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Finance

Using ANAI, citizen data scientists and other developers with limited machine learning expertise can easily ingest data, generate insights and build/train ML models.

 

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potential use cases

How can AI be leveraged in Finance?

Credit scoring

Empower financial institutes through AI-powered credit scoring methods giving an ability to avoid bad debts and defaulting customers while credit lending.

Fraud detection

AI systems can determine fraudulent transactions before they actually occur by analyzing them and can help banks prevent frauds such as money launderings and fake identity sign-ins.

Process Automation

Automate repetitive processes such as documentation, report creation, or keeping track of share market prices for a financial institute using AI, ultimately saving extra time and costs.

Reconciliation

Deploy AI-based tools to handle reconciliation, helping financial entities manage data and perform these tasks more efficiently in an error-free way saving a lot of time.

limits

challenges found

01
Biased Output
AI-based models trained on biased data can produce biased results leading to the selection of applicants belonging only to a certain persona. 
02
Difficulty in setting up
Getting started with AI integration requires a dedicated Data Science team with the expertise to build and train models and then deploy them.
03
Cost challenges

The entire process is quite expensive if hiring the proper talent and building and maintaining such complicated systems are involved.

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04
Trust Issues

Even if the model shows the best performance, customers and other stakeholders can still have trust issues with the system which can lead to a failure in adoption. 

our platform

With ANAI, Build The Best AI Solutions

  • ANAI provides explainability as one of its main features, using various eXplainable AI (XAI) techniques which help in identifying bias in the data early on and helps in building an AI model that is explainable and fair.
  • ANAI enables businesses to perform high-level data science tasks with a simple no code approach-based UI and helps them incorporate AI into their workflow with ease.
  • Using ANAI, citizen data scientists and other developers with limited machine learning expertise can easily ingest data, generate insights and build/train ML models.
  • ANAI is built with trust and responsibility in mind and hence it allows businesses to understand and explain the automatic AI processes to their stakeholders for helping them generate trust in the system.
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