An interview with Dr Mark Goldspink is CEO of The ai Corporation.
Financial IT: To kick this off, could you please tell us more about the ai Corporation and your background?
Mark Goldspink: The ai Corporation was founded in 1998, and has a long and exciting heritage as one of the world’s leading companies in fraud management. In 2016, ai purchased a payment gateway and now also offers all its solutions via a state of the art managed service offering.
For over 20 years, ai has provided solutions to some of the world’s largest financial institutions, international merchants and other major payment service providers. Today, our fraud detection solutions, including our new ‘state of the art’ neural /machine learning technology, protect and enrich payments experiences for more than 100 banks, over 3 million multi-channel merchants and over 300 million consumer cardholders.
I have worked in payments for over 17 years. I spent 5 years at Retail Decisions as Managing Director, and then as Vice President for CGI Inc, working on some very large payment outsourcing opportunities including winning and managing large payment contracts worth over $500m.
In 2013, I was lucky enough to start working with Ashley Head (who is highly recognised as a payment entrepreneur) on rejuvenating The ai Corporation. I am now extremely fortunate to be working with a highly performing and ambitious team, who are driven to re-engineer the current fraud and payment processes, using machine learning technologies.
Financial IT: How has the financial services industry changed since The ai Corporation started off in 1998?
Mark: We didn’t start The ai Corporation, but we saw the opportunity to evolve the business from a product based business, into a world class service organisation. Put simply, “our why” is to allow our clients to take control by developing common sense/practical payment solutions. To this end, we have long believed that data driven decisions are the only way to truly understand our customers. The days of “gut feel” subjectivity, are being replaced by data drive objectivity- and rightly so.
Nowhere more is this true than in the fraud prevention world – inevitably as businesses move more and more real-time, offer full omni-channel capability and accepts more payment types, new solutions are required.
The main change that I’ve seen is that cybercrime and fraud have become a global problem. The team at ai have over 200 years of management experience of fighting providing fraud preventions solutions around the world. At ai our omni-channel solutions have been evolved from working with financial institutions and merchants globally.
Outstanding service has also become non-negotiable and rightfully so. It is on this basis that the ai team focus on service and constantly look at ways we can service our customers better, via a programme we call ‘Total Service Transparency’. Which is a clear team strategy that is based on creating a culture on happy people and the values associated with that vision. There are two main items we have worked on to pursue Total Service Transparency, namely: developing a clear framework that the team members understand and operate confidently within; and creating a zero-ambiguity environment, which empowers people to feel at ease when working with customers.
Financial IT: What makes The ai Corporation special compared to other providers and what are the solutions that you bring to the market?
Mark: For a start, we are truly global. Many new start-ups are domestic and not international – fraud is global and our omni-channel solutions have been evolved from working with financial institutions and merchants globally.
Much of the ‘competition’ are product only companies and not service based businesses. They certainly don’t run gateways and issuing. As I said, we understand our customers pain points.
We eat what we cook too and we believe it is important to truly understand the pain points of our customers. To ensure we live by this approach, our research and development activities are proven on our payment processing and issuing platform. This means that when it comes to release our products, they are operationally fit for purpose – unlike many of our competitors we don’t carry out research and development on our customers, we carry it out on ourselves.
At ai, we create unique payment solutions that include our new “state of the art” neural / machine-learning technology. We believe that humans should spend more time on complex decisions if machines take care of the rest and our solutions are designed with that premise in mind. Our self-service fraud detection rules engine is now considered by industry ‘thought leaders’ to be best in the world.
Our ‘best of breed’ payment solutions are designed to help our clients grow profitably. Our team of experts cover the full spectrum of risk management and business analytics across the globe. These innovative, easy-to-use self-service/self-learning solutions have been deigned to help provide our customers with greater controls. By doing this, we constantly strive to help our business partners create superior returns on their investments by using our solutions.
Our new outcome based service model is the culmination of many months of hard work, statistical calculations and focused live service from our alert management team. We are able to offer the new service because we are so confident in our man and machine learning technology; that after the initial base cost, we won’t ask our clients for a penny more until we have achieved the promised performance – and that goes for all our clients who sign up to the new service.
We wouldn’t be able to offer this service without our team of experts and the way they have integrated our machine learning tools into their day to day operations. ai’s success is based on our clients being successful and this service exemplifies how committed we are to performing and becoming a trusted partner within our client’s businesses. It also clearly focusses our research and development activities, because under a service-based model, it is in our best interests to develop practical and operationally sound products.
Financial IT: What are the trends you are mostly excited about and what do you foresee next for the industry?
Mark: I’d like to see businesses in the FinTech sector taking a more common-sense approach. What I mean by this, is to remove organisation silos and to take a more holistic view across a business. We are very fortunate that many of our clients see the value in this approach and use our state of the art decision engines for more than just fraud and our quick to deploy cloud based payment solutions.
The first principals for running a business are profitable growth. At ai, we believe the objective of our business partnerships is to help our customers drive profitable growth. Doesn’t a common-sense approach suggest providing payment solutions that automate repetitive tedious activities and allow customers the controls they need to work on more proactive business opportunities?
Business history is littered with senior management subjectivity taking an organisation in the wrong direction creating new business activities that destroys profitable growth or worst still, destroys an organisation entirely. On the assumption that “data driven decisions facilitate profitable growth” activities are seen as primary drivers for running a business. Our common-sense approach is augmenting these activities into a single approach to create even greater enterprise value.
Financial IT: How does The ai Corporation harness innovation to address these challenges and trends?
Mark: Today, our fraud detection solutions, including our new ‘state of the art’ neural / machine learning technology, protect and enrich payments experiences for more than 100 banks, over 3 million multi-channel merchants and over 300 million consumer cardholders.
Over the past 4 years, we have moved from being a product only business to a service based business – lumpy to smooth revenues. We have also expanded our range of solutions not only vertically within the fraud domain but horizontally across the payment landscape. The reason for making all of these changes was very simple – to create greater business resilience.
This new unique end-to-end offering has been constructed to target a gap in the market place and is constructed around the following technology and business principles:
- State of the art business rules technology– allow customers to take control
- Flexible and agile so new customer features could be deployed quickly
- No CAPEX with “pay as you go” business model (controllable OPEX)
Financial IT: Going forward what are the major plans you have for The ai Corporation?
Mark: We have very ambitious plans to grow the business, both organically and through acquisitions, to help fulfil our strategic vision. At the same time and, as stated above, we are looking to expand our industry leading team globally. The greatest expansion will be in our commercial teams, as we look to exploit our new products and help more businesses across the globe.
Financial IT: What is your message for the larger players in the Finance industry?
Mark: Proactively managing data by adopting simple to use and practical A.I. (Machine Learning). ML is already here and it will be central to organisations taking digitalisation to a new, exciting level by increasing personalisation and driving deeper relationships between brands and their customers. Ensuring they are accessible across all channels has become key and artificial intelligence is helping organisations boost accessibility and their bottom line.
The finance industry needs to embrace the latest technology by working with more agile entrepreneurial providers. Take A.I. the growing focus on customer experience means businesses now have no choice but to continuously improve their customer journey. A.I. is central to brands taking digitalisation to a new, exciting level. Ensuring they are accessible across all channels has become key and artificial intelligence is helping organisations boost accessibility and their bottom line.
Even the data collected by fraud platforms is being used for more than just identifying fraud. The data from fraud platforms can be utilised in many ways, for ‘good’, as well as ‘bad’. For example, in analysing spending patterns amongst customer data and helping marketing teams to develop targeted marketing campaigns. Purchasing data can also help a brand identify customer segments and establish target markets for advertising.
There are many factors driving the requirements for effective A.I. solutions for payments and transaction processing. As technology evolves, online fraud is becoming more prevalent and damaging, with financial services and e-commerce companies especially vulnerable to attacks.
Modern fraudsters have evolved their ability to detect vulnerabilities in systems and are shifting their targets to those weak links. They are using new tactics too –distributed networks, big data and the dark web to locate vulnerabilities and maximise the associated risk. Fraudsters are also devising multidimensional tactics that inflict damage by sequentially compromising more than one point of vulnerability.
A.I., more specifically machine learning, is already helping organisations combat fraud in ways that just weren’t previously possible. It is an exciting time for businesses, with disruptive opportunities in virtually every market sector.
Organisations that want to defend themselves against these risks and thwart modern fraud attacks must be able to react in real-time. To do this, they need powerful solutions that are responsive and dynamic, yet still easy to use and integrate into their existing systems.
Traditional rules-based fraud management engines are breaking down at this level of sophistication, speed and scale. What is needed is a paradigm shift in the tools used to fight multichannel commerce and banking fraud. A.I. solutions can replace high-maintenance, rules-based fraud management tools with self-learning algorithms, reducing ‘false positives’ by using big data to identify new fraud patterns. Ultimately, these capabilities enable managers to make better decisions related to fraud, and so significantly reduce fraud loss.
After graduating from London University with a PhD In Chemistry, Mark worked for a multinational oil company Texaco for 12 years mainly involved in forecourt retailing.
In 2000 Mark moved to an Internet Billing company and in 2005 became Managing Director for Retail Decision’s Global Payments and Fraud Division. In 2010, he moved to Logica (bought by CGI Inc. 2012) and was Vice President responsible for managing Shell’s outsourced payment contracts worth over $0.5bn. He joined ai in 2013 to work with Ashley Head on developing and expanding a whole series of inter-related payment businesses globally.
 Machine Learning (ML) is one example of A.I. It is a statistical and data driven approach to creating AI, for example, when a computer program learns from data to improve its performance in completing a task. ML starts off by making lots of mistakes, the machine then learns from these mistakes and improves its performance on future tasks. Learning from historical data in this way is the most successful approach to generating many different types of A.I.