Data-Driven Fintech: Why AI Still Needs a Human Touch

In the age of the internet, is the growth in the collection, analysis and use of data in our everyday lives going too far? I think it may be.

We are seeing everything from elections to crop yields predicted by big data. Reading the newspaper is harder with online advertising directed specifically at you, drawing your eye away from content and many other ways we do not even know is happening.

In the financial world the use of data has only really begun over the last few years. Having spent my career analyzing companies in almost every possible way, my love data is as strong as the next financial nerd. But, what have I learned from looking at data for nearly 20 years? Data doesn’t tell the full story of a business.

Data only tells part of the story of a company

Data shows the hard facts of what went on over a period of time, what was achieved, and how this may affect the future. But there are a number of things it won’t tell you:

1. The story behind a company. Simple things like: how it got started or that quarter that had lumpy sales.

2. How well the management team knows their business. Can the management team answer questions on dynamics within the company, which give insights to why certain data points happened?

3. What are the management and founders’ view of the market they operate in?

4. What are the plans in the short/medium/long terms for the business and how do they plan on getting there?

5. Does the whole picture make sense (including the data)?

The Power of AI

In today’s world of data driven decision making can AI analyse data better than a human? It certainly can analyse far more data than a human ever will and quicker.

AI has the ability to take huge amounts of data—think of every bank transaction for every person in the world for the last ten years—and query this data, analyze trends in this vast data and come to conclusions in a matter of seconds. Of course, this fundamentally depends on the AI tech being built properly.

For humans to do the same amount of work, it could take thousands of hours and a huge amount of people. Humans are also more prone to errors and biases, for example AI can help us remove human bias in lending (in theory).

However, today’s AI can’t speak to a founder of a business, listen to their story, ask them questions, and debate the ins and outs of different issues.

Where We See AI Used Today

The amount of data collected in the financial world is epic. We should be harvesting and using this data to make better decisions. In the world of lending where we at Element SaaS Finance operate, we see a rise in the use of AI to make rapid lending decisions.

In the consumer world, we see Klarna and Affirm, who both offer ways for consumers to buy now and pay later. In the SMB sector we see the likes of Kabbage, who can provide lines of credit and general business loans without you ever speaking to a banker. These are certainly innovators, who have built platforms that can analyse the data very quickly and make lending decisions based on this analysis.

Speed is a great thing for both the borrower and for the lender. The borrower can receive funding without much human interaction and quickly return to growing their business. And the lender gains the ability to provide funding more rapidly and to offer smaller loans that were previously unprofitable for banks to provide.

Lending small amounts of money to a business or consumer needs to be a fairly light touch approach due to the volume of loans needed to make it commercially viable. AI helped banks solve this problem and led to the availability of more lending products in the market, giving borrowers more options.

However, when you start lending larger amounts of money to a business, I certainly believe those who rely on data alone will run aground in some ways.

AI Isn’t Ready for Everything Yet

Data and AI analysis of a company’s financials doesn’t tell the whole story. Conversation with management teams and founders of companies give powerful insights into the reasonings behind what happened and why certain decisions were made. These decisions will have had an impact on the financials and data coming through, but getting context in a conversation is hard to replace.

Humans have an incredible ability to innovate. Much of this relies on human interaction, emotions, gut feelings or the understanding of one's market, which spurs the seeking of new opportunities. The data analyses on selling coffee for $4 a cup back in the 1980’s would have told the operators of Starbucks not to build the business in the way they did.

The Oakland A’s used data analyses to great effect, as seen in the movie Moneyball. However, it was the people that needed to gel to make the cohesive team that went on a 19 game winning streak. Along the way Billy Bean and his team needed to use some human intuition to get there.

So what do I think the future will hold?

Like a lot of things in life, we may go too far, realise the error of our ways, and end up at a point where we use AI as the great tool it can be.

We have seen how technology can positively impact our lives and businesses, but we have also seen how it can take over. Let's embrace the use of AI but not let it take over what humans do best. 

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