Skip to main content
The Actuary: The magazine of the Institute and Faculty of Actuaries - return to the homepage Logo of The Actuary website
  • Search
  • Visit The Actuary Magazine on Facebook
  • Visit The Actuary Magazine on LinkedIn
  • Visit @TheActuaryMag on Twitter
Visit the website of the Institute and Faculty of Actuaries Logo of the Institute and Faculty of Actuaries

Main navigation

  • News
  • Features
    • General Features
    • Interviews
    • Students
    • Opinion
  • Topics
  • Knowledge
    • Business Skills
    • Careers
    • Events
    • Predictions by The Actuary
    • Whitepapers
    • Moody's - Climate Risk Insurers series
    • Webinars
    • Podcasts
  • Jobs
  • IFoA
    • CEO Comment
    • IFoA News
    • People & Social News
    • President Comment
  • Archive
Quick links:
  • Home
  • The Actuary Issues
  • August 2014
08
Interviews

The predictive power of data

Open-access content Tuesday 29th July 2014

William Trump and Paul Hately consider what is really achievable by using ‘big data’

2

Predictive analytics is nothing new, and has been playing a role in life insurance for over a decade. Life insurers have tried to emulate what banks and some general insurers were already doing with data. These companies use what they know about customers, such as purchase data, to derive a competitive advantage - for example by pre-approving customers for specific products, or by better targeting certain messages. One example of usage in life insurance is the analysis of banking and life insurance data from bancassurers to find new 'predictors' of health. These are then used to pre-select a group of customers for a targeted offer of life insurance with minimal underwriting.

Today, amid the hype around the 'big data' revolution, it's worth taking a step back, and revisiting the past 10 years to reflect on the lessons already learned about how to use big data to inform underwriting and other business initiatives. 


Start with the end in mind - know what you want to predict 

This may sound obvious, but it is surprising how many people want to be 'doing big data' without having a clear business purpose in mind. They should start by asking "What are we seeking to achieve?". The goal can vary hugely from one market to another: for one insurer, it may be that underwriting simplification is key, whereas another may find that it is retention that's the real pain point.

The reason it's so crucial to define the aim is that it will hugely influence both what data will be needed, and how the analytics will be run. Some examples include:

• reducing the length of the underwriting process for healthy customers - in which case, predictive underwriting methods apply; 

• differentiating on price based on the risk profile of the individual - typically done based on past claims data;

• aiming to achieve higher conversion rates on sales campaigns - where propensity-to-buy modelling or trigger-event marketing can 

be deployed; 

• seeking to improve retention, where we use past data to build a propensity-to-lapse model - either to target better customer prospects at the point of sale, or to target retention efforts within the in-force book. 


Be realistic about limitations

Unfortunately, there are still a lot of wild promises about what is achievable through big data. The real world is far more constrained and some fairly strict criteria apply,particularly when looking for health predictors. The strongest models are those built from scratch, on a bespoke basis. By definition, this means sufficient high-quality past data is needed. 

Bancassurers have invested heavily in getting their data to the point where it is an asset. As a consequence, they are now exceptionally well placed to take advantage of it. Typically, their wealth of past sales data - including underwriting decisions and claims - means that, when matched to banking data, unique insights can be learned by applying statistical techniques to the anonymised data-file. But even with banks, there can be vast data differences, whether it's quantity of data or quality - such as the number of variables available per customer. 


If you're not a bank, it's still worth doing something

Not having perfect data is an easy excuse for not doing anything at all. This is a real mistake, for, as Eric Siegler puts it in his very helpful book, Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die, "a little bit of prediction goes a long way". 

Five years ago, people would ask whether they should be doing this type of analytics, whereas now they are asking how they can do this. This is a good sign.

Even insurers with relatively weak data can - and should - be using it to make some improvement to their processes. The important thing is to ask what can be done - rather than what can't - with what is accessible.

A key question is about how different types of data-sources can be used to predict health, purchase, or lapse. Table 1 shows our analysis.

Data doesn't get you all the way

There is sometimes the tendency for those working in predictive analytics to believe that, given the right data, perfect predictions can be made. Unfortunately, this is not the case. Models make mistakes and customers don't always behave the way they are expected to. There will always be the customer with a low propensity to lapse who cancels their policy. 

Analytics can help improve the process, by removing redundant health questions for healthy customers, for example. However, strong sales methods and messages are still needed. Reliable results can only be expected when good analytics come together with strong sales or retention processes. 

The growing body of evidence emerging from the field of behavioural economics is a helpful reminder that we are not as fully rational as we think we are - and as we claim to be. This should encourage taking a 'test and learn' approach to everything we do. Only then will the true drivers of customer behaviour be determined.


Lots of people talk about it - but few actually do it

It's easy to lose count of the number of industry events where the presenter has spoken about Google and Amazon and what they are doing with their data, but the life insurance industry is still very slow to react in actually making use of the data it has access to. Experience so far has proven that much can be achieved through matching life insurance data with other descriptive data in order to predict health, purchase or lapse. Some insurers have led the way on this, and hopefully many more will follow.

This article appeared in our August 2014 issue of The Actuary .
Click here to view this issue

You may also be interested in...

2

Bowled over

Having been one of the most influential regulators in the European Union, Sharon Bowles speaks to Mark Dowsey about her many achievements and how she believes actuaries can engage in policy debates in Europe
Tuesday 29th July 2014
Open-access content
2

Appliance of science

Oliver Werneyer asks whether actuaries can master the power of new technologies
Friday 1st August 2014
Open-access content
2

Tales of evolution

Lord Robert Winston, world-renowned scientist, emeritus professor of fertility studies at Imperial College London, Labour party peer and popular TV presenter, has a reputation for being provocative in his views. Angus Macdonald and Sharon Maguire meet him to find out why
Wednesday 27th August 2014
Open-access content
2

Backward in coming forward

Non-disclosure of medical conditions by life insurance applicants is nothing new, but what is the true cost of this to the life insurance industry? Paul Morden and Phil Brown explore further
Tuesday 29th July 2014
Open-access content
2

Measure for measure

A number of common misconceptions prevent the optimal use of data, argues Douglas Hubbard
Wednesday 30th July 2014
Open-access content

Hanging in the balance

Suzanne Vaughan reports on the Scottish Independence debate hosted by the Institute and Faculty of Actuaries
Wednesday 6th August 2014
Open-access content

Latest from Position

TPR publishes coronavirus guidance

The Pensions Regulator (TPR) has published guidance to help UK pension trustees, employers and administrators deal with the financial and regulatory risks posed by coronavirus.
Monday 23rd March 2020
Open-access content
2

Expert advice

This edition of the magazine focuses on data science and its applications, which will be a recurring theme for the IFoA.
Friday 28th February 2020
Open-access content
2

Tesla sparks fears of insurance market overhaul

That is according to a new report from Moody's, which highlights how Tesla has already started offering premiums that are up to 30% cheaper than those of mainstream insurers.
Friday 14th February 2020
Open-access content

Latest from Professional

dxf

Bespoke tailoring: the UK government’s proposed reforms to Solvency II

Vrishti Goel discusses the UK government’s proposed reforms to Solvency II
Wednesday 31st August 2022
Open-access content
Financial services seen as most desirable sector for career changers

Financial services seen as most desirable sector for career changers

Over a third of UK workers will look to start a new career in the next year due to the cost-of-living crisis, with financial services seen as the joint most desirable sector, KPMG research suggests.
Wednesday 24th August 2022
Open-access content
web_p43_Student_student_july_2_CREDIT_Simon-Scarsbrook.jpg

Three’s a charm: the next iteration of the internet

Adeetya Tantia explains what we can expect from the next iteration of the internet, and how it could shake up the insurance industry
Wednesday 6th July 2022
Open-access content

Latest from August 2014

Pensions industry sets out 'pot follows member' priorities

The success of the government’s ‘pot follows member’ pension transfer system will depend on efficiencies and long-term cost management across pensions and investment firms, according to a standard-setting body for eCommerce.
Friday 29th August 2014
Open-access content

Regulators secure pensions payments from Lehman Brothers after 2008 collapse

US investment bank Lehman Brothers, which collapsed in 2008 at the peak of the financial crisis, has agreed to pay £184m to nearly 2,500 former employees to end a six-year legal battle with The Pensions Regulator over pension entitlements.
Thursday 28th August 2014
Open-access content

Standard Life urges caution on lump sum pension deals

Employers and trustees have been urged by Standard Life to think twice before using new rules allowing pension savers to access their funds through a lump sum as the default option for schemes.
Thursday 28th August 2014
Open-access content

Latest from Interviews

rdth

Make My Money Matter's Tony Burdon on the practical power of sustainable pensions

Years working in international development showed Tony Burdon, head of Make My Money Matter, that sustainable pensions can harness trillions of pounds to build a better world – at a scale governments and charities can’t. He talks to Travis Elsum
Wednesday 1st March 2023
Open-access content
iugu

Interview: chemist and climate expert Sir David King on how actuaries can save the Arctic

Actuaries can save the Arctic, according to esteemed chemist and climate-change expert Sir David King. He tells Alex Martin that risk management is as relevant to preserving the planet as groundbreaking science
Wednesday 1st February 2023
Open-access content
res

Interview: Tim Harford on the importance of questioning our assumptions

Tim Harford speaks to Ruolin Wang about why it’s so important to slow down and question things from emotive headlines to the numbers and algorithms we use in our work
Wednesday 30th November 2022
Open-access content
Share
  • Twitter
  • Facebook
  • Linked in
  • Mail
  • Print

Latest Jobs

Life Actuarial Contract - Capital Project (outside IR35)

England
Negotiable
Reference
149010

Pricing Consultant (Non-Life)

London / Leeds
Up to £70,000 + Benefits
Reference
148996

Senior Actuary

London (Central)
Negotiable
Reference
148991
See all jobs »
 
 
 
 

Sign up to our newsletter

News, jobs and updates

Sign up

Subscribe to The Actuary

Receive the print edition straight to your door

Subscribe
Spread-iPad-slantB-june.png

Topics

  • Data Science
  • Investment
  • Risk & ERM
  • Pensions
  • Environment
  • Soft skills
  • General Insurance
  • Regulation Standards
  • Health care
  • Technology
  • Reinsurance
  • Global
  • Life insurance
​
FOLLOW US
The Actuary on LinkedIn
@TheActuaryMag on Twitter
Facebook: The Actuary Magazine
CONTACT US
The Actuary
Tel: (+44) 020 7880 6200
​

IFoA

About IFoA
Become an actuary
IFoA Events
About membership

Information

Privacy Policy
Terms & Conditions
Cookie Policy
Think Green

Get in touch

Contact us
Advertise with us
Subscribe to The Actuary Magazine
Contribute

The Actuary Jobs

Actuarial job search
Pensions jobs
General insurance jobs
Solvency II jobs

© 2023 The Actuary. The Actuary is published on behalf of the Institute and Faculty of Actuaries by Redactive Publishing Limited. All rights reserved. Reproduction of any part is not allowed without written permission.

Redactive Media Group Ltd, 71-75 Shelton Street, London WC2H 9JQ