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Synechron partnered with CapSpecialty to Build Solution for Excess Casualty



Synechron, Inc, a global financial services consulting and technology services provider, and CapSpecialty, a leading provider of specialty insurance for small to mid-sized business in the US, have collaborated to build an excess casualty platform, DragonX. The project focused on the creation of a portal solution powered by emerging, innovative technologies and an InsurTech approach to streamline business processes for brokers and underwriters while empowering them to be agile against competitive startups and Insurtech firms. As an out-of-the-box thinking insurance company, CapSpecialty chose Synechron, a digital consulting firm focused on out-of-the-box thinking technology provider, to develop the solution.

Today, the insurance industry is dominated by legacy institutions relying on outdated systems and technologies, resulting in reliance on many isolated systems, decentralized communication, and unstructured data delivered and processed both manually and electronically. CapSpecialty recognized the operational inefficiencies in this system and sought to improve processes by offering intuitive tools to streamline these processes for their brokers. Synechron’s scope of work included creating a project roadmap and designing the portal.

DragonX, a commercial insurance platform, unifies all of the previously siloed operations into one central location for the key areas that brokers focus on for excess casualty. Additionally, the portal provides specialized tools to more effectively manage data and increase the bottom line. The portal addresses pain points such as midterm endorsements, and affords brokers improved speed, and as a byproduct, improved efficiency. DragonXwas built specifically for brokers with brokers involved in the design from stage one. Synechron and CapSpecialty’s unique approach began with interviewing 20 brokers around the country to uncover the challenges they are facing with current systems and to identify the functionality in an ideal system. Synechron leveraged its design thinking analysis and user experience design expertise to complete end-to-end development of a user-friendly interface and design based on the results of the survey, delivering increased speed and efficiency through the automated platform. This approach helped shape the development and truly arm a traditional carrier with innovative technologies in-house, rather than relying on investments in outside competitive startups for an agile approach.

Adam Sills, Head Professional Liability and Small Commercial P&C at CapSpecialty said, “At CapSpecialty, we are committed to providing tools that will empower our brokers while providing a high-quality experience. Previous legacy systems were not able to perform to the standard we expect, so creating a new, innovative solution was the obvious next step. Synechron was able to pair its insurance-domain expertise and deep technology and digital innovation skills with CapSpecialty’s vision for what a system could deliver. This allowed us to make our revolutionary vision into reality and bring a competitive advantage to brokers.”

Ashish Nangla, Senior Director, Synechron commented, “The insurance industry as a whole has been slow to change historically, but new startups and InsurTechs are driving the need to innovate or be left behind. We are pleased to work with CapSpecialty as it invests in innovative technologies toward a shared vision of revolutionizing business processes that bring digital-first approach directly to brokers to meet the changing needs of business owners, while leveraging emerging technology solutions.”

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With big tech firms making massive redundancies, could we see a tech bubble burst in 2023?




Rhys Merett, Senior Account Director at PHA Group


Following the pandemic, the return from lockdown triggered an influx of capital into scaling tech businesses. This massive cash injection resulted in record-breaking valuations, resulting in an unprecedented boom of companies receiving unicorn status. In 2021, there were 85 new tech unicorns created in Europe in 2021 with the UK leading the charge with 41 recently created tech unicorns during that time. To give you an even better understanding of how impressive Europe’s tech unicorn boom was in 2021, the growth rate in 2021 outpaced the rate of other overseas markets by a whopping 100%.

But all good things must come to an end and sadly, this shrap spike in tech unicorns springing into existence proved to be a short-lived phenomenon. By the time 2022 rolled around, the party was over. We started to witness sharp company valuations decline – drastically. For example, Klarna, the Swedish fintech company that started the ‘buy-now-pay-later’ fad, saw its valuation slashed by 85% in 2022.  This decline in valuations directly corresponded with UK technology investment dropping by 22%, which was one of the steepest falls in Europe. Overall, UK tech investment fell by $27.9bn in 2022.

Rhys Merrett

The rise of layoffs

With tech unicorns suffering crippling devaluations and trying to stay afloat in an recession-battered economy, we have begun to see unprecedented job losses as a consequence. First, we had Amazon axing 18,000 jobs early this year, then we had Google cut 12,000 jobs and Microsoft followed suit with 10,000 job redundancies.  

Naturally, employees at tech companies are getting itchy feet. More than half of UK tech employees (53%) are bracing themselves for layoffs according to a survey from CWJobs who interviewed 2,000 UK-based tech workers.

So how reliable are tech company valuations in this day and age?

With impending layoffs and declining investment into tech companies, a question now hangs over whether valuations for tech companies are even worth acknowledging by investors. In such a sketchy economic environment, investors are naturally treading carefully when it comes to investing in promising tech companies.

Gone are the days of fancy brochures or grand pronouncements from tech entrepreneurs about how their tech company is ‘disruptive’ or  a ‘game changer.’ Proof is in the pudding and investors are looking very closely at the pudding.

As a result of the above, investors now have a preference for backing companies that are actually generating revenue and, most importantly, an actual profit. To protect their money, investors are no longer buying into the hype. Profits over promises.

It is no coincidence then that, already in 2023, the UK government has pulled the plug on Tech Nation, a flagship initiative launched by David Cameron, to support investment in UK technology start-ups and bring talent to the UK.  Signalling its weariness in putting too much faith in tech valuations, the government has put the tech investment fund in the hands of Barclays – an indication that the government is no longer taking risks with tech companies, especially during a time where government spending needs to be more justified than ever before .

With private and public investors being more scrupulous in selecting which tech companies to pour their money into, tech startups need to assess and redefine their brand position, ensuring there is a workable and sustainable work model which they can prove to potential financiers.

So, could we see another tech bubble burst? It is not totally out of the question but it would be confined to specific sectors in the tech space that are more volatile in nature, such as the metaverse and cryptocurrency. However, tech startups who understand that the days of hype and grandstanding are over and only sound business models are what will attract investors, will  stand a stronger chance of avoiding any tech bubble burst and receiving the investment they need.

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Defining Fraud in 2023




Scott Buchanan, Chief Marketing Officer at Forter

Fraudsters are fluid — they constantly experiment with new tactics to find cracks in a merchant’s defenses. In 2023, there are five trends that merchants need to be aware of — we saw each in 2022 and expect to see them with even more frequency in the year ahead.

Human ‘Bot’ Farms

First, let us acknowledge that while “human bots” is an oxymoron, it is also highly insensitive. At present, our industry lacks a better way of describing the practice. It used to be that human ‘bot’ farms referred to sweatshop-style arrangements in which poorly paid workers, often in developing countries, spent their days on brute force attacks, solving things like CAPTCHAs.

Now, though, a new twist on this old theme has arisen. In short, human bot farms use trafficked humans to scale their fraud operations. Often, they behave as bots, conducting brute force (and similar) attacks.

Human bots were widely recognised in fraud manager communities as a driving force behind recent repeated attacks, especially during the holiday rush. For example, human bot farms bombarded merchants that offer limited edition merchandise, decreasing the chances that prized products find their way to (and ultimately frustrating) good customers. These same operations also applied several tactics that follow at a scale that overwhelmed some fraud solution providers and their merchant customers.

Low-tech Address Manipulation

In the past year, fraudsters reverted to old tricks to circumnavigate rule-based fraud prevention as we saw an uptick in low-tech address manipulation. Consider a merchant with a rules set that checks a shipping or billing address against a negative list. And let’s say a noted fraudster has an address of 123 Main Street that is on that list. Therefore, any transaction with a shipping or billing address of 123 Main Street will be blocked by rules.

Fraudsters found an easy workaround. They simply write a variation of the address during checkout that evades the rules but can be easily understood by FedEx, UPS, or any other delivery company. For example, 123 Main Street becomes One-two-three Main Street or 123 Maain Street.

This should be simple to identify and block in theory. Still, fraud managers were frustrated that rules-based solutions — even those that applied artificial intelligence to speed rules application — struggled to spot this manipulation. During the Black Friday rush, more than one vendor threw up their hands and admitted they had no way to stop this tactic effectively. And as a result, fraud teams with these solutions had to manually review a growing queue of transactions.


With the growing presence of marketplaces to exchange goods, fraudsters are using triangulation more. Think about this as ‘stolen to order’ (instead of made to order). A fraudster posts a sought-after item for sale on a marketplace; in 2022, some of the most popular items for triangulation were high-end ‘cozy’ blankets, sneakers, gaming systems, and other electronics.

When a consumer buys an item from a fraudster on the marketplace, the fraudster then steals the item from a merchant. They input a shipping address for the marketplace buyer at checkout, which typically evades address verification checks. The marketplace buyer gets their item; the fraudster gets their money; the merchant gets penalised, and the marketplace is entirely unaware.

Fraudsters prefer triangulation because they don’t make any effort until they have a buyer — they never have to worry about stealing something they can’t sell, and they never have to touch the merchandise (further reducing their operating costs).


Emboldened cheaters are attempting more brazen tactics. A prime example of that is double-dipping — while this is not new, we did see more attempts (especially from amateurs and previously good consumers) to double-dip in 2022.

Double dipping can take any form where a bad actor wins twice. For example, the bad actor makes a purchase and has the product shipped. They tell the merchant the item was not received and simultaneously file a chargeback with their issuer. Since it may take hours or days for the issuer to inform the merchant of the refund request, the communication gap can mean the bad actor receives money back from both entities and keeps the product.

We’ve also heard examples of bad actors buying and receiving an item, then filing a return, yet failing to return the item. Instead, they send the merchant back a package with rocks (or something else weighted). In one particularly devious example, a bad actor filled a bag with dry ice, which evaded a weight check by the delivery company, and then arrived at the merchant as an empty package.

Friendly Fraud

The best-known form of friendly fraud is chargeback fraud when a customer makes a purchase and receives it but files a fraud chargeback claiming that the purchase was made by a fraudster. This form of friendly fraud has been growing dramatically in recent years. Less recognised is that other forms of friendly fraud — which can also be labeled policy abuse — are increasingly serious.

For example, a consumer buys a sweater as a final sale. When it arrives at their doorstep, they realise it doesn’t fit as they’d hoped. Disappointed, the (previously good) consumer contacts the merchant to claim the sweater never arrived (code = Item Not Received) and demands a refund. The consumer now has the item they can wear (hey, at least the fit is close) or resell on a marketplace for profit.

Friendly fraud can also surface as returns abuse (returning items worn or outside of store policies), promotions abuse (re-using new customer discounts or other voucher codes), and more.

Friendly fraud is difficult to stop since it is often perpetrated by good consumers — they don’t appear on negative lists or fail basic rules. But professional fraudsters get in on the same acts, industrialising the consumer problem by increasing its scale and professionalism significantly. To increase their odds of success, they have gotten pretty systematic about this form of fraud. For example, on the dark web, fraudsters have shared the exact language to use when calling specific large merchants or issuers to nearly guarantee a refund or chargeback.

Parting Thought: The Power of Identity

The above tactics that fraudsters used with some success in the past year generally exploit gaps in rules-based systems (deployed by the merchant and/or offered by a fraud solution provider). These tactics don’t work when you can pinpoint the identity behind an interaction.

When you can be statistically confident that the identity entering an address of “One-two-three main street” is associated with fraud, it doesn’t matter what they enter in the address field; their transaction attempt is blocked. When a known fraudster is attempting to put an item up for sale on a marketplace or purchase an item with a net new shipping address, you stop them. And when they try to re-use promotional codes repeatedly, you reject the attempt.

You cannot pinpoint an identity with rules — instead, you need a massive graph of online identities and as much data as possible on each. While fraudsters always manipulate aspects of their identities, they cannot mask thousands of data points. Next-generation fraud solutions that use machine learning to augment human expertise can pattern match and pinpoint identity.

And to build the largest identity graph, you need a consortium of the largest merchants — collectively, they will ‘know’ the vast majority of online identities. And in this model, an identity — a bad actor or a good customer — known to one merchant is immediately known to all merchants.

And that is why the final trend for 2023 will be merchants abandoning rules-based systems at an increasing rate. That includes the rules-based fraud solution providers masquerading as machine learning (but really just speed up the application of rules). To combat more sophisticated fraudsters, merchants will make decisions based on identity. They will seek out the largest identity graph in order to achieve superior results.

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