Managers working in finance and UK-resident banks or investment companies should always seek an optimal approach to customers, processes and data. Embracing AI technologies can help here. This is why the AI maturity of UK banks and other financial institutions is in the spotlight. Let’s see what benefits these institutions get by implementing and scaling AI.
What exactly does the AI do? AI finds dependencies and patterns that serve as the foundation for information related to marketing, customer retention, business processes, and operations. Using AI algorithms and big data, fintechs can personalize their services. For example, banks are developing unique apps that can create offers tailored to customer needs, taking into account their location, age, spending habits and preferences. According to the State of the Connected Customer report prepared by SalesForce, 66% of customers expect such an approach, where companies clearly understand their needs.
At the same time, customer needs are becoming increasingly diverse. The evolution of technological capabilities, including the analysis of transcripts for mood prediction, allows fintech companies to find the appropriate solutions. In the future, fintech companies will respond to customer wishes and create even more data-driven solutions using high-quality data and complex AI models.
This transformation must be aligned with business objectives and restrictions. According to the BoE and FCA AI Public-Private Forum report published in February 2022, financial firms should consider AI from a governance, data and model risk perspective. By taking all of these perspectives into account, they can adopt AI in a much smoother way, ensuring the provision of new opportunities for customer engagement, risk management, chatbot application, and more. We will examine these opportunities in the following sections.
Anti-fraud tactics help fintech companies create safe experiences for their customers. With AI, financial services become safer because algorithms can identify abnormal behavior and prevent fraud. Let’s see what we mean by banking fraud.
The most common types of fraud are unauthorized transactions, phishing scams and identity theft. Fraudsters use these approaches to steal money. Statista reveals that by 2027, the total value of fraudulent transactions made with payment cards could reach $38.5 billion. Thus, to protect customers, fintech companies must use sophisticated AI methodologies, namely:
- Create customer profiles. Understanding typical customer behavior via Machine Learning, categorizing the profile and predicting future behavior – all this helps to identify suspicious transactions and request further confirmation.
- Implement fraud score assessment. Based on the transactions processed and a dozen other factors such as transaction time, IP address, amount of money, etc., an algorithm analyzes the risk of fraud; after that, the transaction can be approved, rejected, or forwarded for further review.
- Fraud investigation. ML assesses transactions, allowing teams to simplify time-consuming investigations.
- Additional verification. With AI, banks can apply identity verification, introduce facial recognition or verify fingerprints to perform any financial transaction.
When it comes to risk management, banks can use AI models to predict borrower behavior. It should be noted that the application of AI in this field must be clear and explainable. We can look at the model that uses Shapley values and was created to know credit scores and make relevant assumptions about borrowers. The Bank of England mentions that Explainable AI here foresees the ability of a stakeholder to understand the crucial drivers of a model-based decision. Otherwise, the AI request may be considered discriminatory.
The adoption of a chatbot or virtual assistant is a vivid example of AI-powered fintech innovations. Thanks to the latest technological advancements, amazing applications have appeared. Let’s explore a few.
Cleo is a personal financial assistant that aims to encourage people to save money. The London-based company’s product has become popular with users under 35 who want to track their spending and save money automatically. The ML-powered app targets Gen Z and includes various features, namely different savings styles, a credit coach, and salary tips.
Kasisto is an AI chatbot for the finance department. It may be suitable for businesses working in industries such as retail or wealth management. Kasisto can be seen as a digital customer engagement booster. The platform enables institutions to evaluate conversational data and train models to improve user experience. However, Kasisto is not unique. Similar chatbots are Tars, Haptik, Hybridchat, Core, and even Paypal (yes, this company also has an AI-powered chatbot that works through Facebook Messenger).
Nova is a tool that predicts bills, expenses and the achievement of financial goals. With its help, users can manage their balance, avoid impulse purchases, and contribute to their financial well-being through informed planning. Nova also offers a plan for companies that want to motivate their staff and help them with their financial planning.
To stay competitive in the market and meet the needs of their customers, fintech companies, which work in the fields of banking, payments, investments, insurance, blockchain and cryptocurrencies, are actively using the AI and ML. The precision and convenience of these solutions allow well-known British companies to benefit from them.
Tradeteq has been operating as a tool for banks and institutional investors since 2016. The product was created to implement automation to reduce transaction costs in corporate credit and trade finance. This approach also allows financial institutions to find new investment opportunities and increase business financing.
Monzo & Revolut
Monzo is a digital bank that has already implemented AI capabilities in customer service. The internal system not only helps customers find relevant answers to their questions, but also helps customer service agents choose relevant answers to queries. Monzo has over 2.5 million customers in the UK.
As for Revolut, this fintech company with a global money app uses AI technology to prevent card fraud. An ML system analyzes customer behavior to detect anomalies and prevent suspicious transactions.
The London-based fintech company named Zilch launched a beta version of its product almost three years ago. It allows customers from anywhere Mastercard is accepted to buy from Zilch’s partners using six-week interest-free payments. Zilch has become popular with Gen Z and Millennials.
Between 2016 and 2020, UK-based fintechs received $111 billion in investments across 1,380 venture capital, private equity and M&A deals, according to Global City. Significant investment and AI capabilities seem like a very attractive future. Even more scalable products and fintech startups will appear in the coming years as this industry attracts both bold ideas and stable funding.
As a result, employees and customers of financial services will be able to work and cooperate more productively. Also, in this race for high-level Fintech ecosystems, London will certainly be able to retain one of the first places.
By Maksim Bieliai, BA Team Leader and Fintech Market Analyst at MobiDev