We're a fraud detection company using advanced machine learning and network analysis technology to solve big problems. Our goal is to make online transactions safer and help our clients feel confident serving their customers. And we have fun in the meantime! We are a friendly bunch and pride ourselves in having a strong culture and adhering to our values of empathy, ambition, unity and integrity. We really value work/life balance and we embrace a flat hierarchy structure company-wide.

Ravelin, the London-based company using machine learning to help companies fight fraud when accepting online payments, has raised $20 million in new funding. The Series C round is led by Draper Esprit, with participation from existing investors Amadeus Capital Partners, BlackFin Tech, and Passion Capital. Ravelin disclosed $10 million in Series B funding in September 2018. Launched in 2016, Ravelin utilises machine learning and graph network technologies to help online businesses reduce losses to fraud and improve acceptance rates of orders. The idea is to do away with cruder, rule-based systems and use machine learning to negate false positives and give merchants more confidence accepting customers/transactions. With regards to product-market fit, Ravelin says it first found success with large-scale food and cab-ride marketplaces, but has since expanded into travel, ticketing, entertainment, gaming, gambling, and retail.

Identity fraud, in which a slice of your identity ranging from new credit cards to entire bank accounts is taken over by criminals, rose by 49 per cent in 2015 on the previous year. That totalled almost 170,000 cases, according to data collected by Cifas, the financial industry's non-profit fraud advisory service. The reason for the rise is that more and more we use the internet for financial transactions, but have very few ways to verify our identity without cumbersome systems involving human interaction, which are also vulnerable to fraud. Cifas' 2015 Fraudscape report shows that 86 per cent of identity fraud happened online, with bank accounts and credit or debit cards most targeted, closely followed by loans and communications, typically mobile phone accounts. Businesses looking to tackle fraud are turning to artificial intelligence and deploying neural networks because the systems learn in a manner like the brain's own neurons to try to bust fraud Traditionally, companies dealing with such problems have acted after the fact, trying to unravel complex or opportunistic frauds by working back through audit trails.

Customer churn is not the only problem being reduced by machine learning in the financial services sector. Another large focus area where leaders are breaking down barriers is in fraud prevention. Ravelin is a company showing just how effective machine learning can be in the space. The basic idea lies in spotting irregularities across patterns, as fake transactions have different attributes than legitimate ones. This technology also gives a company like Ravelin the ability to predict such fraudulent transactions to occur before they do.

The UK is at the forefront of the machine learning revolution, and the Early Stage investment team here at Amadeus is an active investor in the field. Start-ups applying artificial intelligence ('AI') and machine learning to a vast range of products come onto our radar almost daily, but investing in these complex technologies is not for the faint-hearted. So, I thought I would share some insights on start-ups we have backed and'where next?' for investors in a sector offering apparently endless possibilities. First, a quick analogy to explain what the difference between rule-based and machine learning-based systems is: remember when you were taught it was safe to cross a road when the light was green but not when it was red? That's just like old-fashioned computer programming: a set of conditions is described with a rule, or an'IF this, THEN that' statement, and some action or operation is chosen.

Identity fraud, in which a slice of your identity ranging from new credit cards to entire bank accounts is taken over by criminals, rose by 49 per cent in 2015 on the previous year. That totalled almost 170,000 cases, according to data collected by Cifas, the financial industry's non-profit fraud advisory service. The reason for the rise is that more and more we use the internet for financial transactions, but have very few ways to verify our identity without cumbersome systems involving human interaction, which are also vulnerable to fraud. Cifas' 2015 Fraudscape report shows that 86 per cent of identity fraud happened online, with bank accounts and credit or debit cards most targeted, closely followed by loans and communications, typically mobile phone accounts. Traditionally, companies dealing with such problems have acted after the fact, trying to unravel complex or opportunistic frauds by working back through audit trails.