From collaborator to revolutionary - the new role of an insurance CDO
My belief is that the insurance industry is at an inflection point regarding how it best uses data. Should more power and control be given to an insurance CDO? Would love to hear your thoughts...
The growth and abundance of data in the industry is causing insurance companies to reimagine how they harness it's power to inform how they operate in the future world. There is an explosion in the volume of data gathered by carriers, brokers and TPAs and an ever increasing variety of data available publicly or through external enrichment. Some of this is powerful, even predictive. Some of it is noise.
This is causing teams to rethink how data is used across operations, analytics functions, risk management and customer servicing to inform strategic innovation in areas such as customer interaction and distribution, hyper-personalization and the customer self-sufficiency as well as underwriting, ratings and fraud which underpin losses and profitability.
It is well understood now that access to data helps insurance firms understand customers in more detail than ever before.. This new level of granularity can help improve their ability to make relevant, insight-driven decisions in real-time from this knowledge. However, what the industry is seeing is that, whilst most insurance companies recognise this opportunity, only a few have been able to successfully execute against it.
What has held the industry back
Data lakes (or swamps) were intended to facilitate data intelligence and insight-driven data analytics. Yet in many cases they are becoming investment drains and are creating new bottlenecks to how decisions are actually made across the value-chain. They are often hard to maintain and mean that data teams spend more time wrangling, governing or migrating data from place to place that actually using it to inform operational and business needs. Or it results in operational teams having to source it from multiple places (meaning slower human decisions) or worse, being swamped by information that therefore gets ignored, resulting in sub-optimal decisions.
Not only that, but any insurer that writes more than one product, distributes via more than one channel or operates across more than one country also has data siloed all over the business. Even if every piece of enterprise data was in one single data lake or PAS (which it never is) , what that gives at best is a simplification on logistics of where data stored. The data, insight and knowledge itself is still disconnected & fragmented.
This leads to a lack of consistency in the way data and analytical modelling is implemented across business units, and across the value-chain. In turn, leading to disjointed operational decisions and processes.
Turning data into knowledge
It is becoming accepted that change is needed. It is not about having data, it is about getting knowledge from the data and then turning that knowledge into decisions which are trusted, transparent and consistent.
A future proofed data estate (mesh, ecosystem etc etc) has to ensure that all data is connected. This has to happen irrespective of whether it is located in one place, or in complete silos across the business. It must create a foundation for knowledge which is connected, can be resolved quickly and is integrated into a variety operational processes and systems. This foundational ensures that operational and analytics team spend more time on data decisioning (whether via an AI/analytics process or a human mind) and less time on data interpretation. This means investments become focussed and can be centred around the thing that matters most - the customer.
The creation of this, Decision Intelligence nirvana creates a means by which any person, process or analytical model can assemble any data and turn that data into knowledge that makes sense for a particular decision at a particular point in time.
For an underwriter that could mean assembling every historical submission, active policy, loss run and claim across all lines of business for a global corporate structure to review risk exposure and offer services which will prevent claim events. For a customer service team team it could mean having a single view of every communication, interaction, complaint and preference that has ever been made by a customer so that a more empathetic and personal touch can be applied. For a claims function it could understanding the highest performing supply chain for particular claims of a particular type in order to resolve the claim with the highest speed and at the lowest cost thus limiting the impact on future renewal prices.
Effectively it comes down being able to derive everything you need to know about each and every Entity you do business with (person, business, location, risk object, digital footprint ++), irrespective of their role (applicant, customer, claimant, employee, supplier ++), at any point of the value-chain to inform faster and more informed decisions.
Those leading the pack are already achieving this through Dynamic Entity Resolution and Entity-powered, Real-world Network Analytics. Those which aren't, have a huge opportunity awaiting them.
The importance of the insurance Chief Data Officer (CDO)
Insurance companies don’t lack data, they lack the means to unlock it. I believe, the knowledge of how to unlock the value lies with a role which, historically, has been under-served and under-powered; the CDO.
When a CDO is given the right investment and right backing, they often hold the mindset, the technical expertise and the practical nous to create value from data in the lowest cost and most future-proofed way that best serves the insurance enterprise as a whole. They understand the value of data utilisation and will maximise the opportunity to build data as a product; capturing once but using repeatedly. Not only that, they are typically able to help with change management and cultural adoption as well.
The insurers that will create the highest degree of competitive advantage are those that invest in a CDO but also back them to invest in technologies that create that Decision Intelligence nirvana. This can ensure you will cater for the undoubted evolution in the shapes, sizes and scope of data of the future to always bring it back to informing decisions around the customers and third-parties you do business with.
A CDO shouldn't be someone who is consulted, they should be accountable for data-revolution.
Now, reflect and think:
Does our CDO really have the power and influence required?
Do we have the technologies at our disposal to connect that unconnected data now and in the future?
Are we using the data to deliver a more trusted, informed and holisitic view of every party/entity I do business with?
And does that view give me the consistency and agility we need to bring step change improvements to operational decisions?
@Issam_Hijazi @Martin_Maisey @Chris Sanders @Shyam_Bhatt @Alan_Haskins @Areefih @Darryl @Marie @Patricia Arenas
@DavidClamp - would be interested in your view on this? :)1
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