AiThority Interview with Christer Dichiara, Senior VP and General Manager at Experian DataLabs

Hi, please tell us about your role and the team / technology you handle at Experian.

In my role as GM of the North America DataLab, I help lead a multidisciplinary group of data scientists with PhDs and applied research practitioners with expertise in advanced analytics and machine learning, applying cutting-edge data science to real-world business situations. Experian has created a truly inclusive culture, where everyone has an inherent sense of belonging, knowing they are working in an environment where they can be who they are both personally and professionally.

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What is Experian and what are your services? Which industries do you currently serve?

Experian is the world’s leading global information services company. We empower consumers and clients to manage their data with confidence. We help individuals to take financial control and access financial services, businesses to make smarter decisions and thrive, lenders to lend more responsibly and organizations to prevent identity fraud and crime. We have nearly 18,000 people operating across 45 countries, investing in new technologies every day.

Tell us about your recent initiatives in the AI ML and Data Science domains? 

Advanced analytics such as Artificial Intelligence and Machine Learning play an integral role in almost all of our work. We use machines, computational horsepower and algorithms to help us automatically recognize and learn patterns and classifications in the data through supervised and unsupervised learning methods. Our team is committed to being early adapters of any technology that might improve the power of data for our clients.

How is Fintech transforming data science applications for the industry? How do you see the evolution in fintech impacting marketing performances?

I think Fintech has the advantage of starting from a clean slate with respect to data and production infrastructure, software and tools used to maximize use of data and the science applied to extracting valuable information from the data. Of course Fintech also leverages the learnings from traditional financial services providers to help guide where opportunities are, to change and enhance targeting and customer engagement, to streamline the journey and customer treatment, as well as to use alternative data for risk assessment and fraud detection.

What is the Experian DataLabs?

Experian DataLabs is the research and development arm of the company that is continually focused on addressing the disruptive forces within the market that can benefit from the fusion of raw data and machine learning. As the research and development arm of the company, Experian DataLabs is continually addressing the disruptive forces within the market that can benefit from the fusion of raw data and Machine Learning. We help businesses solve strategic marketing and risk-management issues through an advanced data analysis process, research and development. We are focused on innovating new data sources with an emphasis on financial services, telecommunications, and healthcare.

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Why is data so valuable in today’s digital society?

At its essence, data is a representation of occurrences over some time duration, whether the data represents truths or non-truths. A collection of occurrences enables better informed decisions by humans and machines, an element our clients depend on in order to solve problems and discover new opportunities. In our line of work for example, drawing a conclusion from a single data point is an opinion at best. Occurrences of data, or rather patterns in data, enables us to help our clients and consumers make confident and informed decisions. Data allows businesses to provide a better customer journey.

How can a business make sure they are maximizing their data?

The simplest answer is to ensure senior leadership and operating executives realize data and the interpretation of data drives virtually all business functions, and then to make that data available to data science teams, and others as required, to extract and transform that data into material and actionable information.  One of the ways we help clients maximize the use of their data in combination with ours and others is through our Ascend Technology Platform.

Does AI play a role when it comes to data?

Absolutely, AI and Machine Learning are core fields and techniques to extract meaning from data, enable machines to learn and adjust from the data, and ultimately enable machines to reason like humans or perhaps even better.

Can you share some of the interesting projects you are working on in the DataLabs?

We have numerous interesting projects going on right now, but most of our work I’m not able to discuss until it’s brought into the market. However, one project worth mentioning is Experian’s Sure Profile product. Our team built the underlying algorithms for the product/capability to support higher resolution and detection of probable synthetic identity fraud in the financial services space.

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How do you address the shortcomings in the data management and analytics? What kind of tools / platform help to deliver contextual data intelligence to customers?

We use both licensed and open-sourced software for our data management platform and Spark is heavily used for our data process and data analysis tasks. To deliver contextual data intelligence to our clients we use exclusively open-source tools, including but not limited to, scikit-learn, PyTorch and TensorFlow, as well as Proprietary Algorithms developed at Experian DataLabs that are tailored and optimized for our industry needs.

Your predictions on the role of Data Science in Business Operations: 

Data Science is here to stay.  It is key to enabling organizations to be smarter with their data; drive better insights and predictions, efficiently automate across different functions and applications.

Your take on AI ML in marketing technology stack — how do you leverage AI ML for your marketing?

In a world where consumers and households have multiple devices (mobile phones, tablets, laptops, connected TVs, etc) and a future of more connected devices (via IoT and TinyML), it’s imperative to help brands understand their customers across these different modes of interaction and channels to create appropriate and seamless customer journey’s and treatments.  At Experian, we have deployed advanced Machine Learning approaches that unifies multi-dimensional offline and online behaviors in a privacy compliant manner.

Thank you, Christer! That was fun and we hope to see you back on AiThority.com soon.