By Sochima Thomas Ozougwu

Like every industry, the finance industry has transformed from being largely manual to becoming highly technologically-enabled. Back in the day, businesses would receive only cash for their day-to-day transactions, and individuals would always facilitate payments with cash in their day-to-day activities.

Banks were at the forefront of this practice, as the only way customers could transact was via cash, and this often led to long queues both for customers in the banking hall to make deposits into their accounts, those with the intent to withdraw money from their accounts, as well as those wishing to resolve account-related issues. As you may imagine, complaints regarding account issues were often face-to-face, unlike in today’s era where there are multiple channels for resolving these issues.

Each phase in the transformation journey of the finance industry over time has been enabled by the need to continuously improve across all areas of value delivery, from money transfer, customer service, to fraud detection and prevention, among others. In recent years, fintechs have revolutionized the industry by bringing so much ease to the way customers all over the worldtransact. The speed at which they are onboarded, the speed at which issues are resolved, and the speed and channels through which they can instantly move funds around the world have all been heavily boosted and are making the traditional banks play catch-up. For fintechs, achieving this efficiency means leveraging technology in a timely and efficient manner that helps the business drive better internal processes and helps the customer with all-round efficiency.

As the technological landscape rapidly evolves, artificial intelligence has emerged as a game-changing innovation which has played a transformative role in the finance industry, where fintechs are at the front seat of maximizing the efficiency of AI in diverse, yet strongly competitive business environments; however, there are opportunities which many fintechs are not leveraging to the fullest. These opportunities range from personalized customer experience, improved risk management and fraud prevention, to improved operational efficiency and cost reduction, as well as efficient regulatory compliance. 

Personalized Customer Experience

Fintechs can leverage AI to drive more efficient customer experience from the very moment the customer signs up. It is critical to deploy machine learning algorithms to understand customer interaction on the fintech’s app, their behavior, patterns, preferences, and all other data points critical to providing targeted and personalized solutions, product recommendations and related opportunities (such as savings plan, investment strategies and cost-saving practices to help achieve their goals) to each customer. In addition, the speed at which you can point the user in the right direction when they need information and the speed at which complaints are resolved can be enhanced while also ensuring compliance and account security.

AI-powered virtual assistants and chatbots can now use natural language processing to provide ongoing support, answering all your questions. These chatbots can manage conversations in the most natural and contextual manner, ensuring a smooth and non-repetitive interaction that does not increase customer frustration. These opportunities go beyond providing answers to customer questions but could enable customers to carry out transactions such as making transfers, paying bills, placing a trade, etc., right within the chatbot.  However, fintechs must not lose sight of account security while providing these capabilities through the chatbot. By leveraging AI to provide enhanced customer experience, fintechs build a closer bond with their customers, making them feel that the business is paying attention to their needs; and in that way, your fintech business would be on its way to boosting its revenue.

Improved Risk Management and Fraud Prevention

For fintechs and the finance industry as a whole, the possibility of occurrence of fraud is a major risk which has been around for as long as the industry has; however, AI has provided yet another opportunity to approach fraud detection and prevention from a more systematic and information-driven approach as against the traditional approach which relies on human judgement and time-consuming manual review of historical data which is often plagued by inconsistencies, errors and bias. With machine learning algorithms, data can be captured real-time from several sources andanalyzed, anomalies can be detected, and these patterns can be exploited for decision-making.

The ability of AI to pull all relevant data to build the risk profile of a potential customer before entering into a contractual relationship with the customer is the first level of defense for fintechs.This is not a one-time affair, as financial services companies must always maintain and update their customer risk profile. This data can be anything ranging from customer identity, credit score information, social media activity, transaction history, criminal record, investment history, among others.

Leveraging this data can be highly beneficial, and in the case of ongoing business relationships, AI-enabled continuous transaction monitoring can help flag suspicious transactions, and based on inbuilt compliance practices, as well as fraud patterns, however evolving, fintechs can prevent fraud before it occurs. Through a nonstop practice of transaction monitoring and ongoing maintenance of customers’ risk profile, critical timely decisions can be made, while the business is safeguarded from potential loss, and the possibilities of fraud and money laundering, greatly reduced.

Efficient Regulatory Compliance

Holding people’s money or facilitating payment means control and regulations by state actors; hence, fintechs are required to comply with certain regulations depending on location. AI algorithms can research through large knowledge bases of regulatory requirements, capture and streamline them into actionable compliance practices. Having documented these requirements, AI tools can automate various elements of regulatory reporting, retrieve relevant data from business systems and other tools, thereby enabling the business to push scheduled or on-demand reports to regulators.

By tapping into AI for compliance, the end-to-end compliance process can be built into the system and day-to-day operations, so that certain alerts could trigger if a potential compliance issue is observed. This could be via transaction monitoring to flag transactions above compliance limit, regulations around changes to employee salary, employment termination, minimum age regulation for customers, among several others.

Improved Analytics and Market Insights

The ability to understand past and present trends, patterns, behaviors, and results provides an unparalleled potential for fintechs to make data-driven forecasts into the future. Today, in every industry, data is king, and only businesses that can tap into data and efficiently make data-driven decisions will win. AI algorithms can analyze multiple historical datasets to predict the market, customer behavior, cost, and revenue. With such capabilities, fintechs can tailor their product offerings to meet the perceived future needs of the market and would play a crucial role in both human and material resource allocation in a bid to tap into the market opportunity revealed through data.

For fintechs, AI can point you to where the money is by telling you the customers that are likely to make you the most money due to their transaction history; however, most fintechs are not leveraging this capability to provide targeted solutions to such customers. For example, a customer who constantly searches for investment-related tips, but at the same timespends a large part of their disposable income on shopping, travel and outdoor food with little or no savings may need investment products from the fintech; hence, by drilling into customer queries, searches, behaviors, transaction history, fintechs can boost revenue. This same practice can be replicated across other areas, such as customers who may default on loans, customers who may be associated with fraudsters or politically exposed persons, among others, and this would ensure a more rigorous risk assessment and management before commencing such a relationship or transaction.

Improved operational efficiency and cost reduction

To deliver value to customers, fintechs have internal processes that are executed behind thescenes, and often, these processes may be largely inefficient because of certain manual and routine tasks. This can range from data entry, modeling, reconciliation, reporting, emailing, and notification, among others. By leveraging AI to handle such manual and routine tasks in seconds via automation, customer value delivery can be fast-tracked, and time would be saved for more value-adding operational tasks.

Through this, fintechs could save thousands of man hours annually, and this directly translates into cost saved which would have been channeled to salaries, subscriptions for productivity tools, among others, allowing them to channel resources to core business and customer success enablers.

For fintechs whose operations solely depend on value delivery via technology, AI has become a very handy companion to communicate speed, reliability and security to customers; hence, the extent to which fintechs can leverage AI for excellent customer experience could be a differentiating factor between very successful fintechs and the rest. With AI continuously evolving and deploying new capabilities, the possibilities are endless for fintechs to deliver secure and targeted solutions to customers while also protecting themselves from various risksby responsibly and thoughtfully aligning their vision with technology and customer centricity.