AI in FinTech

FinTech (Financial Technology) is a technology-enabled innovation in the financial sector. This can range from financial transaction management to fraud busting. The staggering increase in FinTech companies appearing in recent years has given consumers personal ways to manage their hard-earned cash in ways that weren’t possible a decade ago. For example, AI-powered chatbots are being utilized by fin-tech companies of all sizes, from customer care representatives to salespeople. 

Indeed, the rise in financial technology has grown substantially in recent years. In fact, traditional banking has taken notice of disruptive FinTech companies and their innovative solutions, by introducing their own technologies that utilize artificial intelligence and robotics to reduce costs and address consumer pain points.

What are the core benefits of artificial intelligence in FinTech?

The convergence between artificial intelligence and FinTech is huge. Improved cognition and social simulation have ensured that artificial intelligence technology has moved from the fringes to the centre of the debate. It is putting the personal touch back into banking – which has been somewhat lost in previous decades in conjunction with the dominance of multinational banks.

Stronger Security 

AI has proven to be such a success in the financial technology sector as it provides a massive boost to security. AI in cyber security today generally comes in the form of chat-bots that convert frequently asked questions (FAQs) into simulated conversations. In addition, they can reset forgotten passwords or grant additional access where necessary.

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However, AI is enabling unique solutions for the FinTech sector. Artificial intelligence can analyze large volumes of data, and through machine learning, it can iteratively improve over time. By being able to discern patterns and suspicious behaviours, artificial intelligence is being used to identify fraudulent activity, suspicious transactions, and generally, provide a boost to processing sensitive financial documentation – all with a reduced likelihood of security risk.

Example: Feedzai

Feedzai claims that their data science software, OpenML Engine, can help data scientists employed by banks to build their own custom fraud detection models using the fraud-specific models already provided in the software.

feedzai banking solutions. Source: feedzai

Enhancing human workers through automation 

Financial technology can be improved significantly with technologies that fall under the AI umbrella, such as machine learning, data analytics, neural networks and more. Indeed, AI is now critical in financial services. It is driving new efficiencies and delivering value in all areas of FinTech. 

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For example, artificial intelligence has the capability to generate expenditure reports far quicker than a human can and with a much lower risk of error. In addition, AI can power technologies to supply human workers with tracking and automating processes, aiding workers with cumbersome takes such as compliance, data entry, fraud and security, with the added benefit of being able to watch and learn and verify events for anomalies.

Improved customer service 

Customer service is one of the most prominent areas of FinTech that has been improved by artificial intelligence. The increasing sophistication of artificial intelligence has resulted in chatbot, virtual helpers  and artificial intelligence interfaces that can reliably interact with customers. The ability to answer basic queries offers massive potential in reducing front office and helpline costs.

Anders Emil Balk-Møller, Danske Bank shares the importance of maintaining quality control while simultaneously implementing robotics

Even still, Natural Language processing is still in its relative infancy. As deep learning algorithms and the ability of AI to understand human language and formulate convincing responses, transactional calls and traditional helplines will become less intrinsic to customer care. Indeed, AI can lead to huge reductions in manual management, as AI can understand and follow workflows with minimal risk of error or duplicated processes.

Example: Kasisto

Kasisto is a conversational AI Platform that offers services for consumer banking, business banking and insurance. Their product can help set financial well-being goals and get spending alerts, break down spending patterns, proactively notify when bills are due or balance is low, offer financial tips and more. 

Like most other systems of its type, KAI has been designed to refer the customer to a live agent if it cannot handle a query or topic, ensuring that human workers are spending more time with customers who require it. 

Example of Kasisto in action. Source: Kasisto

Analytics and insights

In conjunction with quick decision making, AI offers FinTech organizations game-changing insights which are key in a sector that is so heavily reliant on gathering and processing customer data. Not only does this empower FinTech companies, but it empowers their customers as well. Companies that specialize in personal financial management often give customers insight into their own spending based on income, expenditure and spending habits, ultimately providing a new method of personalized financial management.

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Analytics tools and AI would be hugely beneficial for fraud detection and claims management. AI tools can be utilized to monitor behavioural patterns to identify warning signs of fraud. Similarly, claims management can benefit from machine learning being leveraged at the various stages of claim handling, increasing the speed on certain claims to reduce costs and processing time. Over time, with the help of its self-learning abilities, AI systems can adapt to and incorporate undiscovered instances into its detection abilities over time.

Example: Narrative Science offers software called Quill, which it claims can help financial institutions generate narrative reports from structured data, such as sales records, using natural language generation that transforms data into plain-English stories. 

Narrative Science offers an array of financial business intelligence solutions. Source: Narrative Science 

Reliable credit scores

In traditional banking, potential customers are often ignored by traditional financial industry elements. Many FinTech companies are providing a more sensible method of applying for a loan without a credit history for a bank to review. There are services, like Affirm, that utilize artificial intelligence to mine data from potential borrowers to create a glimpse into their creditworthiness create a “soft” credit score. products in the category generally assess client variables such as geo-location, web history, job profiles and social media without touching upon traditional metrics that form a credit rating.

Virtual assistants and chatbots

Artificial intelligence can utilize smart agents that examine individuals on a level that wasn’t available a decade ago. Personalization is becoming increasingly important in the FinTech sector and large and small businesses now have the capacity to deliver a banking experience that is bespoke to the individual. A combination of technologies, including codified knowledge and AI, working together is able to mitigate the steep financial burden of supplying human service to each and every customer.

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In practical terms, FinTech companies are able to supply relevant information and guidance for every individual transaction. In addition, chatbots and virtual assistants are able to reliably undertake a range of internal and external communication. These AI-powered chatbots and assistants have been utilized in many traditional financial institutions, such as American Express and HSBC.

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As labour costs in offshore outsourcing rise, robotics and AI will become an increasingly desirable method of reducing costs, as text-based personal assistants deliver can deliver expertise and human-like interaction without having to increase manpower.

Example: Erica

Erica - Bank of America is one of the latest traditional banking institutions to adopt a chatbot. Source: Bank Of America

Stock and financial predictions  

AI and deep market analysis seem like a natural convergence, but it has only been in the last few years that computational power and fidelity has been able to provide predictions comparable to human experts. Aldous Birchall, Head of Financial Services AI at PwC said: “I would go so far as to say that an asset manager or bank that engages in strategic trading will be seriously competitively compromised within the next five years if they do not learn how to use this technology.”

In fact, Wall Street has fully embraced AI to help gauge market movements. There are technologies available that can evaluate companies i a myriad of variables, such as earnings calls and public press releases to analyse speech patterns, semantics, and word usage. As you might imagine, this can help eliminate human bias. On top of that, the machines are able to assess big data over many decades and factor it into all predictions. 

Regulatory compliance and auditing 

Financial regulations and compliance is every changing. It can be difficult, even for the largest financial institutions, to comply with laws while delivering efficient and timely services. Fortunately, Ai can learn and comply with the laws affecting certain services, such as governing asset management. Overall, this gives companies of all size the ability the meet regulatory standards, significantly reduce the risk of human error and detect spot activity that deviates from the norm.

Example: MindBridge

the MindBridge Ai platform helps financial services companies identify and manage complex market, regulatory, and operational risk. Ideal for banking and capital markets, and more.

MindBridge solutions for compliance. Source: Mindbridge

Looking Ahead 

The FinTech landscape has grown substantially over the last few years, with countless companies and start-ups producing scalable products with artificial intelligence at its centre. Technology is no longer centralized to monolithic databases and transaction engines, as the potential to undertake financial transactions without a traditional banking intermediary.

It’s about empowering customers and employees to work smarter, make better decisions and have the freedom to focus on what matters most. or this reason, these technologies hold great potential in just about every aspect of banking, finance and insurance—from retirement planning to financial management, and even anticipating your spending needs before you do. 

While artificial intelligence is appealing as a tool to cut down on practitioner workload, streamlining protocols and offering innovative approaches to what were once menial tasks – it is accompanied by its share of challenges as it is still in its relative infancy. We will look at this growing sector with eagerness. 

While technology has been a driver of change in the finance industry, it has stopped short of disrupting it entirely. Check out the report below

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