Computer Vision
Computer vision is a field of Artificial Intelligence (AI) that enables computers and systems to derive meaningful information from digital images, videos and other visual inputs, and take actions or make recommendations based on that information. If AI enables computers to think, computer vision enables them to see, observe and understand.
Why is it important for the financial industry?
Computer vision can help eliminate financial institution paperwork, save time, resources, and money.
The biggest advantage of Computer Vision is document data extraction.
Financial firms are often swamped with large numbers of incoming paper documents that need to be scanned using optical character recognition software, as well as digital documents such as PDF, Word, Excel and Email, which are typically administered by human workers.
At Semantic Evolution, we have developed a technology that applies proprietary Artificial Intelligence techniques, Machine Learning, advanced semantics and Natural Language Processing, to automatically extract target data from unstructured documents such as PDF, Word, Excel and Email. This flexible and intelligent technology can scale across an organization providing businesses with improved operational efficiencies and a rapid ROI.
The software digitizes paper-based information before segregating it for human review. Traditionally, the process is done manually and is highly error-prone as well as being time-consuming. Image recognition technology integrates with existing processes, automatically identifying and understanding the financial documents.
Through automating the financial data extraction, teams can focus on solving problems, rather than data entry tasks.
Computer Vision could, in some cases, eliminate the need for human inspectors while providing accurate real-time data. Insurance companies can benefit hugely from this as it eliminates the chances of fraud and false claims.
Types of financial documents used with Computer Vision?
Computer Vision is used in many document use cases such as complex Annual Reports, Articles of Incorporation, Bonds, Contract Notes, Corporate Actions, ESG, Financial Statements, Solvency II Reports, Credit Agreements, Loan Notices, Municipal Bonds, Pricing Supplements, Reassurance, Real Estate Offering Memorandum, Term Sheets etc.
Computer Vision algorithms can quickly find important data points, mitigating the need for humans to study them.
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