Airborne – a view of data analytics in Australasia

In April this year, Qantas Loyalty, a subsidiary of the airline, took a 51% stake in Taylor Fry, a general insurance actuarial consultancy founded in 1999. 

This came as something of a surprise to many traditional actuarial clients, including insurers and injury management schemes. However, it follows a growing trend with Woolworths, the supermarket giant, taking a 50% stake in Quantium in May 2013. 

Insurance analytics

Insurance is an industry with remarkable complexity; pricing is often opaque to the consumer and these days is often tailored to the individual characteristics of customers. Online quotes have intensified competition.

There has been huge growth in the amount of data available (geographic, meteorological, demographic, telemetric, competitor as well as the traditional claims history) to understand insurance risk and demand.

Increasingly, actuaries have brought their skills to deconstruct this complexity, driving growths in profits and market share through the use of sophisticated pricing models and price elasticity models.

However, models that overfit to spurious trends or ignore the bigger strategic picture can lead to poor results. Without the guiding hand of an experienced and skilled actuary, this can lead to a winner’s curse, rather than a winner’s boon.

The challenge varies across insurance classes. For instance, injury management schemes such as workers’ compensation schemes have huge heterogeneity in injury types and recovery pathways. Better understanding these pathways via analytics allows optimisation of support offered to claimants, leading to a win for both scheme funders and injured customers.

Insurance represented much of the early analytics work at Taylor Fry. Although the core functions of pricing, reserving, claims management have remained the same over time, our actuarial work has also been shaped by technological change and advancements in statistical modelling.

Government and welfare

Many governments have now recognised the power of data and analytics for maximising the effectiveness of finite fiscal resources. Taylor Fry provides an annual actuarial valuation of the New Zealand welfare system, estimating benefit payments that clients are expected to receive over their working age lifetimes. By monitoring how this cost is changing, the effect of policy and operational changes can be measured, enabling better management.

Actuarial skills used in identifying high-risk segments (such as claimants likely to have long return-to-work durations in injury management schemes) can be adapted to target social welfare claimants that are also likely to take a long time to return-to-work. Targeted investments can be developed to improve employment outcomes and thus reduce lifetime cost – giving an improved outcome for both the claimant and the government.

This framework allows governments to measure their return on investment in interventions, thereby demonstrating value for taxpayer money.

Our models for the NZ government build in a large variety of risk factors including region, education and age to show how people’s circumstances affect their pathways through the welfare system. Over the past three years the government has reduced lifetime welfare costs by over 10%, even after allowance for favourable economic performance. Disciplined measurement and implementation has made this investment approach to welfare a powerful demonstration of effective government analytics. Other countries are watching closely, with Australia recently announcing an investment approach to welfare that uses annual actuarial valuations.

Another notable feature of our work is that it is one of our first supercomputing jobs; calculations are spread across a bank of computers and our projections quickly create terabytes of information.

There are many other government activities where increasingly actuaries have been applying data analytics. There is huge potential for actuaries to add value in government sectors such as fraud and compliance, health, justice, housing and education.

Loyalty solutions and airlines

With a new majority shareholder, airline analytics will continue to be a core part of our work. Most of our work is in the loyalty division; Qantas, like many airlines, has a large and profitable frequent flyer program. Taylor Fry’s Analytics services assists Qantas in leverage this program in a number of ways.

We assist Qantas to increase engagement in the frequent flyer program through targeted communication and offers. Analytics can maximise the useful information given to customers while minimising ineffective communication, leading to better engagement and increased sales. As actuaries, we have been applying our skills in predicting insurance customer behaviour for many years, and we have transferred those skills to predict the response of customers to marketing communications.

Qantas is also expanding its range of business services, leveraging the vast amount of information it has on its 10.7 million frequent flyer members. Qantas Loyalty helps its partners to acquire and grow its customer relationships, with a focus on proving the effectiveness of campaigns.

One example of these services is digital advertising. By overlaying analytical insights from the frequent flyer program with behavioural data from the online world, clients can create targeted and effective online ad campaigns to drive sales and brand recognition. Technically this means we now are competitors with companies like Google, which can seem daunting! However, with the right mix of data, measurement and analysis we believe there’s significant value to be created.

Other industries

We have also been involved in some analytics projects in other industries including telecommunications, energy and banking. Again, these industries are characterised by the availability of large amounts of data, which can be analysed using our skills, to assist companies in understanding the long term implications of their decisions, and driving their planning based on those insights.

Recurring themes

While every analytics project is different, there are a number of recurring themes in our analytics work:

• Ensuring our work adds value. This means constantly asking whether a solution will have a positive impact on business, and whether there is a practical implementation of a proposed solution.
• A bias towards understanding long-term implications. Traditional actuarial work often involves projecting over long terms, and this skill is vital in many other contexts.
• It takes time to move into a new industry. Successful modelling depends on a deep understanding of the language, dynamics and challenges of an industry. This also means a lot of research, as well as working with and learning from other experts.
• There is a lot of competition. In Australasia traditional actuarial work is performed by a relatively small number of firms. However in the broader analytics space competitors include economists, technology companies, start-ups, management consultants, software vendors and even a company’s internal analytics team. This involves learning humility – recognising that many other people are doing lots of work, much of it high quality. There are no Appointed Analyst statutory roles!

Source of success

While all success relies on a mix of planning and luck, we think that the following factors have had the strongest contributing to our analytics practice.

Firstly, strong technical skills are needed in data analysis and modelling. In a world where better prediction translates directly into revenue or savings, being able to provide a good technical solution to a problem is paramount. This increasingly requires expertise in statistics and computer coding. It also requires making your IT department your new best friend. Keeping on top of developments in academia can also be rewarding, as best practice continues to develop.

Second is business insight. Many analytics projects have suffered from either ‘solving the wrong problem’ or ‘losing the forest for the trees.’ Best practice analytics goes beyond describing current trends; it must recognise how a model can be used to drive operational change and improvement.

Third is integrity. The actuarial brand is widely respected and the public generally believe that fellows are appropriately skilled and give honest, impartial and objective advice. We are fortunate to have inherited this reputation and recognise the need to maintain it in the advice we give.

The analytics industry is wide and fragmented, and growing; actuaries are only a part of a landscape that is rapidly evolving. However, our experiences suggest that actuaries have a valuable role to play.

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