TAIGER secures seat in CaixaBank’s open innovation programme
Spain’s leading financial group in retail banking, CaixaBank, has selected TAIGER as one of the most innovative startups as part of its CaixaBank Fintech by Innsomnia open innovation program.
TAIGER is one of the 7 fintechs, out of 200 applicants from 28 countries, to secure this exclusive seat. The Singapore and Madrid-based AI vendor will be developing a proof of concept that applies NLP and AI technology to unstructured documentation.
TAIGER to fill in gap in intelligent technologies
Intelligent technologies that effectively deal with language, like TAIGER’s offering, are seeing new waves of demand across large financial institutions. Exponential increases in both the variety and volume of documents are taking a toll on traditional automation tools. Most Optical Character Recognition (OCR) and document processing tools in the market are still technologically inferior in handling such problems.
Built with Machine Learning and Deep Learning algorithms, these document processing tools perform well only with highly specific document types. For example, they’re able to read e.g. a Spanish passport, and not a Singaporean passport. Or, they’re able to extract data points from a shipping invoice issued by Company X, and not a retail invoice issued by another business.
Consider the variability of documents spread across different use cases, from onboarding and KYC, to records management and claims processing. Scalability becomes a clear hurdle considering the reality of unstructured data.
NLP has a growing potential to unlock hard-to-read data
Emerging technologies like Natural Language Processing (NLP) which are capable of reading natural language–i.e. everyday, human language–are hence bridging a crucial gap. Embedding advanced tools like NLP into Intelligent Document Processing (IDP), a tool which processes all kinds of documents into structured data, will be a gamechanger in lowering costs.
Unlike pure Machine Learning methods, NLP is able to understand the context behind the data in each document, similar to the human brain. When working alongside other technologies like OCR, Machine Learning and Deep Learning, the hybrid approach helps to more accurately convert unstructured information into structured insights.
Customer service a top priority for financial institutions
The new call for innovation comes at an opportune moment as well, with the expectation of real-time responses emerging as a new normal for customers today. Organisations are struggling to provide high quality customer service in a timely manner. To do so, organisations need to realise new levels of speed, accuracy and scalability in the tools they bring on board.
With customer satisfaction in mind, banks like CaixaBank are leading the pack by taking decisive steps towards more innovative, emerging technologies.
CaixaBank selects TAIGER from 200 fintechs in its Open Innovation program
TAIGER secures seat in CaixaBank’s open innovation programme
Spain’s leading financial group in retail banking, CaixaBank, has selected TAIGER as one of the most innovative startups as part of its CaixaBank Fintech by Innsomnia open innovation program.
TAIGER is one of the 7 fintechs, out of 200 applicants from 28 countries, to secure this exclusive seat. The Singapore and Madrid-based AI vendor will be developing a proof of concept that applies NLP and AI technology to unstructured documentation.
TAIGER to fill in gap in intelligent technologies
Intelligent technologies that effectively deal with language, like TAIGER’s offering, are seeing new waves of demand across large financial institutions. Exponential increases in both the variety and volume of documents are taking a toll on traditional automation tools. Most Optical Character Recognition (OCR) and document processing tools in the market are still technologically inferior in handling such problems.
Built with Machine Learning and Deep Learning algorithms, these document processing tools perform well only with highly specific document types. For example, they’re able to read e.g. a Spanish passport, and not a Singaporean passport. Or, they’re able to extract data points from a shipping invoice issued by Company X, and not a retail invoice issued by another business.
Consider the variability of documents spread across different use cases, from onboarding and KYC, to records management and claims processing. Scalability becomes a clear hurdle considering the reality of unstructured data.
NLP has a growing potential to unlock hard-to-read data
Emerging technologies like Natural Language Processing (NLP) which are capable of reading natural language–i.e. everyday, human language–are hence bridging a crucial gap. Embedding advanced tools like NLP into Intelligent Document Processing (IDP), a tool which processes all kinds of documents into structured data, will be a gamechanger in lowering costs.
Unlike pure Machine Learning methods, NLP is able to understand the context behind the data in each document, similar to the human brain. When working alongside other technologies like OCR, Machine Learning and Deep Learning, the hybrid approach helps to more accurately convert unstructured information into structured insights.
Such natural language technologies have been identified by Gartner in its Hype Cycle report. TAIGER is spotlighted as a sample vendor in both the Gartner Hype Cycle for Natural Language Technologies and the Gartner Hype Cycle for Emerging Technologies (2020).
Customer service a top priority for financial institutions
The new call for innovation comes at an opportune moment as well, with the expectation of real-time responses emerging as a new normal for customers today. Organisations are struggling to provide high quality customer service in a timely manner. To do so, organisations need to realise new levels of speed, accuracy and scalability in the tools they bring on board.
With customer satisfaction in mind, banks like CaixaBank are leading the pack by taking decisive steps towards more innovative, emerging technologies.
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