In today’s fast-paced and ever-changing financial landscape, it is essential to implement technologies that detect risks in advance. Financial risks can arise from a variety of factors, including market volatility, fraudulent activities, and cyber threats. Without adequate monitoring and alerting of these areas, companies fall short in identifying these risks, leading to severe financial and regulatory consequences.
One of the most effective ways to detect financial risks is to implement platforms that utilise natural language processing (NLP). NLP is an AI technology that enables machines to understand human language, including written and spoken language. NLP can help financial institutions identify and detect financial risks by analysing vast amounts of unstructured data from various sources, including news articles, social media, and financial reports.
Challenge
Traditional risk management methods may not have the analytical capabilities to analyse unstructured data such as news articles, which may contain critical information about potential risks. The challenge is that a human’s ability to analyse vast amounts of unstructured and structured data is limited. To put this into perspective, AMPLYFI’s models can process a lifetime of human reading in just 20 minutes. The benefits in using AI to detect risks faster is evident.
Here are some of the challenges facing companies that don’t implement these technologies in today’s volatile landscape:
Data Overload
Financial institutions have access to vast amounts of data from various sources, including market data, economic indicators, financial statements, and news articles. Analysing this data manually can be a daunting task, as it is time-consuming and prone to errors.
Limited Coverage
Financial institutions may miss out on detecting potential risks if they rely solely on traditional risk management methods. These methods may not cover all sources of risk, including emerging risks, market trends, and sentiment analysis.
Delayed Detection
Traditional risk management methods may not detect risks in real-time, leading to delayed responses and increased financial losses. For example, traditional risk management methods may not detect sudden market changes or significant events that may impact financial markets.
Inadequate Analytics
Traditional methods may not have the analytical capabilities to analyse unstructured data, such as news articles and social media posts, which may contain critical information about market movement or regulatory change.
Fraudulent Activities
Traditional methods may not detect fraudulent activities, such as money laundering and financial fraud, which require sophisticated techniques to identify.
Solution
AMPLYFI’s Monitoring and alerting platform provides near-real-time information on regulatory changes, adverse media mentions, trading activities, and market volatility. The platform uses sophisticated NLP models to identify patterns and anomalies that may indicate a risk event.
Here are some ways DeepInsight can help detect financial risks:
Sentiment Analysis
DeepInsight analyses the sentiment of news articles to determine market sentiment and investor sentiment. A negative sentiment may indicate potential risks, such as a financial scandal, corporate fraud, or a significant market downturn.
Topic Modelling
DeepInsight identifies and categorises financial topics discussed in news articles and social media posts, allowing financial institutions to identify potential risks. For example, if the majority of the news articles and social media posts discuss a company’s debt and financial struggles, it may indicate potential risks such as a credit rating downgrade or even bankruptcy.
Named Entity Recognition
DeepInsight identifies and extracts specific entities from financial documents, such as company names, people, and locations. This information can be used to identify potential risks, such as significant changes in a company’s management team or regulatory changes in a particular location.
Event Extraction
DeepInsight analyses news articles and social media posts to identify significant events that may impact financial markets, such as natural disasters, political changes, or global pandemics. This information can be used to predict market trends and identify potential risks.
AMPLYFI offers a powerful platform that can help financial institutions detect financial risks by analysing vast amounts of unstructured data from various sources. By leveraging our natural language processing tools, financial decision-makers can proactively manage financial risks, minimise financial losses, make more informed decisions and ensure the organisation’s long-term success.
If you have any questions or have feedback about DeepInsight, please reach out to your Customer Success Manager or contact support@amplyfi.com.
