Earlier this month, our MD Martin Hill and Head of Insurance and Data Strategy Christian Ingrey headed down to the two-day ‘Artificial Intelligence (AI) in Financial Services’ conference in London.
Accompanied by 100 other senior executives from leading financial institutions, the aim of the event was to produce a concrete, step-by-step guide to implementing AI strategies within the financial services sector.
Key speakers from The Bank of England, TSB, Lloyds Bank, Direct Line and Silicon Valley were a few of the businesses present on the day. They tackled several key themes – using AI and machine learning to draw genuine value from a data strategy, and how to use it to improve efficiencies in your business, generate revenue and cut costs.
Not everyone knows about AI…
Interestingly, not everyone in attendance knew precisely what AI was before the event. From the circa 100 people, only five or six people already had strategies in place! This highlighted how complex this emerging technology really is, and we were excited to find out more about its potential.
So, here are some of our key takeaways from the day…
What you put in…
…determines the level and quality of data driven decision you get in return. If you are going to utilise AI and machine learning and exploit its full potential, it’s important to ensure that all your data sources are clean, to be in with the best chance of achieving the quality outcomes you desire.
Data security is important
As suggested above, cleansing your data will not only produce the best results, but it will also protect the source, and be GDPR compliant to boot. It’s therefore paramount that security – as well as a process to manage it – forms a key part of your own strategies.
A tip to help you with this step, is to outsource training and accreditation to improve your knowledge around security management. For example, here at DealTrak we are gold ISO 27001 accredited, which is the international standard for data security.
There’s more to AI than meets the eye
AI actually an overarching term, which has several parts to it. The very basic level is robotisation which can perform simple tasks, such as a customer service chatbot. This is ideal for a business which offers a 24/7 helpline, meaning all queries are dealt with quickly – in some form.
The easiest way to understand the relationship between the different levels of AI is to imagine them as concentric circles. The idea of AI came first – and is the largest of the circles. Next up is ‘machine learning’, which blossomed later. And finally, driving today’s AI explosion, is ‘deep learning’ – fitting inside both.
Some challenges and worries were highlighted alongside this intelligent technology too. It’s feared by many that AI could take jobs, leading to people losing their place within an organisation. But, it’s important for firms to remember the value of human interaction, which can’t be removed completely from a business.
Instead, AI can be utilised in a way to bolster efficiencies. By freeing up the time of staff members to concentrate on high-value activities, the individuals in the firm can drive the business forward and take it to the next level.
Machines and humans should work together – not replace one another!