How Intelligent Automation Changes the Game for FinTechs

Cloud computing and the advantages it presents is certainly no secret in the financial services sector; it is estimated that 94% of workloads in 2021 will be processed by cloud data centres. Within this, adoption from FinTechs, whether it be challenger banks, digital wallets, or contactless payments, will be almost total. Most FinTech organisations (particularly B2B) adopted three key principles on this basis: Be Cloud, Be Agile, and Be Microservices, and set out to conquer the minds and experiences of the digital consumer.

With familiar names such as AWS and Microsoft Azure leading cloud vendor services with a 32% and 20% market share respectively, the services offered by the platforms have increased exponentially since their inception. This rapid technology innovation and widespread adoption has been a significant contributor to the rise of FinTech: it offered a cost-efficient service to support the speed necessary to get to market and facilitate funding.

One aspect of cloud technology benefitting from innovation is that of intelligent automation. With the market for automation technologies expecting to reach a total value of US$6.1 bn by 2027, an opportunity to drive productivity and efficiency is clearly present for early adopters.

FinTechs are taking advantage of cloud technologies to accelerate growth and scalability and are leveraging intelligent automation to drive revenue, let’s see how…

Fraud Detection & Prevention

With artificial intelligence (AI) and machine learning (ML) spearheading FinTech into a new age of automation, fraud detection and prevention methods grow more sophisticated. Organisations, in particular incumbent banks and new digital banks, are turning to Robotic Process Automation (RPA) to manage their fraud detection processes. This typically involves training an AI to identify unusual activity, such as abnormal transaction values or geographical locations. This does however require a lot of data to be effective; more data used to train the model means it will be more effective at identifying patterns and outliers.

This real-time data analysis through automation allows for faster and more accurate data processing. The benefits of this to organisations are clear: legitimate claims can be paid out faster (insurance) and illegitimate transactions can be identified quicker (banking) which in turn leads to happier customers, more security, and reduced costs.

Moving forward, the banking and financial sector should seek to utilise intelligent automation to prepare for new attack vectors. Fraudsters will take advantage of new innovations too, so institutions must be prepared.

Credit Risk

Whilst somewhat slower to adopt the technology than the world of fraud prevention, credit risk is another area of FinTech soon to realise the power of intelligent automation. When a bank or lender seeks to calculate credit risk or an individual’s credit score, this can typically involve both high-skilled specialisms (credit analysis) and low-skilled components (manual data entry). This mixture of systems requires regular human interaction and a long-winded paper trail of unstructured data.

With advanced AI and ML able to replicate significant functions of a trained credit team, there is the potential to automate a lot of these processes, reducing paperwork and increasing speed and consistency. As a result, more sophisticated algorithms and decision paths can be established faster and at lower cost while increasing reliability and customer experience.

The incumbents continue to be less responsive to the market than FinTechs due to having outdated systems and processes in place. However, incumbents benefit from a wealth of customer data which they seek to harness to anticipate future customer needs and provide services accordingly.

A recent example of innovation in credit risk comes from Apple with the announcement of its Apple Card Family, currently only available in the US. Using intelligent automation to track purchases and manage spending, two people can “co-own an Apple Card and share and merge their credit lines while building credit equally”. With plans to roll out globally providing a successful pilot in the US, the challenge will lie with the incumbent banks to follow suit or lose market share to these new innovations, as Apple seeks to provide a people-centric solution to the complicated world of credit.

Looking Forward

The benefits of intelligent automation for FinTechs are clear: AI and ML innovation is a key area of growth with a high return on investment due to faster and more efficient processes and increased customer satisfaction. It is important for organisations to adopt these new automation technologies or be left behind.

At intive, we utilise ready-to-use cloud solutions to push time-to-market for emerging FinTech organisations. For those looking to develop existing architecture, we adopt an agile approach for modern application development, enriched with practical AI and ML methods and algorithms, allowing for the management of risk and compliance at moderate cost.

Take a look at our recent press release demonstrating intive’s deep technical expertise as a long-standing technology partner of Tandem Bank, where we successfully implemented intelligent automation processes for their new revolutionary digital app.



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