I see the future mortgage advice business as one which advises across all the risks associated with taking on debt, much as the investor needs to understand the risks they are being exposed to in the investment markets.
This model will see regular contact between client and adviser. So for me it is only a question of whether the business model will get there ahead of the regulatory requirement.
There will be a changed landscape, but it is full of opportunity for those active in the mortgage market who deliver real value added advice to the end customer. As wealth advisers have discovered post-RDR, delivering advice is the key service valued by clients.
We should also not lose sight of the fact that in recent years the entire adviser community has faced both regulatory and capital issues and yet – against many predictions – has seen off the challenges of banks, direct salesforces and the direct marketing activities of life companies.
This is a truly amazing result and demonstrates the resilience of a profession which is valued and trusted by its clients in the delivery of outstanding customer service.
The threat posed by artificial intelligence
So far, so good, but a spectre has appeared on the horizon which has set its goal to challenge the hegemony of the financial advisory community.
This spectre is spoken of in many guises, including FinTech and robo-advice, but at its core is the use of artificial intelligence (AI) for the delivery of the next generation of financial advice to customers.
Consumers live in a fast-changing technological world, where most use smart phones and tablets - devices not even around a decade ago, and they use them for every aspect of their lives. Just walk down any UK high street and you will see people walking with their heads down checking their screens. The power of these devices to deliver content, information and guidance is just beginning.
Last year Amazon reported a huge surge in sales of voice recognition machines. So where might this take us? With increasing sophistication, voice recognition will be able to take information and translate it into guided information, or advice, if you like.
In the political world, sophisticated pressure groups have scraped the data from Facebook and LinkedIn to help identify likely supporters of a point of view. The use of predictive analysis has helped them to create opinion-forming stories – some of which are actually true!
These same digital analytical processes, using freely available social media sources, are being used to provide automatically completed insurance applications and build customer risk profile models.
