Last month at Finovate in New York I saw a new type of financial planning system which could put its users at a huge commercial advantage to other advisors. The INSIGHT below outlines why I think this service is so revolutionary and you can watch the demonstration yourself from the video below.
For many years I have been writing about how the convergence of big data, artificial intelligence and enhanced medical data would transform financial planning, so that we are able to give far more insightful guidance to clients and shape far more accurate, personalised recommendations. Imagine being able to predict when, within a couple of years accuracy, a client might suffer a specific serious illness or when they would be likely to suffer a debilitating condition.
It is not an exaggeration to say that such services will transform the very nature of financial advice, life insurance will become far more about enabling preventative behaviour and making provision for incapacity at certain points in life. Equally it will be possible to plan retirement income needs with a greater certainty based on a clearer understanding of personalised mortality.
As a veteran of some 20 or so Finovate events over the last decade the presentation by Robert Kirk, the founder and CEO of Intergen Data was without doubt the most compelling WealthTech pitch I have seen at any of the shows.
What differentiates Intergen from any other financial planning system I’ve ever seen is the way in which it assimilates detailed information on family history and then uses analytics to predict future life events. As part of the process the user populates family medical history from both parents and grandparents to build a likely future health profile.
Kirk included some very personal examples to illustrate this including his grandfather’s Alzheimer’s and the huge financial burden which it put on the family, including providing a long term care facility costing $15,000 a month for four years at a total cost of close to $700,000.
Through the use of the data and analytics the system is designed to enable advisers to attract more customers and be able to have more contextual relationships with them, and in turn find the solutions to the challenges the system has identified in their very personal analysis.
This presentation was the first time I had every heard best interest and suitability raised in a Finovate presentation. If I have one criticism of the Finovate shows it is that too many presenters focus on selling more products, frequently with little or no interest in if they are actually the right solution for the customer. If the conference is going to move more towards services that produce the right consumer outcome that will be a very good thing.
The system actually looks very like traditional financial planning software, but it captures a far more granular level of healthcare information, not just for the clients but also immediate past generations. In addition to the normal fact find type data it will also take into account issues such as ethnicity, where the client lives, both geographically and if it is a rural or urban area, their level of education and subjects studied. There is growing evidence that these factors can have a significant influence on future health and life expectancy.
Health information from grandparents and parents is demonstrably significant in identifying the likelihood of an illness recurring. If neither of them had a disease then basically it would be low, maybe 8% to 11% likelihood of getting that disease if one of them had it. The chance is significantly increased if both of them have had it, it might be anywhere from a 38 to 42% chance. If parents have had a disease the likelihood could be even higher. As one would expect with a system based around big data, frequently information is called via API rather than manually entered.
From the full data the system can then generate a life event prediction planner to show where statistically different events can be expected to take place in the individual’s life. By adding a partner further life events can be identified. This can include when houses might be bought, children might be born. The analysis can also identify the cost of raising children from birth to adulthood. Perhaps most significantly it can identify when particular diseases might occur. Kirk actually provided some very personal insights and identified that using this model the system predicted his wife would get cancer at 45, she was actually diagnosed at 48 and fortunately is now in remission.
The data is designed to grab the client’s attention and facilitate much deeper conversations. I have previously seen a version of the system working over Amazon Alexa where it is far more sophisticated than the typical Amazon skill and gives some real insight into the art of the possible in the future for financial advice.
Combining data driven predictions of future life events with traditional cash flow has enormous potential to enhance the science and accuracy of financial planning and consequently the suitability of the advice given.
I first met Robert Kirk at the Technology Tools for Today Enterprise conference last October and have spoken to him at length about his system and the methodology. Intergen Data is the first time I’ve seen some of the scenarios I have expected for some years based on big data, advanced medical data and artificial intelligence put into practice. I’m convinced the potential of his system to transform financial advice is enormous.
A demo of the InterGen Data system can be viewed at below: