Technological Thoughts by Jerome Kehrli

I spoke to to Rudolf Falat, founder of the Voice of FinTech podcast about leveraging AI in anti-fraud prevention and cybersecurity.

The Podcast is available here and can be listened to directly from hereunder:

Happy listening !

The full transcript is available hereunder

(Article initially published on NetGuardians' blog)

Whenever our software is run head-to-head in a pitch situation against that of our rivals, we always come out top. We always find more fraud with a lower number of alerts. For some, this is a surprise – after all, we are one of the youngest companies in our field and one of the smallest. To us, it is no surprise. It is testament to our superior analytics.

A focus on customer behavior

We began working in fraud prevention in 2013 and quickly realized the futility of rules engines in this endless game of cat-and-mouse with the fraudsters. The criminals will always tweak and reinvent their scams; those trying to stop the fraud with rules engines will always be left desperately working as fast as possible to identify and incorporate the latest scams into their surveillance. Far better to focus on what we know changes very little – customer behavior.

If a bank knows how a customer spends money, it can spot when something is awry by looking for anomalies in transaction data. However meticulous the fraudster is at trying to hide, every fraudulent transaction will have anomalous characteristics. People’s lives are constantly changing – they buy from new suppliers, they move house, go on holiday and their children grow up – all of which will affect their spending and transaction data. Every change will throw up false alerts that will undermine the customer experience unless you train your models correctly.

The three pillars of 3D AI

We train our models using what we call our 3D AI approach. This enables them to assess the risk associated with any transaction with extraordinary accuracy, even if it involves new behavior by the customer. This also keeps false alerts to the minimum.

Developed by us at NetGuardians, this approach has three pillars, each of which uses artificial intelligence (AI) to constantly update and hone the models.

The pillars are: anomaly detection, fraud-recognition training analytics and adaptive feedback. Together, they give our software a very real advantage by not only spotting fraud and helping banks stop fraudulent payments before any money has left the account, but also by minimizing friction and giving the best possible customer experience. This is what differentiates our software in head-to-head pitches.

Yesterday we were amazed by the first smartphones. Today they have almost become an extension of ourselves.
People are now used to be connected all the time, with highly efficient devices on highly responsive services, everywhere and for every possible need.

This is a new industrial revolution - the digitization . and it forces corporations to transform their business models to meet customers on these new channels.

Banks worldwide are on the first line in this regards and for many years now they have well understood the urgency in proclaiming digitization as a key objective.
From a user perspective, the digitization confers enormous benefits in the form of ease, speed and multiple means of access and a paradigm shift in engagement. Since banking as a whole benefits from going digital, it is only a matter of time before operations turn completely digital.

The journey to digital transformation requires both strategy investments as well as tactical adjustments in orienting operations for the digital road ahead.
Fortunately, if technology can be perceived as a challenge, it is also a formidable opportunity.
And in this regards, Artificial Intelligence is a category on its own.

The world of fraud prevention in banking institutions has always been largely based on rules.
Bankers and their engineers were integrating rules engines on the banking information system to prevent or detect most common fraud patterns.
And for quite a long time, this was sufficient.

But today we are experiencing a change of society, a new industrial revolution.
Today, following the first iPhone and the later mobile internet explosion, people are interconnected all the time, everywhere and for all kind of use.
This is the digital era and the digitization of means and behaviours forces corporations to transform their business model.

As a consequence, banking institutions are going massively online and digital first. Both the bank users and customers have evolved their behaviours with the new means offered by the digital era.
And the problem is:
How do you want to protect your customer's assets with rules at a time when, for instance, people connect to their swiss ebanking platform from New York to pay for a holiday house rental in Morocco? How would you want to define rules to detect frauds when there are almost as many different behaviours as there are customers?

The digitalization with its changes of means and behaviours and the induced society and industrial evolution is putting increasingly more pressure on banks.
Just as if regulatory pressure and financial crisis weren't enough, banking institutions have realized that they need to transform the way they run their business to attract new customers and retain their existing ones.
I detailed already this very topic in a former article on this blog: The Digitalization - Challenge and opportunities for financial institutions.

In this regards, Artificial Intelligence provides tremendous opportunities and very interesting initiatives start to emerge in the big banking institutions.

In this article I intend to present these three ways along with a few examples and detail what we do at NetGuardians in this regards.

This is a collection of three videos I recorded for the "empowerment fundation" as part of their file on Artificial Intelligence.

In parallel and in addition to BeCurious, the Empowerment Foundation launches in 2018 a project of curation files thematic through the bee² program.

Taking up the practice of curating video content, bee² means: exploring the issues that build our world, expand the perspectives of analysis, stimulate awareness to enable everyone to act in a more enlightened and responsible way facing tomorrow's challenges.
It's about bringing out specific issues and allowing everyone to easily discover videos the most relevant, validated by experts, on the given topic without having to browse many sources of information.

The three videos I contributed to are (in french, sorry):

• AI and Cybersecurity: Preventing Bank Fraud
• How does the Google self driving car work ?
• What are the limits of AI?

The three videos can be viewed directly on this very page below.

In this article, I intend to present my company's - NetGuardians - approach when it comes to deploying Artificial Intelligence techniques towards better fraud detection and prevention.
This article is inspired from various presentations I gave on the topic in various occasions that synthesize our experience in regards to how these technologies were initially triggering a lot of skepticism and condescension and how it turns our that they are now really mandatory to efficiently prevent fraud in financial institutions, due to the rise of fraud costs, the maturity of cybercriminals and the complexity of attacks.

Here financial fraud is considered at the broad scale, both internal fraud, when employees divert funds from their employer and external fraud in all its forms, from sophisticated network penetration schemes to credit card theft.
I don't have the pretension to present an absolute or global overview. Instead, I would want to present things from the perspective of NetGuardians, from our own experience in regards to the problems encountered by our customers and the how Artificial Intelligence helped us solve these problems.