Risk profiling

What is risk profiling?

Risk profiling is a process of measuring the amount of risk a person, entity, or an organization is willing to undertake, which could be about a transaction, investment, process, or a decision. In general, risk profiling is associated with finance and investment, where organizations take careful steps to investigate the kind of risk acceptable to their organization.

In the case of investment, risk profiling requires the following data points to function:

• Behavioral data
• Financial capacity
• Regulatory constraints
• Transaction amount or loan amount to be granted
• Past spending and historical patterns.

With the help of risk profiling systems, the organization could make decisions:

• Can we proceed with approving the transaction/loan/application?
• Does this look suspicious?
• Should continuous monitoring be enabled for this?
• Risk profiling vs risk assessment

Risk profiling and risk assessment sounds the same, but they aren’t. Risk profiling is all about understanding the type and level of the risk, while risk assessment evaluates the impact of a specific risk. Unlike risk profile that gives importanace to behavioral data, risk assessment focuses on historical data, threat models, vulnerabilities, etc.

Which industries require risk profiling the most?

Risk profiling is a major process in many sectors. Here are some, with specific requirements.

Banking & financial services: Banks and mortgage processing agents require risk profiling to assess credit card applications, loans, and financial investments to manage credit risk effectively. Similarly, insurance sector needs risk profiling to check customers’ life, health, and property insurance policies.

Cybersecurity: IT teams and cybersecurity experts require risk profiling to do risk-based authentication and prevent anomalous behavior, insider threats, and user access with malicious intent.

Wealth management: Portfolio recommendations could be curated to meet investors’ risk appetite with the help of accurate risk profiling.

Healthcare: Healthcare instituitions and hospitals could apply risk profiling to take care of patients with critical illness and allocate medical resources efficiently.

eCommerce: eCommerce companies can use risk profiling to monitor to flag risky transactions, bot invasions, or fraudulent user access and also handle chargebacks.

Compliance: Risk profiling is necessary to stay vigilant of changing regulations and validate customer risk as a part of KYC/AML lifecycle.

The role of ML & AI for risk profiling

AI is transforming many use cases, making them more accurate, speedy, and accessible. Here’s how risk profiling makes it better.

Better decision-making: With better speed and accuracy, AI can improve decision-making, allowing to access and process both historical and live data at the same time.

Handling large amounts of data: Traditional systems cannot handle large velocity of data at faster times and certainly cannot process billions of data points at the same time. But AI makes it possible and also could spot hidden trends that human analysis can miss.

Continuous learning and improvement: Unlike traditional systems, AI/ML models can improve their risk profiling capabilities over time when it’s exposed to new data and feedback. Hence, no matter how dynamic the landscape can turn, the risk system can re-adjust without having to be reprogrammed.

Personalization: Modern fintech or eCommerce applications are all about hyper-personalized experiences, which AI-driven processes can do, tailoring content, offers, and risk suggestions with high precision.

Accurate fraud detection: With cyber threats becoming more sophisticated, finance companies and payment processers have to be more adept. There is a possibility of accessing millions of data points without appointing a large number of labors 24/7.

Automative repetitive tasks: AI is perfect for handling rule-based, repetitive tasks which can be automated to get them done faster in real time.

Benefits that are industry agnostic: Be it finance, healthcare, or higher education, AI-driven solutions can be customized for any industry and its challenges. Highly domain-adaptive and flexible. For example, risk profiling in manufacturing could be employed in predictive analytics whereas in logistics, it can help with route optimization.

Benefits of risk profiling

• Businesses can run at optimized costs with fewer resources and better time and accuracy.
• Better personalization, where better curation of products, content, and experiences based on user risk tolerance.
• Customers could manage and diversify their investments with accurate, data-driven recommendations and take proactive steps and do better damage control.
• Businesses can stay aligned with finance, insurance, and KYC compliances.

Risk profiling is an ongoing process and requires decisions on accurate and automated basis, not on guesswork. With the help of AI and other innovative solutions, you can bring real-time insights and automated action every time there is a requirement.