Insurers & Financial Services: should you embrace AI?


Alexandra Bigland AI, Technology, artificialintelligence...

A revolution is underway in the insurance and financial services industries – the AI (Artificial Intelligence) revolution. And much like its predecessor “The Industrial Revolution” there is plenty of hype, concerns about robots taking over, and a desire to throw a clog or spanner into the works.

AI is not just one thing

First of all AI is a catch-all phrase for some very different things. At its basic level it’s a way to automate and speed up back office processes in claims, underwriting and compliance. At the next level, it’s about crunching the big numbers, all that data that can help financial services get closer to the customer and tailor their services. The scary bit – that chat bots and robo-advisers might eventually tell us how to manage our assets and financial wealth.

A recent PwC survey shows that 54% of insurers are using machine algorithms to inform decisions. Its reach is considerably less in banking – 34%, and by the time we get to asset and wealth management, AI is currently used to inform only 26% of business decisions.

Possibly one of the biggest perceived threats posed by AI is that it will take jobs from the financial services sector, already under threat from disruptive “fintech” and the aftermath of global recession.

There is truth in every rumour. Undoubtedly many formerly human tasks can be done by machines, certainly in the case of flagging fraud or compliance reviews, defining underwriting algorithms or ensuring accurate financial reporting. But, and it’s a big but, that actually frees up the industry to do what it does best.

The machines can tell you how to get closer to the customer, how to map out the customer journey into a “type” that other machines can take the customer through, but ultimately creating innovative services and products will be firmly in the human domain.

New business ecosystems

As Mike Mihaylov at Venquis points out in his article in Global Finance and Banking, while car manufacturing, the biggest industry a few decades ago, employed millions, today’s top players – Google, Facebook and Apple retain only thousands of professionals directly. However they rely on an enormous interconnected ecosystem of start ups, bespoke players and geographical experts to underpin their market dominance and expansion. So the jobs are just appearing elsewhere.

He uses by example the market for creating social media synced mobile apps, which today is already larger than the entire global movie industry, to indicate the sheer scope of the tech sector and the jobs it has created.

People must lead the AI revolution

Perhaps the greatest mistake the financial services industry can make is to plan and adopt AI without doing their homework on their people.

Resistance to change from employees is probably the single biggest reason that IT transformation fails. Success of any technical change depends most heavily on its adoption by the people who must use it or work with it.

A major European oil and gas company set up live two-way video conferencing to allow its off-site engineering team to see and experience issues as they happened on the rig, without having to physically be there. Although a logical step, the initial adoption failed, because on-site engineers felt it was a “big brother” move by head office, and started accidentally putting their hard-hats over the cameras or switching the system off. The transformation was rational, but the people responded emotionally.

A telecoms giant encountered a similar “rebellion” when it installed GPS tracking in its engineer vans. Designed to improve fuel consumption, increase productivity and get engineers out to emergencies quickly, it was received badly as a way of cutting overtime (which it did quite considerably) and spying on engineers.

The main reason both technology transformations failed: lack of communication with the people involved in adopting the new technology, and a failure to note the human element of the change.

Finding the right transformation specialist

Today, a transformation specialist needs more than just the tech skills of a developer, designer or coder. They must be able to win the hearts and minds of different people to ensure effective adoption of technology, and recognise that small factors can make a huge difference to the change process. By understanding the impact of seemingly tiny changes, and incorporating them into a project’s risk, they can make sure that a company’s investment reaps a return.

Finding financial services transformation specialists is hard enough, and finding an agile thinker who understands business and IT but is also a skilled leader and communicator is even harder. Companies who have one will be doing all they can to hold on to them.

If you’re struggling to find the right team to support your adoption of AI, talk to Venquis. Technology changes like AI are here to stay. To make them work for you, you need the right team to ensure they successfully transform your business.