FinTech Connects... with Dr. Henna Karna , Chief Data Officer, AXA XL
Henna is AXA XL’s Chief Data Officer and is responsible for its digital & data evolution & transformation. A recognised expert on digital strategy, data analytics and organic & inorganic transformation, she has more than 20 years of experience leading innovative digital/data strategies in the risk management & insurance industry. Her skills include bleeding-edge innovations, end-to-end transformations, and development of proprietary data-driven risk solutions comprising genetic cognitive learning, behavior modeling, proprietary algorithms and deep neural networks.
As an industry stalwart who has led the digital transformation at this insurance powerhouse, we asked her some of the key questions currently facing financial services.
Firstly can you tell us a little bit about what AXA XL are doing in the fintech space?
Simply said, for us, it is very much about moving us from a transactional firm to a partnership with our customers. Hence not only are we investing in a strategy to evolve the way we leverage our data and analytics, but also ensuring that the insights we can bring to the table are highly differentiated and valued.
How do you see data changing the way financial institutions operate?
My speculations are that there will be further democratisation of data and personal ownership of data. We should expect increased scrutiny and increasing ownership, such that there may be a redistribution of ownership rights to the consumer/ end customer. On the supply side, there is a corresponding democratisation such that the complexity of financial transactions will need to evolve quickly. Reality is that there is a cost to serve, and that may be under pressure from increasing demands from peer to peer lending and transactions. In fact, the structural construct of financial institutions may be under pressure for their cost-to-serve. Their operating costs have to scale down or structure has to change. Due to data sharing, peer-to-peer transactions may become even more prominent with distinct networks that will prevail.
How has your data strategy evolved?
Our data strategy continues to be our customer-first design and the reflective architecture and methodology continues to be calibrated with our business goals and target state plans. Thus far, we have been able to validate a great deal of early hypothesis that we had both inductive and deductively reasoned. Today, we are live and leveraging several deliverables that originated due to the data strategy and see meaningful benefits. One great lesson we continue to embrace is the value of investing in our people and talent as we evolve our capabilities to sustain our data strategy.
Every conference I’ve been to in the past 2-3 years, someone has said the cliché ‘data is the new oil’, what are your thoughts on this statement?
Oil is considered to be the most important commodities of the world. It is a driver of the world economy and a dominant energy source. It’s so central to many things. I suppose it is a cute analogy (although I am not a fan of it). Oil is oil and Data is data. Data has enabled us to quantify things we couldn’t before - but data is not new to many industries. In fact, oil rigs one of the biggest users of IoT data. It’s not as cute but the reality is that Data is blood. Oil is food.
A lot has been discussed around taking AI beyond the hype – where are you currently seeing successful use cases?
It’s early days still. Predicable data sets are starting with robotics automation but the learning pieces are in much earlier stages. There is incredible amount of AI today where we are mapping language and structure. Deep learning, certainly at scale, has just started. The way AI becomes of value is based on scale. And it comes down to data. How do we get the right data for the AI to be trained? There’s no way to plug in to get all the relevant, unbiased data that is correlated to a certain problem solutioning. As it has always been, teaching everything to any one person or thing is a holy grail, isn’t it? Staying a bit dramatic, the AI engine could be a thing called GOD, if only everyone would just focus to train it, and do so objectively. That would be something. But that in itself is a godly, highly complex, task. To say it less controversially, the long pole is not in the ability to develop more and more intelligent AI only. The capacity to develop more intelligent AI is not a known limitation, nor is the storing of the data needed for training. It is more a training and enablement issue that we must solve for.
You are coming to London in December, to deliver a keynote around the core themes of digital transformation. You have led a number of technology transformations through out your career; how much is a digital transformation about the technology and how much is it about culture?
We cannot divorce the two. I suppose a standard answer is technology provides direction and culture drives adoption. There is an intrinsic interdependency between culture and technology. Culture is tied to human experience. It is inseparable from anything we do. It’s tied to who we are, our existential needs. It is core to our fundamentals, and without it we can perish. Technology is a derivative of that. We could argue that everything is a derivative of that.
If we want to operate in a world that is entirely quantifiable with the use of data, which is perhaps a digital transformation end state, technology and culture becomes cyclical. The genesis is Culture, which will drive innovation and innovation will leverage technology and get to the art of the possible. And then culture becomes the adoption mechanism. It’s an exponential function basically.
Financial institution’s seem to be taking a build, buy or partner model to fintech/insurtech – where do you think they should be focusing?
It’s never a 100% answer here. 10/45/45 is a better split, pushing more towards buy and partner. Incumbencies are a problem. They have a presence and some level of control points in the ecosystem and when those control points shift, they are not nimble enough to respond in a timely way.
What do you think the role of the tech giants (GAFA) will be in finance?
They all have investment arms... there is immense investment in tech, and hence Fintech. Googles parent company is “Alpha Bets”. As I understand, tech companies go after a problem and solve it in a fundamental way, without the baggage that incumbents have. It’s very hard to move away from the baggage incumbents have and what capital markets expect you to do is grow.
Which location leads in innovation; are you looking at London, NYC or further afield?
Silicon Valley and Israel. A lot of innovation comes out of Israel. They are leaders in security and hence a lot of data innovation comes out of Israel. SV, San Francisco, the VC spend is orders of magnitude bigger than anywhere else. Other places that are bleeding out are Seattle, London, Ireland, Finland...