How insurers can achieve greater data fluency for a digital era – Mphasis

To succeed in today’s digitally driven environment, insurance firms need a higher level of data fluency and analytics.

Data is emerging as a source of strategic advantage for identifying unserved or underserved markets, creating new and profitable business models, managing risk better, optimising channel performance, enhancing services and improving the customer experience.

Solving the intractable data problem

Typically, insurers have used data to monitor their past performance. However, they can tap into significant growth opportunities once they start focusing on using data as a fundamental asset that can optimise critical business decisions.

There are several roadblocks to gaining value from data.

First, many companies are hindered by legacy IT infrastructures, with suboptimal, inconsistent or inaccessible and siloed data.

Additionally, much of the industry still runs on physical documents and insurers must find ways to digitalise this information at source to get a full view of the customer and proactively recommend more tailored solutions.

Successful data implementation projects rely on two critical competencies:

• DataOps, the data engineering capability that can make the management of large and complex datasets more efficient, reliable and scalable.
• Data science, which can extract insights and knowledge from data to translate it into actionable insights that can drive transformative outcomes in real-time.

Utilising a ‘front to back’ model

Achieving value from data doesn’t need to involve a disruptive, bulky or cost intensive overhaul.

Instead, firms can employ a ‘front to back’ data strategy, phasing out legacy technology and introducing innovation in a self-funding model.

One of the first steps of this process is to identify the minimum data required to address priority customer needs and specific business problems, integrate this data to deliver immediate value and continue to build on it iteratively.

Insurers can use not only their internal customer data for this, but also richer sets of external data that are readily available - advancements in the fields of artificial intelligence and machine learning can enable greater access to datasets through open finance too.

This smarter approach to data will grow more prevalent and become crucial to retain a competitive edge. The market has already seen how Tesla, for instance, is planning to move into insurance precisely because it has access to vast datasets and is looking to leverage that to provide a better and more personalised insurance product to Tesla owners.

This data transformation is happening across the insurance market but not fast enough.

Particularly in the current climate, it is vital for insurers and brokers to know their customers so that they do not risk underserving them.

Data used to be an afterthought, but more businesses are now discussing how to put data front and centre and really start making use of it as the tremendous business asset that it is.