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Artificial Intelligence and the Financial Services Industry

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Using Artificial Intelligence, also known as AI, is becoming an important part of the economy. Its use in manufacturing can help reduce production costs, increase productivity, and improve products. With a variety of software programs available, it can help your business streamline processes and eliminate duplicate tasks. It also can help your business improve customer service.

Orum

Amongst the competition, Orum has a shot at the billion dollar prize. In a bid to differentiate themselves from the pack, the company is also trying to break into the international market with the help of a $28 million round of funding, according to a press release. A free version of its wares is also on the horizon. Its competitors include Google Cloud, Amazon Web Services, Five9, and Connect and Sell. The company specializes in intelligence backed payment orchestration. It also boasts an impressive suite of technologies, including mobile payments, artificial intelligence, and big data. This includes a robust payment platform for banks and other financial institutions, and an automated, AI-powered customer engagement platform.

Orum also has a robust CRM platform that allows its users to create custom workflows, and provides analytics and intelligence backed reporting. The company also has a solid mobile presence, with over 400 customers. Orum has also garnered a lot of press coverage for its customer support efforts, notably in CNet, TechCrunch, and other tech savvy publications.

Artificial intelligence

Despite the hype, the financial services industry has already started to deploy artificial intelligence. The biggest challenge for data scientists was operationalizing their models. Rather than using standard applications, the data scientists are using a new form of computational discipline called cognitive search. This technique uses AI to ingest, organize, and query digital content.

The next challenge is to get AI into production. According to a recent survey, 32% of execs said that it took longer to get AI into production than they expected. One reason for this is that AI is a dynamic discipline that does not exist in a static state.

Another reason is that many executives have no idea how to get to AI in 12-18 months. There are several tools that can address risky AI deployments.

Currently, there are several applications that integrate blockchain with AI. One example is PatientSphere. This is a blockchain-based data-sharing platform that uses AI to provide patients with treatment plans and exercise tips. Another is Cerebras Systems. This company announced a partnership with Jasper AI on a generative AI tool. The tool can be used to create and share AI algorithms.

Ethics statement

Developing an Ethics Statement for AI requires a proactive approach. It requires addressing three key areas.

The first is AI’s role in society and how to best use it. Consumers should know what impacts unethical AI will have on them. They should also understand how to balance the value of AI with the risk. The other two are defining a set of societal norms and defining fairness.

The third area involves developing a code of ethics for AI. An AI code of ethics is a guide to ethical decisions for all stakeholders involved in the AI system. It provides a framework for making ethical decisions, and includes rules about deployment, continuous monitoring, and tracking the provenance of data. The AI code of ethics should also incorporate measures to guard against the development of unintended bias in machine-learning algorithms.

Conclusion

Developing a code of ethics for AI requires a system that is explainable and inclusive. It must also include safety measures to prevent corruption and ensure that the system works equally well across all spectrums of society. It is also important to include measures to track the identity of those who train the algorithm.

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