AUTOMATION IN FINTECH: A THREAT OR AN OPPORTUNITY?

Peter Tuvey, co-founder of alternative finance provider Fleximize, believes that business is about so much more than just the product or service – it’s about creating personal customer relationships. Here he discusses whether automation in fintech is a threat or an opportunity.

Digital transformation ripples across all areas of the financial system. Each week a new application of artificial intelligence or machine learning hits the headlines – whether it’s AI assistants, investment aids or predictive models. Under significant pressure to shrink costs and improve the volume, speed and quality of customer information, financial services companies are looking towards machine learning to automate key business functions.

Overtime, robots can learn from data patterns and prior decisions to make machine-speed assessments and performcertain operational functions 24 hours a day, seven days a week. With competition increasingly growing in the financial world, automation provides companies with the opportunity to expediate key processes and provide customers with a more efficient service.

This is particularly useful for fintech innovators who can harness thistechnology to offer a growing range of tools and services to consumers and businesses, from mobile payments to crowdfunding and online lending.In the case of alternative business lending, automated credit checks and online applications have replaced lengthy negotiations between clients and bank managers. All it takes is a computer, smartphone or tablet to access a range of funding options at affordable rates.

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However, whilst automation represents ingenuity and advancement in knowledge, machine learning is not a straight replacement for human interaction with clients.When it comes to business lending, a ‘computer-says-no’ algorithm leaves many companies without the chance to negotiate or justify their need for a loan. In the name of mechanized efficiency, businesses are often unfairly rejected, as there is little evaluation of a company’s assets or its real ability to pay off loans.

The issue here is that people will always place a premium on personalisedcustomer experience and expect their specific needs to be catered to.There is also no better way to overcome an issue than by speaking in person –something that is frequently forgotten by tech-driven startups. For precisely this reason, robotic process automation (RPA) is only effectiveif it is usedto free up the time of human advisers who can add a personal touch to the lending process.

At Fleximize, we have created an efficient but relationship-driven approach, utilisingautomated credit-checking softwareto help us produce a fast process from initial application.A significant part of our assessment is still made through online data, such as credit scores and behaviour, but we believe there are better ways to predict a company’s growth. We take the time to understand what businesses are about to try and find a reason to approve them for funding.

Whilst it is undeniable that we are heading towards a world where an exponential growth in data and advances in machine learning will transform the finance industry for good, therewill always be roles that only humans can perform because of emotional and cognitive requirements.The fintechindustry now needs to find an equilibrium between automation and manual practices sothat one compliments the other. As much as fintech is concerned with data, finance and algorithms, the end user is still very much a person in need of conversation, empathy and advice. Any credible organisation should be amalgamating the two for the good of its customer.

Suffolk-based entrepreneur Peter Tuvey is making waves as an alternative finance provider by disrupting the status quo to ensure that more small and startup businesses have access to a suite of truly flexible funding options, tailored to their own unique needs, rather than being faced with a computer screen that simply says ‘no’. To date, Fleximize has lent over £60 million to SMEs all over the UK and in 2017, saw a massive 132% increase in total capital lent.

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