AI for Financial Analysis
Updated: September 09, 2019
2019. AppZen raised $50M to build AI for financial analysis
AppZen, the startup which builds AI-powered tools to automate functions within the finance department, has raised another $50 million. To date, AppZen’s biggest product has been a service that automatically audits expenses — comparing, for example, an employee’s charges with travel that person has undertaken (along with many other data points) to see if the charges match up; as well as making sure the expenses are compliant with company policies and raising flags when they are not. This is the product that has won the company a ton of clients, including Amazon, Nvidia, Salesforce, three of the top 10 banks in the U.S.
2018. Zoho Analytics got AI-powered Assistant
Zoho Analytics now sports the AI-powered Zia, Zoho’s intelligent assistant. Whether it be questions like ‘Get me the support tickets received this month, by product by region’ or ‘Give me sales by country by channel’, you just ask Zia. Zia converts such questions asked in natural language to complex SQL queries in the back end, and comes up with multiple relevant report suggestions. You can save the suggestion that best suits you as a report directly. Besides, the new Zoho Analytics makes it easier to analyze data from across apps, and to easily create interactive reports and dashboards and predicts future trends accurately based on their past data. Also Zoho Analytics adds seven new connectors for popular business apps. Each of these connectors come with more than 100 pre-built domain-specific reports and KPI dashboards that users can benefit from right away.
2018. Tableau acquired AI-analytics startup Empirical Systems
Enterprise BI giant Tableau has acquired Empirical Systems, an early stage startup with AI roots. Their product is still in private Beta. It is delivered currently as an engine embedded inside other applications. That sounds like something that could slip in nicely into the Tableau analytics platform. What’s more, it will be bringing the engineering team on board for some AI knowledge, while taking advantage of this underlying advanced technology. Empirical was developed to make complex data modeling and sophisticated statistical analysis more accessible, so anyone trying to understand their data can make thoughtful, data-driven decisions based on sound analysis, regardless of their technical expertise.