Fintech is currently facing huge financial losses worldwide. In 2022, the market capitalization of the industry fell to $156 billion, while 70% of financial institutions lost over $500,000 to fraud. In these challenging times, it’s essential for companies to develop an efficient risk management process to mitigate further losses.
In this article, we explain how fintech companies can improve their risk management procedures, the types of risk management out there, and how AI can be used to minimize risk.
Understanding Risk Management
Risk management is an ongoing process of identifying possible business risks. The process is essential for any business relationship, especially in the fintech industry. However, the risks that companies face can differ—for instance, depending on the countries or industries where they operate—which means there’s no one-size-fits-all approach.
Over the past few years, the technologies used by fraudsters have advanced, leading to more dangerous schemes and greater risks for companies—particularly in fintech.
Therefore, the industry should thoroughly develop its risk management systems to confront this new reality, covering the following key points:
· Regulatory risk
· Anti-Money Laundering (AML)
· Countering Terrorist Financing (CTF)
· Fraud risk
· Consumer risk
· Merchant risk
· Outsourcing risk
Types of Risk Management
Companies face a variety of risks, which can be classified in the following manner:
· Liquidity risk
· Inflation risk
· Tax risk
· Opportunity risk
· Longevity risk
· Market risk
· Compliance risk
For each type of risk, a company can employ one of these four management strategies:
All these risk management approaches should be integrated by companies in order to minimize risks.
Challenges in Fintech Risk Management
Shifting regulations (e.g., GDPR (Global Data Protection Regulation), PSD2, MAS), third-party risks, and cybersecurity challenges demonstrate that fintech companies need to develop an efficient risk management framework to avoid financial losses, even if this means additional costs at the initial stages.
Creating a Risk Management Process with AI Technologies
AI has been around for many years, but the last few months have shown the potential the technology has. AI can be used to automate certain fintech industry practices in a way that minimizes risk levels and maximizes profits. For example, trading companies can use AI to more accurately predict customer investments by analyzing their behavior. AI can also help with:
· Fraud detection
· Market analysis
· Automation of compliance and regulatory checks
· Customer risk assessment
By analyzing massive amounts of data on patterns and user behavior, AI can allow fintech companies to focus on their core tasks. For example, companies can implement AI for customer verification to improve automation and fraud detection.
Fintech Niches That Need AI
AI can be used in almost any facet of the fintech industry. This includes customer verification, transaction monitoring, digital banking, chatbots, analytics, and blockchain to enhance security during transactions.
To put it shortly, AI can reduce a variety of costs while increasing a company’s potential in almost any field. Even if AI technologies are still being developed, it’s already clear that they can be highly integrated into a company’s workflow.
Benefits and Drawbacks of AI in Fintech
While AI technologies are being actively implemented in the fintech industry, there are still some risks. In the table below, you can compare the benefits and drawbacks of AI solutions.
A Solution for Fintech
According to a Deloitte report, an efficient risk management solution should include a six-step program:
· Appoint internal management
· Divide all types of risks into categories
· Evaluate the company
· Look out for emerging trends
· Understand the maturity of the risk management process
· Develop proper communication and reporting procedures
Risk management means integrating many different practices and solutions, and AI is one way to simplify the process. Another way to do so is by employing a risk orchestration solution. Such a solution can also be combined with AI technologies, allowing fintech companies to customize the customer verification process to ensure that criminals will not be onboarded.