluch Regiment at the age of 23 and saw action in Afghanistan and Burma during the World War. He rose quickly to the rank of brigadier, drawing attention to himself by his firm and fair handling of the precarious communal situation at Multan. During the splintering of the army in the wake of Partition, Usman was offered the promise of out-of-turn promotions and the prospect of becoming the army chief in Pakistan. A senior Muslim officer at the time, everyone expected him to grab the offer.

    Brig Usman with Nehru
    But the brigadier surprised everyone by opting to stick with India. Neither Mohammed Ali Jinnah nor Liaquat Ali Khan could convince him to have a change of heart.
    Of Usman’s heroics, former vice-chief of the army staff, Lieutenant General S.K. Sinha, then General Staff Officer to General Cariappa, recalls: “I accompanied General Cariappa to Naushera. He went round the defences and then told Brigadier Usman that Kot overlooked our defences and must be secured. Two days later, Usman mounted a successful attack against that feature. He named it Operation Kipper, the General’s nickname. A week later, over 10,000 infiltrators attacked Naushera. With Kot held by us, our boys inflicted a crushing defeat on the enemy, who retreated leaving over 900 dead. This was the biggest battle of the Kashmir war. Usman became a national hero.”
    The defence of Naushera, against overwhelming odds and numbers, made him a living legend. Naushera ka Sher. The Pakistanis announced a prize of Rs 50,000 for his head, an astronomical sum in 1948. But even as congratulatory messages poured in, the brigadier remained unaffected and continued to sleep on a mat laid on the floor. He had taken a vow that he would not use a cot till he recaptured Jhangar, from where he had to withdraw earlier in the face of a fierce onslaught by the infiltrators. Jhangar was of strategic importance, located at the junction of roads coming from Mirpur and Kotli. But more compelling was his fierce pride in his men and determination to restore their honour.

    His memorial in Jamia Millia Islamia. (Photograph by Tribhuvan Tiwari)
    On March 15, 1948, the brigadier signed an order to the “Comrades of 50 (I) Para Brigade”. It read: “Time’s come for the capture of Jhangar. It is not an easy task, but I’ve complete faith in you all to do your best to recapture the lost ground and retrieve the honour of our arms—we must not falter, we must not fail. Forward friends, fearless we go to Jhangar. India expects everyone to do his duty. Jai Hind.” Three days later, his troops recaptured Jhangar.
    The legend grew. It would have grown larger still. Had the Lion of Naushera survived the July of 1948, could he have ended his career as India’s first Muslim army chief?

    Udder Nonsense

    ( From Letters to the Editor, the Economist)

    SIR – I totally support the raw-milk activists you reported on (The menace of moo-shine”, June 1st). Our government has bought in to a herd mentality on pasteurisation, a process that robs milk of most of its nutritional value and which primarily benefits supermarket chains by extending the shelf life of creamy stuff. Americans were drinking milk long before Louis Pasteur came along (did you know that he was French?)
    The government can promote the benefits of pasteurised milk until the cows come home. They can’t butter me up. Long live the Alliance for Raw Milk internationale!
    Kevin Coleman
    Chicago

    GREEN BOOK by Morgan Stanley

    GREEN BOOK by Morgan Stanley.....  gives you tips on energy saving in your Day2Day life...




    What if scientists had their own Logos ?

    Tuesday, July 2, 2013

    How algorithms rule the world ...............


    Financial charts
    The financial sector has long used algorithms to predict market fluctuations, but they can also help police identify crime hot spots or online shops target their customers. Photograph: Danil Melekhin/Getty Images
    On 4 August 2005, the police department of Memphis, Tennessee, made so many arrests over a three-hour period that it ran out of vehicles to transport the detainees to jail. Three days later, 1,200 people had been arrested across the city – a new police department record. Operation Blue Crush was hailed a huge success.
    Larry Godwin, the city's new police director, quickly rolled out the scheme and by 2011 crime across the city had fallen by 24%. When it was revealed Blue Crush faced budget cuts earlier this year, there was public outcry. "Crush" policing is now perceived to be so successful that it has reportedly been mimicked across the globe, including in countries such as Poland and Israel. In 2010, it was reported that two police forces in the UK were using it, but their identities were not revealed.
    Crush stands for "Criminal Reduction Utilising Statistical History". Translated, it means predictive policing. Or, more accurately, police officers guided by algorithms. A team of criminologists and data scientists at the University of Memphis first developed the technique using IBM predictive analytics software. Put simply, they compiled crime statistics from across the city over time and overlaid it with other datasets – social housing maps, outside temperatures etc – then instructed algorithms to search for correlations in the data to identify crime "hot spots". The police then flooded those areas with highly targeted patrols.
    "It's putting the right people in the right places on the right day at the right time," said Dr Richard Janikowski, an associate professor in the department of criminology and criminal justice at the University of Memphis, when the scheme launched. But not everyone is comfortable with the idea. Some critics have dubbed it "Minority Report" policing, in reference to the sci-fi film in which psychics are used to guide a "PreCrime" police unit.
    The use of algorithms in policing is one example of their increasing influence on our lives. And, as their ubiquity spreads, so too does the debate around whether we should allow ourselves to become so reliant on them – and who, if anyone, is policing their use. Such concerns were sharpened further by the continuing revelations about how the US National Security Agency (NSA) has been using algorithms to help it interpret the colossal amounts of data it has collected from its covert dragnet of international telecommunications.
    "For datasets the size of those the NSA collect, using algorithms is the only way to operate for certain tasks," says James Ball, the Guardian's data editor and part of the paper's NSA Files reporting team. "The problem is how the rules are set: it's impossible to do this perfectly. If you're, say, looking for terrorists, you're looking for something very rare. Set your rules too tight and you'll miss lots of, probably most, potential terror suspects. But set them more broadly and you'll drag lots of entirely blameless people into your dragnet, who will then face further intrusion or even formal investigation. We don't know exactly how the NSA or GCHQ use algorithms – or how extensively they're applied. But we do know they use them, including on the huge data trawls revealed in the Guardian."
    From dating websites and City trading floors, through to online retailing and internet searches (Google's search algorithm is now a more closely guarded commercial secret than the recipe for Coca-Cola), algorithms are increasingly determining our collective futures. "Bank approvals, store cards, job matches and more all run on similar principles," says Ball. "The algorithm is the god from the machine powering them all, for good or ill."
    New York Stock ExchangeMost observers blame the 'flash crash' of May 2010 on the use of algorithms to perform high-frequency trading. Photograph: Spencer Platt/Getty Images
    But what is an algorithm? Dr Panos Parpas, a lecturer in the quantitative analysis and decision science ("quads") section of the department ofcomputing at Imperial College London, says that wherever we use computers, we rely on algorithms: "There are lots of types, but algorithms, explained simply, follow a series of instructions to solve a problem. It's a bit like how a recipe helps you to bake a cake. Instead of having generic flour or a generic oven temperature, the algorithm will try a range of variations to produce the best cake possible from the options and permutations available."
    Parpas stresses that algorithms are not a new phenomenon: "They've been used for decades – back to Alan Turing and the codebreakers, and beyond – but the current interest in them is due to the vast amounts of data now being generated and the need to process and understand it. They are now integrated into our lives. On the one hand, they are good because they free up our time and do mundane processes on our behalf. The questions being raised about algorithms at the moment are not about algorithms per se, but about the way society is structured with regard to data use and data privacy. It's also about how models are being used to predict the future. There is currently an awkward marriage between data and algorithms. As technology evolves, there will be mistakes, but it is important to remember they are just a tool. We shouldn't blame our tools."
    The "mistakes" Parpas refers to are events such as the "flash crash" of 6 May 2010, when the Dow Jones industrial average fell 1,000 points in just a few minutes, only to see the market regain itself 20 minutes later. The reasons for the sudden plummet has never been fully explained, but most financial observers blame a "race to the bottom" by the competing quantitative trading (quants) algorithms widely used to perform high-frequency trading. Scott Patterson, a Wall Street Journal reporter and author of The Quants, likens the use of algorithms on trading floors to flying a plane on autopilot. The vast majority of trades these days are performed by algorithms, but when things go wrong, as happened during the flash crash, humans can intervene.
    "By far the most complicated algorithms are to be found in science, where they are used to design new drugs or model the climate," says Parpas. "But they are done within a controlled environment with clean data. It is easy to see if there is a bug in the algorithm. The difficulties come when they are used in the social sciences and financial trading, where there is less understanding of what the model and output should be, and where they are operating in a more dynamic environment. Scientists will take years to validate their algorithm, whereas a trader has just days to do so in a volatile environment."
    Most investment banks now have a team of computer science PhDs coding algorithms, says Parpas, who used to work on such a team. "With City trading, everyone is running very similar algorithms," he says. "They all follow each other, meaning you get results such as the flash crash. They use them to speed up the process and to break up big trades to disguise them from competitors when a big investment is being made. It's an on-going, live process. They will run new algorithms for a few days to test them before letting them loose with real money. In currency trading, an algorithm lasts for about two weeks before it is stopped because it is surpassed by a new one. In equities, which is a less complicated market, they will run for a few months before a new one replaces them. It takes a day or two to write a currency algorithm. It's hard to find out information about them because, for understandable reasons, they don't like to advertise when they are successful. Goldman Sachs, though, has a strong reputation across the investment banks for having a brilliant team of algorithm scientists. PhDs students in this field will usually be employed within a few months by an investment bank."
    The idea that the world's financial markets – and, hence, the wellbeing of our pensions, shareholdings, savings etc – are now largely determined by algorithmic vagaries is unsettling enough for some. But, as the NSA revelations exposed, the bigger questions surrounding algorithms centre on governance and privacy. How are they being used to access and interpret "our" data? And by whom?
    Dr Ian Brown, the associate director of Oxford University's Cyber Security Centre, says we all urgently need to consider the implications of allowing commercial interests and governments to use algorithms to analyse our habits: "Most of us assume that 'big data' is munificent. The laws in the US and UK say that much of this [the NSA revelations] is allowed, it's just that most people don't realise yet. But there is a big question about oversight. We now spend so much of our time online that we are creating huge data-mining opportunities."
    Pair of handcuffsAlgorithms can run the risk of linking some racial groups to particular crimes. Photograph: Alamy
    Brown says that algorithms are now programmed to look for "indirect, non-obvious" correlations in data. "For example, in the US, healthcare companies can now make assessments about a good or bad insurance risk based, in part, on the distance you commute to work," he says. "They will identity the low-risk people and market their policies at them. Over time, this creates or exacerbates societal divides. Professor Oscar Gandy, at the University of Pennsylvania, has done research into 'secondary racial discrimination', whereby credit and health insurance, which relies greatly on postcodes, can discriminate against racial groups because they happen to live very close to other racial groups that score badly."
    Brown harbours similar concerns over the use of algorithms to aid policing, as seen in Memphis where Crush's algorithms have reportedly linked some racial groups to particular crimes: "If you have a group that is disproportionately stopped by the police, such tactics could just magnify the perception they have of being targeted."
    Viktor Mayer-Schönberger, professor of internet governance and regulation at the Oxford Internet Institute, also warns against humans seeing causation when an algorithm identifies a correlation in vast swaths of data. "This transformation presents an entirely new menace: penalties based on propensities," he writes in his new book, Big Data: A Revolution That Will Transform How We Live, Work and Think, which is co-authored by Kenneth Cukier, the Economist's data editor. "That is the possibility of using big-data predictions about people to judge and punish them even before they've acted. Doing this negates ideas of fairness, justice and free will. In addition to privacy and propensity, there is a third danger. We risk falling victim to a dictatorship of data, whereby we fetishise the information, the output of our analyses, and end up misusing it. Handled responsibly, big data is a useful tool of rational decision-making. Wielded unwisely, it can become an instrument of the powerful, who may turn it into a source of repression, either by simply frustrating customers and employees or, worse, by harming citizens."
    Mayer-Schönberger presents two very different real-life scenarios to illustrate how algorithms are being used. First, he explains how the analytics team working for US retailer Target can now calculate whether a woman is pregnant and, if so, when she is due to give birth: "They noticed that these women bought lots of unscented lotion at around the third month of pregnancy, and that a few weeks later they tended to purchase supplements such as magnesium, calcium and zinc. The team ultimately uncovered around two dozen products that, used as proxies, enabled the company to calculate a 'pregnancy prediction' score for every customer who paid with a credit card or used a loyalty card or mailed coupons. The correlations even let the retailer estimate the due date within a narrow range, so it could send relevant coupons for each stage of the pregnancy."
    Harmless targeting, some might argue. But what happens, as has already reportedly occurred, when a father is mistakenly sent nappy discount vouchers instead of his teenage daughter whom a retailer has identified is pregnant before her own father knows?
    Mayer-Schönberger's second example on the reliance upon algorithms throws up even more potential dilemmas and pitfalls: "Parole boards in more than half of all US states use predictions founded on data analysis as a factor in deciding whether to release somebody from prison or to keep him incarcerated."
    Norah Jones, 2012Norah Jones: a specially developed algorithm predicted that her debut album contained a disproportionately high number of hit records. Photograph: Olycom SPA/Rex Features
    Christopher Steiner, author of Automate This: How Algorithms Came to Rule Our World, has identified a wide range of instances where algorithms are being used to provide predictive insights – often within the creative industries. In his book, he tells the story of a website developer called Mike McCready, who has developed an algorithm to analyse and rate hit records. Using a technique called advanced spectral deconvolution, the algorithm breaks up each hit song into its component parts – melody, tempo, chord progression and so on – and then uses that to determine common characteristics across a range of No 1 records. McCready's algorithm correctly predicted – before they were even released – that the debut albums by both Norah Jones and Maroon 5 contained a disproportionately high number of hit records.
    The next logical step – for profit-seeking record companies, perhaps – is to use algorithms to replace the human songwriter. But is that really an attractive proposition? "Algorithms are not yet writing pop music," says Steiner. He pauses, then laughs. "Not that we know of, anyway. If I were a record company executive or pop artist, I wouldn't tell anyone if I'd had a number one written by an algorithm."
    Steiner argues that we should not automatically see algorithms as a malign influence on our lives, but we should debate their ubiquity and their wide range of uses. "We're already halfway towards a world where algorithms run nearly everything. As their power intensifies, wealth will concentrate towards them. They will ensure the 1%-99% divide gets larger. If you're not part of the class attached to algorithms, then you will struggle. The reason why there is no popular outrage about Wall Street being run by algorithms is because most people don't yet know or understand it."
    But Steiner says we should welcome their use when they are used appropriately to aid and speed our lives. "Retail algorithms don't scare me," he says. "I find it useful when Amazon tells me what I might like. In the US, we know we will not have enough GP doctors in 15 years, as not enough are being trained. But algorithms can replace many of their tasks. Pharmacists are already seeing some of their prescribing tasks replaced by algorithms. Algorithms might actually start to create new, mundane jobs for humans. For example, algorithms will still need a human to collect blood and urine samples for them to analyse."
    There can be a fine line, though, between "good" and "bad" algorithms, he adds: "I don't find the NSA revelations particularly scary. At the moment, they just hold the data. Even the best data scientists would struggle to know what to do with all that data. But it's the next step that we need to keep an eye on. They could really screw up someone's life with a false prediction about what they might be up to."