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Our Customers Experience a
3x Deployment Rate



Financial Services Industry Expertise



Our platform, expertise, and services mix delivers the most cost-effective, highest ROI approach to train AI models. We provide the most diverse, scalable labeling options across data types, languages and dialects, and security demands. Choose the level of service and security you want, from white-glove managed service to flexible self-service.


  • Five of the top financial service and software companies

  • One of the largest bank holding companies in the US
  • Expertise in tax, accounting, financial software, banking use cases, payment providers, and gateways
  • Security-cleared staff available for onsite transcription/annotation

  • PII data capability: ISO 27001 certified secure facilities, ISO 9001 accredited operations

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Data quality and access to data, as well as access to suitable talent, are all seen as major obstacles to implementing AI [for financial services companies].



Cambridge Centre for Alternative Finance (CCAF)
University of Cambridge Judge Business School and the World Economic Forum


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The Appen Difference



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Higher Quality



Quality assurance peer review workflows, continuous testing and auditing, and our highly-skilled managed crowd collectand label your data

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Greater Speed & Scale



AI assisted capabilities like computer vision, named-entity recognition, intent classification, information extraction for NLP, model validation and retraining, query-result relevance, and more

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Global Expertise



Access a global crowd of over one million, with support for 180 languages and dialects, combined with our global multilingual in-house experts

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Ethical AI



One million people all over the world enable you to build unbiased AI, and our Crowd Code of Ethics, built on a foundation of fair pay, inclusion, and privacy and confidentiality, is key to our crowd well-being






Top Use Cases for Financial Services



Deploy AI projects with confidence to make smarter, faster, and less expensive decisions. Leverage AI to enhance customer experience, customer acquisition and retention, increase business efficiency, and achieve cost reduction goals.



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Automatic Speech Recognition



Improve customer interactions with automatic speech recognition systems by training them to better understand human language.

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Fraud Detection



Increase fraud detection rates, reduce false positives, and minimize losses through systems built with high-quality data sets.

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Risk Management Models



Use human insight to improve the quality of the data used in your machine learning-based risk model.
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Semantic Search



Improve your semantic search capabilities with training data that provides user intent and context.
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Text-to-Speech



Improve customer interactions with TTS systems that are fluent in every language.
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Virtual Assistants and Chatbots



Train your virtual assistant or chatbot to better understand and respond to human interaction, driving higher levels of customer satisfaction.





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Single Data Collection and Annotation Pipeline


Financial services teams can leverage our full suite of multimodal collection and annotation tools and combine them in an automated process with Workflows within the Appen Platform to:
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Break complex projects down into simple jobs, then automatically route data between the jobs using configurable routing rules
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String multiple jobs or models together in a branching or linear configuration
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Leverage machine learning in workflows to offset costs and expedite project completion

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Choose your level of effort



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Platform



Your team is technology savvy and you have experts in-house to leverage our industry-leading platform to manage training data projects independently.

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Platform Plus



Your team manages your training data projects, but you want expert guidance and support to ensure you consistently get high-quality training data.

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Managed Services



Your team sends us raw data and specifications, and we deliver high-quality training data with our end-to-end solution, leveraging our platform, expertise, and crowd so you can focus on models, not labels.