5 Artificial Intelligence (AI) Trends That Will Drive Finance in 2020

5 Artificial Intelligence (AI) Trends That Will Drive Finance in 2020

Whether we like it or not, AI is here and will continue to impact people’s lives. It will bring new opportunities for businesses and the workforce alike. It will create new experiences for customers that are more aligned with their expectations. Here are 5 most notable artificial intelligence (AI) trends that will drive finance in 2020.

Open source frameworks will grow.

Thanks to open source software, the barrier to entry in AI is lower than ever before. Nowadays, there are a number of open-source tools to choose from, including Keras, Microsoft Cognitive Toolkit, and Apache MXNet. Before these, Google has already warmed the market with it released its TensorFlow machine learning library as an open source back in 2015.

Predictive maintenance algorithms will gain traction

Cost pressures will continue to drive many companies to find ways to save millions of dollars in unexpected failures. As such, predictive maintenance algorithms, which constantly collect data to predict equipment failures before they occur, will gain traction. With continued drop of sensor costs and increasing availability of required skillsets, investments in this area will grow dramatically.

Cost pressures will continue to drive many companies to find ways to save millions of dollars in unexpected failures. As such, predictive maintenance algorithms, which constantly collect data to predict equipment failures before they occur, will gain traction.

Auto claims processing and settlement will improve

In the past, humans manually analyse accident images and review driver behaviour based on available documentary record. This will change. With many insurers and fintech companies now using AI to compute a car owner’s “risk score”, expect the whole system to be overhauled resulting to faster claims processing and better customer experience.

Language translation will become more responsive to business needs

Natural language processing for the purpose of language translation accurate enough to respond to business needs has always been a challenge. Thanks to companies such as Google and Baidu, this might be a thing of the past. With much resources being poured into improving translation frameworks, expect great improvements in language capabilities, allowing wider adoption across industries.

Proactive cyber threat monitoring

The financial industry has been rocked with multiple cases of breach in cybersecurity. It resulted to an immeasurable amount of loss in revenue, not to mention the trust and confidence of many customers in these institutions. With advancements in computing power, proactive hunting of threats using machine learning is now possible and will continue to grow as more businesses realise its intrinsic value.

 

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