BNP Paribas Global Head of AI and Digital Risk Analytics Adri Purkayastha talks to us about how COVID-19 is accelerating the firm’s digital transformation and the future of risk analytics
You’ve been at BNP Paribas for roughly 18 months. What would you say are the main differences between working for an in-house data science function and the kind of consultancy work you previously did?
At Deloitte, I led greenfield product and service offerings, using AI and ML around data-value chain and business-transformation levers to support senior management from multiple industries.
I was fortunate to have the opportunity to found and stabilize interesting AI-SaaS solutions and help build a cloud-native commercial banking proposition. (It was very sector agnostic in experience but cutting edge!)
At BNP Paribas, my focus has been to set up an AI and data science function for the group to help in the areas of technology, digital and information risk. I have been able to get deep into the operating model and strategic initiatives of the bank.
Hence my experience is now firm-specific. That said, it’s still fairly broad, as BNP Paribas operates in almost every area of finance.
What were your main responsibilities when you first joined BNP Paribas as its Global Head of Cyber and Risk Analytics?
The main objective was to build the group technology risk analytics function from ground-up, developing its strategy, delivering data science applications for cyber risk management and building out intelligent apps in the cloud. This really is a team sport. So, as a team we have achieved a great deal. We work in all areas of technology, cyber and data risks.
For instance, we have collaborated on applying data science in cyber threat intelligence, insider risk, cloud risk, data privacy and operational resilience (among other domains) to build a holistic and scalable approach towards data-driven risk management.
You recently became BNP Paribas’ Global Head of AI and Digital Risk Analytics. What’s the scope of this new role? And what do you hope to achieve over the next 12-24 months?
In essence, the focus is on bringing a collective vision around AI and data science across BNP Paribas group and building a business-driven playbook to achieve a competitive advantage using data.
Hence, we will partner with senior management, data protection officers, risk managers, machine learning experts, data scientists, software developers and engineers and cybersecurity and IT risk managers to evangelize about shifting AI risk management to the left.
The ambition is to develop, champion and build an enterprise-wide understanding of AI/ML opportunities and risks, and to establish an end-to-end AI governance and operating model throughout the entire lifecycle. I would like to look back on our journey as one where we have incorporated AI into our digital operating model with ethics and trust at the core.
Of course, COVID-19 has transformed the global business environment. What impact has it had on demand for AI and analytics at BNP Paribas, and the work that you’re doing?
The pandemic has forced almost all companies wherever they are in their digital transformation journey into expediting that process. For us, we are focussed on continuing digital transformation to enhance the customer experience, offer new services and serve new customers.
AI and analytics are common denominators to our growth levers across building adaptive information systems, upgrading the digital operational model, implementing intelligent customer journeys, empowering digital-working ecosystem and making better use of data to serve our clients.
So, these technologies are very important to our mission to better manage business risks and capitalize on opportunities.
Putting the global pandemic to one side, what are the other key challenges you’re facing, when it comes to planning, developing, implementing and monitoring AI products?
There are opportunities and challenges in various dimensions, such as availability of good quality data and talent across the entire ecosystem.
I like to approach technology as an ecosystem with multiple moving parts. One key aspect of securing strategic and tactical wins with AI is aligning business strategy, risk appetite and internal controls to buttress investment in a resilient AI or ML ecosystem. We are building our foundation across algorithmic integrity, fairness, resilience and explainability.
What do you think will be the greatest advances in the field of digital risk analytics over the next 12 months?
Digital risk analytics is the core ingredient of digital risk management and transformation. With increasing incorporation of emerging digital technologies into society – in far-reaching areas ranging from multiomics to smart manufacturing – we will see a flywheel effect from data.
I am excited about using analytics in the areas of privacy and data security, AI systems management and cloud operations. Digital risk is moving vector and nebulous, depending on when and who you ask. But the key principle is to use analytics for business risks arising from digital technologies. That playbook is being written now.