AI and the data revolution are transforming every sector of the economy beyond recognition and finance is no exception. The ability of AI programmes to plough through vast data sets, quickly spotting patterns and trends which it would take a human weeks or months to find, have a huge range of potential applications.
So, how is this technology being applied in fintech and what can fintech leaders do to stay ahead of the AI curve?
The new oil
The idea that data is the new oil has become something of a cliche in recent years but there’s some truth to it nonetheless. While there is not yet any agreed means of assessing the value of data to an organisation, there is agreement that it does have value and - in any information economy - that value will continue to grow.
For fintech then, data is key. Whether its customer data, transaction data or patterns of monthly spending, increasing numbers of fintech businesses are applying data science and AI to find niches in the market. These are niches which traditional financial institutions may have avoided for reasons of scale. Nimble data focused fintech start-ups however can develop products tailored to an increasingly broad array of customers, using data to develop risk profiles, make predictions about customer behaviour and develop products adapted to these profiles. All of which is driven by AI.
While human intelligence remains crucial to many business functions in the finance and fintech sectors, AI opens up areas of analysis which are beyond its reach. Consider credit risk profiling for example. Developing customer risk profiles requires analysis of a vast array of data ranging from transaction history, employment history and income to factors such as age and location of the customer.
While it might take human underwriters weeks to analyse this data, and produce an imperfect judgement, well trained AI programmes can analyse it in minutes. An individual's profile can then be compared to millions of others to help understand the kind of behaviour the customer is likely to exhibit. Other areas too are ripe for automation including claims processing, customer service and contract analysis.
AI powered business
It’s not just in the realm of product development and customer profiling that AI can power emerging fintech businesses, there are other applications too ranging from customer services to compliance.
As we’ve written about here, one of the best applications of machine learning in today’s online business world is a chatbot. A chatbot can respond to customer queries, either by referencing products, sending concerned customers to support articles, or putting them in contact with a human agent.
Chatbots are already widely used in fintech and having an impact. Queries to a chatbot create a data set of keywords and answers. AI powered chatbots will experiment and send different responses to different clients, expanding the data set, and adapting to customer needs.
Machine learning can be used in fintech to comply with state regulation relating to financial transactions and supervision. AI can be trained to track regulatory changes, and make recommendations for action. Regulation is constantly changing, and a machine learning system can help update fintech systems efficiently.
Any fintech company has a lot of data to work with. From visits on a website, to conversions in the Analytics dashboard, to the financial metrics of the company. It’s a reality of fintech - data is king, and any means to gather it, and analyse better, is extremely valuable.
That’s exactly what machine learning can do. There are a lot of SaaS companies selling data mining and analysis software, but your business can take it a step further. You can create your own software, your own crawler, to mine the data you have - financial or otherwise. The same software can also study your data sets and draw complex conclusion that would otherwise not be available after human analysis.
Data and AI are the engines of the information economy, and the opportunities for fintech to capitalise on their digital first platforms and business models as the fintech economy grows are immense. To succeed, recognising the value of data is key, and harnessing the data within your organisation, and protecting that data with the same care as would be applied to any other asset, will ensure future success.