Financial Services
Dynamic facets revolutionizing financial services
Overview
The financial services industry irrevocably and monumentally changed in the last ten years due to digital disruption. The past five years brought a higher level of innovative digital technologies than ever before. Digital transformation combined with the industry’s highly regulated nature has led to an exponential increase in the content that firms deal with, such as regulatory publications, KYC docs (e.g., passports and payslips), claim forms, application forms, leases, and other documents. These are in addition to the mountains of internal documentation stuck in silos, which hinders legacy financial institutions from using it to drive business decisions.
Internal data needs to be combined with public domain data to enable banks, asset management companies, and hedge funds to drive personalized customer experiences and identify ways for alpha generation while ensuring efficient operations to reduce costs.
The rise of FinTechs, which operate outside the barriers of legacy systems in a digital-only environment, has accelerated the pressure on financial institutions. While financial institutions have come a long way in implementing machine learning and AI, these are limited mainly to structured datasets.
Challenges
Some of the challenges that firms face when dealing with unstructured content include
Handling many unstructured documents such as identity and address proofs, payslips, property documents, valuations, contracts, etc., in various formats with varying levels of quality.
Manually processing the documentation limits scalability; about 30–40% of the time is spent on noncore automatable tasks.
Acquiring unstructured public data at scale within the compliance framework.
Information requiring manual cross-referencing with original documentation across databases, third-party providers, government agencies, and customer-supplied data.
How Straive can help
Our text and public data intelligence solutions enabled by our Straive Data Platform (SDP) can help financial organizations mine their unstructured data by leveraging artificial intelligence, machine learning, and NLP and automate integrating unstructured data into their business processes.
Banks
Straive enables banks to manage unstructured data from loan documents, application forms, payslips, property documents, regulatory documents, etc., and public sources such as social media, government registries, and watchlists.
Capital Markets
We enable investment banks, asset and wealth managers, hedge funds to generate alpha by acquiring alternative data and manage regulatory risk such as LIBOR transition.
ESG Solutions
Our ESG services focus on helping you derive intelligence and value from unstructured data sources to make it consumable and improve any ESG rating framework.
Risk & Compliance
Straive enables financial institutors to automate and enhance their existing processes in AML and KYC through adverse media monitoring, watchlist consolidation, and enhanced KYC.
Our Solution
Key capabilities of Straive’s Text Intelligence solutions include:
- Processing complex unstructured documents such as payslips, leases, application forms, insurance documents, tax returns, etc.
- Removing native noise to handle poor quality scans
- Handling handwritten documents
- Extracting relevant entities and key-value pairs using machine learning & NLP
- Creating abstract and extractive summaries
- Correcting and validating using the human-in-the-loop approach
- Delivering as API or in any structured/semi-structured formats like CSV, XML, JSON, and TXT for downstream integrations
Key capabilities of Straive’s Public Data Intelligence solutions include:
- The ability to extract information from millions of websites through a few pattern-based generic engines
- The expertise to extract data from complex web pages, including automated handling of captcha using computer vision
- The capability of attended and unattended bots for websites that restrict automated crawling
- The proficiency to automate scaling based on infrastructure as a code set up on AWS and downstream integrations with APIs
- The competence of Named Entity Extraction from unstructured website content with NER and NLP libraries
- The ability to extract data from 27+ languages and optional integration with a translation engine
Insights
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Our solutioning team is eager to know about your challenge and how we can help.