I firmly believe that over the next 10-15 years the insurance industry will be transformed through the use of advanced technologies such as artificial intelligence and blockchain. This will be coupled with access to incredible amounts of data collected through real-time sensors connected to our homes, cars and bodies, as well as commercial assets such as trains, bridges, buildings. And let’s not forget transaction and behavioural data from all of the technology services we interact with such as banking, taxis, retail. The potential insurance products and services these will enable are as yet unknown, suffice to say that they will be much more tailored to meet the individual needs of customers, as well as more closely reflecting the risks presented by that individual customer.
The current insurance sector is a long way off this vision, although the essential building blocks are underway with various degrees of urgency and commitment across the sector. For example, real-time data and algorithms are providing 24/7 pricing in competitive markets such as car insurance; telematics in cars are beginning to provide real-time data to car insurers and breakdown services, allowing policies and pricing to be adjusted for actual usage, driving behaviour, or automatically activating claims processes following an accident; smart contracts on the blockchain are being piloted to dramatically simplify claims management. Each of these examples provides a glimpse of the future, yet we are very much at the early stages of the transformation of the industry, and like it or not, in order to survive insurance companies will need to become technology and data companies that specialise in insurance, rather than insurance companies that use a bit of technology and data.
Of course it is not quite so straightforward, as technology and data simply create a capability, but by themselves deliver no value. Value is created by the business delivering unique value to the customer. To achieve this insurance companies must be totally customer-centric, using technology and data (both proprietary and public) to generate real insights into understanding customers and more closely offering what they need. And it goes without saying that all of this must be done efficiently to ensure a level of profitability.
How to navigate all of this
This level of industry transformation is unprecedented, and requires a transformation of the business model and culture, as much as in the adoption of technology and data. No mean feat, not helped by the fact that the three main strategic challenges of customer-centricity, using technology and data to create differentiated products to meet the needs of targeted customer groups, and continuing to reduce operating costs through automation and process improvement, are inter-twined and mutually dependent. This drives the necessity to tackle these changes as part of a holistic, prioritised and joined-up change agenda.
Some firms will be undertaking large programmes of work whereas others will be focusing on smaller incremental goals. Whichever approach fits, there is a necessity to be proactively moving into a more technology enabled and digital operating model, shifting the processes, skills and culture of the firm to align to the emerging demands of the market. The industry may still be in the early stages of a major transformation, but it is now moving fast enough that firms will be left behind if they have not learnt to adapt.
Managing technology and digital transformation
Like it or not, technology and data will be at the heart of any transformation. Rather than list the pitfalls, here are a few tips for success.
Define and brand the transformation on the business outcome rather than the technology label – e.g. Artificial Intelligence Programme, even the more common Digital Transformation Programme – change is driven by a business need, and beware the technology driven initiative.
Break the transformation down into deliverable chunks that create value, reduce the risk of implementation, and allow the business change to keep pace with the technology.
Over-estimate the complexity and criticality of the data elements. In many businesses this is breaking new ground, and the current state of the data, along with the operational changes required to embed new processes to ensure future data quality and capture, often requires more work than anticipated. This can quickly breach the project critical path leading to delays and additional costs. Bring in expertise early and transparently manage stakeholder expectations throughout. Data issues often include fully understanding data definitions and make-up, data compatibility and integrity, data pathways and behaviour after it has been ingested onto the new platform, and complexity of integrations across multiple systems.
Stick to the essential scope required to deliver the core business value. This is a particularly tough ask, as there is huge temptation and pressure from the technology vendors to embrace all of the exciting functionality. However, all too often it is the ‘small’ additions that become the critical failure points.
Understand the dependencies across the full technology stack, from infrastructure through applications, mobile and data. Much new technology is now on the cloud and being offered by vendors as IaaS, or SaaS, or PaaS. These may be new arrangements for the business, that need to be integrated into the technology eco-system, with resultant changes in the roles and skills within IT, as well as the performance monitoring and network resilience protocols.
Pay attention to the quality and robustness of governance and oversight by the executive, business owners and the overall programme. This is standard stuff although it is all too easy to let the quality of governance fall under pressure. We need the leaders of the business to fully understand the risks, and be ready to take the prioritisation and trade-off decisions when they inevitably come.
Technology, digital and data are all at the very heart of the industry transformation that has started, albeit in the early stage. Every insurance business will have to embrace the implications – greater reliance on technology, proliferation of data and data analytics, new skills, processes and governance, and in some cases wholesale changes to the operating model and culture.
For the incumbent firms in the market, they need to be proactively engaging in the revolution, otherwise they may well get left too far behind by their competitors as well as tech-enabled newcomers.
This article is the second in a series looking at Transformation in the Insurance Sector. You can read the first article here: Transformation in the Insurance Sector - a glimpse at the scale of the challengePosted over 3 years ago