Learn how to build an efficient risk management process for fintech companies.
Fintech is currently facing huge financial losses worldwide. In 2022, the market capitalization of the industry fell to $156bln, while 70% of financial institutions lost over $500k to fraud. In these difficult 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.
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:
Companies face a variety of risks, which can be classified in the following manner:
For each type of risk, a company can employ one of these four management strategies:
Risk avoidance is the process of refusing to participate in a financial activity that causes a given risk. This typically takes place when a company expects the risks to be much higher than the possible benefits of a given arrangement.
Risk reduction is when companies attempt to predict and reduce risks typically at the early stage of any business relationship. This can be achieved by creating a standardized set of terms for partners, working towards contract negotiations on favorable conditions, and more. Other examples include implementing safety protocols and performing regular maintenance on equipment or systems.
Risk transfer is when companies share the risks of a business relationship with another company. Typically, a company can outsource some certain areas of risk to a specialized third party. A good example is when companies outsource customer verification to specialized KYC providers.
Risk retention is when companies insure against various risks they may face. This could be paying for employee health insurance to avoid potentially heavy medical costs, setting up contingency funds, and accepting higher deductibles on insurance policies
All these risk management approaches should be integrated by companies in order to minimize risks.
These three challenges demonstrate that fintech companies need to develop an efficient risk management framework in order to avoid financial losses, even if this means additional costs at the initial stages.
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:
By analyzing huge 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.
AI can be used in almost any facet of the fintech industry. This includes:
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.
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 company should create a clear governance program explaining the roles, activities, and responsibilities of the company’s risk management personnel, who should monitor the company’s risk appetite and make sure it doesn’t go above the threshold.
Companies can separate risks into different categories (e.g., longevity, market, tax). This way, they can efficiently distribute risk management to people specializing in each category. After this, the risks can be divided by level (high, low, and medium), allowing companies to identify the most critical problems first.
After classifying all the possible risks by types and levels, companies should determine whether they have the means to mitigate them. To do so, companies should complete a risk and control self-assessment.
Companies should evaluate emerging risks and resource management on an ongoing basis to maximize the efficiency of the risk management process.
Companies should be aware of the state of maturity of its risk management. Here are some parameters:
Companies should work towards collecting information from established risk metrics and delivering information to management.
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 won’t be onboarded.
Risk management is the process of identifying possible business risks and analyzing them in order to minimize losses. The main risk types are:
Companies use risk management to evaluate the level of risk in a given business relationship. s. This process also ensures that companies don’t go above their threshold of risk.
Fintech industry is already using AI in the following fields: