Announcing: Paydock + Bleckwen AI – An AI/ML fraud engine you can bank on

We’re ecstatic to announce our partnership with Bleckwen AI as part of the continuation of our vision to ensure merchants are maximising acceptance while minimising fraud.


If as a merchant, you are not currently optimising your fraud strategy you are likely leaving significant profit on the table. It’s time to put that  money back in your bank account.
– Rob Lincolne, Founder @ Paydock


Bleckwen is an award-winning Behavioural Analytics software company, dedicated to help Banks and Financial Institutions to defeat fraud and make a safer world. They take state-of-the-art technologies, applied research, quality engineering and passion to deliver great solutions.

Matching this with Paydock’s agnostic and accessible  infrastructure, means merchants and charities can rapidly ‘step up’ and adopt leading tools and services without having to undergo disruptive internal change.

We have overnight removed the requirement for you to wait for your gateway to update their fraud infrastructure, removed the requirement for a 12 month internal payments transformation project, and eliminated the need for you to to create an internal fraud division to be ‘best-practice’.

PayDock’s agnostic payment rail is specifically designed to enable you to rapidly capitalise on and adopt best-of-breed solutions such as Bleckwen and ensure you are always ahead of the curve and capturing previously lost profit within your overall payments system.


“We’re excited to partner with PayDock as this allows us to combine our expertise and technology to out-smart the bad guys and better protect consumers. Our purpose is to Create a Safer Societe and our relationship with Paydock delivers a cost effective, fast, frictionless and more secure service for merchants.”
– David McLaren, VP Sales EMEA at Bleckwen

A major and fast-growing problem

Card-not-present (CNP) fraud is set to tear a USD $130bn  hole out of the e-commerce and digital market between 2019 and 2023 [1]. Efforts to combat the growing problem are expected to exceed USD $9.6bn in 2018 alone. This is a big deal.

Beyond the 33% CNP fraud increase from 2015 to 2016 [2]  false positives stripped a further $331bn out of the retail market in 2018 [3], itself a significant increase from 2016. So it’s not just a simple case of locking out the fraudsters, many legitimate purchasers have their customer experience disrupted or stopped completely due to efforts to address this growing threat.

A false positive is an expensive problem alongside the legitimate blocking activites – and it’s all expensive and costing the merchant, even if they don’t realise what they’re ‘not getting’.

Old approaches give way to sophisticated solutions

Older ‘rules based’ fraud services simply no longer have the firepower to combat fraud as needed [4] however the rise of AI (artificial intelligence) and ML (machine learning) technologies have provided a number of exciting tools necessary to combat this rise.

The ability to stop fraud in real-time rather than ‘after the fact’ is a gamechanger. AI/ML can analyse transactional information immediately as and when transactions take place and enable assessments that ensure false positives are kept to a minimum while contemporary and nuanced information is incorporated in runtime for results in less than a second.


Inflexible rule-based fraud solutions deliver too many false positives, locking out genuine buyers or causing obstacles in their shopping journey. Unsurprisingly, this makes them rethink their purchase decision. In contrast, machine learning continuously monitors buyer data based on identity and behavior, resulting in a highly accurate fraud score. [5]


AI and ML is the future. As the fraudsters come to grips with these tools it’s also up to providers like PayDock as well as merchants to make sure they are well protected and consistently ahead of malicious operators in the market.

See our announcement (and why we’re excited)


[1] Digital card-not-present fraud to hit $130B by 2023 –

[2] Card-Not-Present FraudIs Skyrocketing. –

[3] False Positives: The Unintended Consequences of Mitigating Card-Not-Present Fraud. –

[4] Rise of the learning machines: How AI is becoming the newest weapon in the fraud fight. –

[5] Rules vs Scores: keeping fraud simple with Machine Learning –

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