AI News, Is fraud artificial intelligence

Rise of the robots: Artificial intelligence and the fight against fraud

While fraud is an age old behaviour, with the rise of the digital age, criminals are finding new and inventive ways to deceive both unsuspecting victims and our public services.

found online fraud is now the most prevalent crime in England and Wales, with the Office for National Statistics (ONS) showing that around one in six of all estimated crimes in England in the year ending March 2018 to be fraud committed online.

The cost of this crime is estimated to be £10 billion, with around 2 million cyber-related fraud incidents last year, however the true extent of the problem remains unknown.

A movement towards hosting most transactional public services online will introduce additional challenges for both central and local government when it comes to tackling this issue.

By developing and launching state-of-the-art algorithms, DWP aims to detect a number of identity cloning techniques which have been commonly used by organised criminal gangs committing mass-scale benefit fraud.

Freedom of information requests by the media to DWP have shown that over the financial years 2015/16 and 2016/17, of the 332,850 cases closed following reports by members of the public, 287,950 were found to have no or little evidence to substantiate the claim –

Many insurance agencies and banks have been investing in AI and machine learning to take on fraud with Lloyds Banking Group, for example, using machine learning for online fraud prevention with models that can detect whether the person logged in to our online banking is a customer, a fraudster, or even a ‘bot’.

Artificial intelligence may help foil online dating scams

Scientists have developed new artificial intelligence (AI) based computing algorithms for dating apps and websites that 'think' like humans to pinpoint fake profiles designed to con victims out of thousands of pounds.

The new algorithms have been designed specifically to understand what fake dating profiles look like and then to apply this knowledge when they scan profiles submitted to online dating services.

They automatically look out for suspicious signs inadvertently included by fraudsters in the demographic information, the images and the self-descriptions that make up profiles, and reach an overall conclusion as to the probability of each individual profile being fake.

Artificial Intelligence could help to foil online dating scams

Researchers from across the UK, including experts from the University of Bristol Cyber Security Group, have developed new algorithms that can understand what fake dating profiles look like and then apply this knowledge when they scan profiles submitted to online dating services.

designed as part of a wide-ranging project aimed at combating online fraud - automatically look out for suspicious signs inadvertently included by fraudsters in the demographic information, the images and the self-descriptions that make up profiles, and reach an overall conclusion as to the probability of each individual profile being fake.

“Of course, we should be mindful that such automated techniques are not 100% accurate so they complement rather than replace existing mechanisms relying on human detection - providing those working on detecting such fraudulent profiles a new tool in their fight against romance scams.”

The work on the textual and other computercharacteristics of online dating messages and profiles formed just one aspect of an overall research initiative that has also involved UCL, King’s College London, Cardiff University and partners worldwide and has aimed at boosting efforts to detect and prevent mass fraud that exploits online channels.

Coupa Blog

It’s something no one wants to talk about, but in the complex world of company spend and supplier relationships, it’s very difficult to avoid: fraud, the dirty little secret of the business world.

5% may seem like a small percentage of annual revenues, but it can add up to millions of dollars in lost revenue for your business, damaged reputations, and a reduction of trust.

Well, at 40%, tips are by far the most common way that fraud is identified, while internal audits and management reviews only identify 15% and 13% of fraud, respectively.

With this in mind, we can turn to the sage advice from Ray Dalio, American billionaire investor, hedge fund manager, and philanthropist, in Principles: Life and Work for guidance: “Have good controls so that you are not exposed to the dishonesty of others.”

In fact, data monitoring and analysis and surprise audits have been correlated with the biggest reductions (52% lower losses) and duration (58% faster detection) compared to alternatives.

The difference between yesterday’s technology and today’s is that now, we can bring these tools into processes at our companies to identify the everyday fraud that chips away at profitability and shareholder value.

if someone finds they can get away with fraud in one area, it suddenly becomes much more tempting to commit fraud in other areas, and soon, money is trickling steadily out of company accounts.

Artificial intelligence has advanced to point where it can do the dirty work of aggregating and analyzing billions of transactions from the business community to compile profiles and learn what constitutes “normal” behavior.

This approach can identify and stop losses to fraud more effectively than traditional audit processes while freeing up resources to focus on higher value tasks to drive company strategy.

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