How to connect new technologies with strategy

Channels: SAA/ALM, Systems/data

Companies: MetLife, IBM, Microsoft, Techstars

People: Greg Baxter

MetLife's chief digital officer Greg Baxter talks to Paul Walsh about which technologies are his top priorities, how such technologies can be applied to asset liability management in a Solvency II environment and what investments the firm is making in the digital economy.

Insurance Asset Risk (IAR): Which specific technologies are you spending most of your time and resources on and why?

Greg Baxter: In this world there are so many technologies that are bubbling through , so the focus is really how you connect it to the clarity of our purpose and strategy.

The capabilities that we're focused on in order to be relevant in a digital-era are in four areas: digital automation, digital distribution, data analytics and innovation.

In digital automation robotic technologies is a big area for us, in digital distribution it's about customer platforms, with data analytics it's about the data science architecture and in innovation there is a lot of artificial intelligence (AI).

The key focuses is to build core customer platforms and open architectures so we've deployed global sales and service platforms across most of our markets. This has been rolled out globally allowing us to manage customers and collect data in a consistent way.

We're now starting to touch on some of the new distribution technologies and also connecting into newer customer platforms. For example, things like our 'WeChat' in China where the majority of customers use the messaging tools for all interactions.

In the US, we're testing 'Alexa' and Facebook messenger as another way of providing status and service updates

In terms of AI, we've broken this into two areas one being perceptive technology and the other cognitive technologies. The former type are those that replicate humans' ability to see, hear and feel things and digitise those external signals. We've deployed natural language interactive voice response systems to handle the majority of our calls in the US.

Taking this forward to the cognitive technologies that's when you start to make decisions and judgements based on human reasoning and this is a lot more complex. We're using an emotional intelligence technology that monitors the tone and emotive context of a conversation prompting how to handle or adjust their communication style. We've been using this in our disability claims space which is a very sensitive and high pressure areas.

Another key area is robotics as you think given cloud, open source API, the operational platform of a company will end up being as efficient and as compressed as the technology side of companies. Robotics plays a key role in that, and we've deployed 175 robots with the majority in our back-office and we're testing in less predictable areas.

Lastly, there is this explosion of data, so putting in new processes to manage that data and connecting that data to outcomes and start to find real insights is critical.

IAR: How can technology be applied to asset liability management, especially in the Solvency II environment?

Greg Baxter, chief digital officer, MetLife Baxter: On the investment side of things for example we've invested in real estate for many years, and as a result we've got historical data over property pricing etc and we've got a phenomenally rich amount of data there but combine this with the amount of publically available data and you start to get very interesting insight.

Once you connect this data to real outcomes which companies like MetLife have, you can start to see correlations and predicative correlations between that data and the underlying asset value.

There's a larger number of things you have to do under Solvency II and that ability to take different perspectives on the underlying data is critical.

The data model we're building now has a raw data zone which collects all of the core data into a big data environment. It then allows us to do levels of abstractive reporting and curation of that data depending on what it is needed for. Whether this is for a regulatory requirement under Solvency II or whether it's to look at how we drive persistency for customers, we're using the same underlying data.

There's two data sets, internal and external that we can start to connect and see the predictive impact of external scenarios, so our risk management becomes far more in tune to what's happening externally.

IAR: Is your organisation looking at making investments in the digital economy? Are these strategic investments or with a view to generating decent returns?

Baxter: Last year we launched MetLife digital ventures, a strategically aligned $100m investment fund. First and foremost, it's around identifying capabilities that could transform our company and bring new forms of value and that's the first criteria, the financial return is something we hope to see and will manage towards but first and foremost is the capability and we would hope that would lead to a financial return.

IAR: Are you expecting existing vendors to lead innovation or are you looking to newer start-ups?

Baxter: Fundamentally, innovation needs to be a core competence of every company as you can't do everything yourself. You need external orientation, but you need to build internal capabilities to not only innovate internally but to take great ideas and run them through into a scaled environment.

We have strategic partnerships with vendors such as IBM and Microsoft to build up new platforms. At the same time we're partnering with a number of universities such as Carnegie Mellon, UNC and recently the MIT Media Lab. In many ways these have brilliant ideas and we have ideas on how to apply them so it's about merging the start-up world and existing vendors.

We've launched the MetLife Digital Accelerator programme, initially in partnership with Techstars, which brings a number of start-ups into our lab. We work with them to drive ideas into viable products that could help us. The best of these ideas would come into the MetLife Digital Accelerator Programme where we would look to test them with the hope of turning them into viable products.