See the life. Not just the policy.
We make customer-centric insurance a reality.
Harnessing the power of AI to give you a complete picture of your customers, their lives and their businesses.
SAS analytics decodes customers, so you can treat them as people, not numbers.
It means you can give them the insurance they need. Before they need it.
Hear their voices
Apply machine learning to uncover customers’ true sentiments and preferences, so that staff can give them the support they need, in real time. It means you can get to know your customers better, respond faster, and give them a better service.
What it means in practice:
A recent call-centre pilot revealed there was an up to 20% deviation between the real call reasons versus what’s reported. Natural language processing can be used to predict and classify call reasons to ensure that customer feedback isn’t mistranslated, and they aren’t kept waiting or given the wrong help.
We work with RBS to analyse 250,000 web chat conversations and millions of lines of text per month. It’s led to improved agent performance and ultimately, to higher customer satisfaction (based on survey scores).
Make it personal
Use AI to better inform the millions of decisions made across your enterprise, so that you can provide a personalised, consistent customer experience.
What it means in practice:
A global insurer improved decision making at FNOL, cutting the average time to settle a claim from weeks, to seconds. 85% of decisions are now made on day one.
Daiwa Securities use AI to make sure branch and call-centre staff have full understanding of customers. They can predict their needs, and make every interaction personal and worthwhile, reducing customer churn by 50%.
A Dutch life and pensions company use a customer’s profile, product history and previous events to predict ‘the next best question’ to ask. They know why a customer is getting in touch and are on the front foot when it comes to giving them the support they need.
Interamerican build customer trust by giving them online access to their portfolio and a transparent way to amend their personal data preferences. It ensures everything is up-to-date, compliant and as convenient as possible for customers.
Innovate, now
With a single analytics platform for consolidating and interrogating every piece of data, you can go beyond policy and premium to get a real view of customer behaviour. It’s about predicting and understanding customer needs as they evolve, proactively responding to them, and improving the customer experience.
What it means in practice:
When an earthquake that measured 7.1 magnitude struck, Farmers Mutual Group used a single platform for viewing data to find and contact all customers within the affected region. The team could estimate exposure to claims quickly and accurately, helping customers when and where they needed it most.
A global insurer has made tens of millions of pounds in savings by making more accurate decisions. It’s helped with everything from knowing when to write off a vehicle versus when to repair it, to determining settlement value in real time.
Protect against fraud and risk
Harnessing data to predict and prevent events is still an early phenomenon in insurance. It’s one that’ll not only help insurers see the people behind the data, but also take proactive steps to protect those people and their way of life.
What it means in practice:
Protect your customers from criminals (both organised and opportunistic) by proactively detecting and preventing fraud. It reduces losses and subsequent costs for insurers and customers.
Unlock the full potential of analytics by using IoT to combine data from the connected home and car. You can detect events like a rise in pipe pressure to alert and send out a plumber, before damage is done and the house is flooded. This preventative approach will build customer trust and be one of the key differentiators when it comes to the future of the insurance industry.
It’s not all about household data, when it comes to businesses SAS & GE combine to create a new ecosystem that collects and streams data from industrial machinery and transportation. These IoT ecosystems present new opportunities for collaborative risk management for business of all sizes.
SAS Real-Time Decisions in Insurance
Make it happen.
The platform:
Our analytics platform works across all areas, helping you join up data silos to get a full view of the customer. Zenith Insurance now receive and collate the amount of data in a week that used to take an entire year.
It’s designed to capture the right kind of data and perform the right kind of analytics for your business. Siemens Healthliners use machine learning and IoT to analyse urgent data generated by its systems worldwide. It means it can predict system problems and potential downtime several days in advance of a failure.
The easy-to-use dashboard gives you a single view of data, allowing quicker decision making. Ecclesiastical Insurance uses the platform to give managers, risk assessors and underwriters improved data to make better decisions.
The setup:
SAS has over 40 years’ experience working with insurers around the globe, industrialising analytics to get to the real business value.
We work on a case by case basis, assessing how you’re currently using analytics and proposing the most effective approach for your journey to a customer-centric business.
Our business value consultants work with you to quantify the benefits and TCO to ensure your analytics business case stands up.
Our SaaS model means we can deliver our platform to fit your setup and needs – whether it’s being deployed as part of a public or private cloud, on-premise, or as a hybrid solution.
Enable your data scientists to move innovations from the lab to the real world.
SAS Real-Time Decisions in Insurance
Change lives.
Our platform forms a solid foundation for helping you to become a truly customer-centric insurer. It means you can stay ahead of the technological advancements that not only insure lives, but enhance them.
Read our blog series to hear the thoughts of Paul Ridge (Head of Insurance SAS UK&I) on how we can use analytics to change lives in practice:
How insurers can enter the era of customer centricity
The people, the homes and the businesses you protect are all changing. Technological advancements mean we can now command Alexa or Siri to write a shopping list by speaking to a box in the corner of the kitchen. Or talk to the delivery guy waiting on our doorstep from another continent. Although this innovation is visibly changing the way we live, the insights insurers need to adapt to that new way of life are hidden. They’re buried among the volumes of data consumers and businesses create.
Why analytics alone can’t deliver customer-centric insurance
Enterprisewide analytics and AI have the power to prepare insurers for a customer-centric future and transform the relationship with policyholders. But will only a handful realise that their current approach to analytics leaves them poorly prepared for the challenge?