Automate (robo-advisor) recommendations for users' investment portfolio advice based on user-completed survey (users must purchase/manage portfolio themselves)

Automated investment decisions by funds that are allocated capital. Funds include Voleon, Castle Ridge Asset Management and Man AHL.

Use satellite image feeds to assess likely commodity prices - this could include likely crop yields for agricultural commodities or shipment levels for mining products.

AutomateRobo-advisor recommends portfolio investing and rebalancing decisions based on defined investment strategies (directly augmenting oversight from investment managers)

Detect potential insider trading through monitoring data flows (e.g. social media, market activity) from company insiders or close contacts.

Enhance business relationship management through generating customer insight and personalised recommendations (improved information flow to operative through ML analysis / personalisation of product and proposition / recommendation - potential suppliers include Accenture, Squirro)

Offer users alternative investment portfolio options based on user-completed risk profile survey (users must purchase/manage portfolio themselves)

Automate key workflow steps in the mergers and acquisition (M&A) process (e.g. document capture) . Banks such as Goldman Sachs can reduce reliance on relatively expensive staff doing low value-add tasks.

Predict asset price movements based on greater quantities of data (e.g., social media, video feeds) to inform trading strategies

Automate generation of reports - for example using financial reporting to generate basic financial market analyst updates

Discover new complex interactions in the financial system to support better risk modelling and stress testing. Analysing large quanitites of data may suggest patterns that are not visible or obvious to human analysts operating with machine learning support. Equally the human will be necessary to question and improve on the ML output.

Automation of documentation steps for Initial Public Offerings (IPOs) of new shares to financial markets helps free up relatively expensive staff time. Automated processes help ensure efficiency, effectiveness and compliance matching (like arranging and tracking legal and compliance reviews, filling in forms and generating reports).

Forecast asset pricing based on market patterns. This can be for investment banking trading and back office teams.

Use chatbot functionality to engage with customer and provide responses to key questions

Automate property manager role with chatbot acting as concierge and interacting with tenants. This is still at an early stage.

Automate aggregation of personalised property listings for real estate customers

Automate building systems to reduce energy costs through AI-powered adaptive temperature and energy control. The challenge is to justify the investment costs against actual energy savings.

Predict pricing and value of real estate based on market and other information. However this is a market where occasionally large price dislocation may be driven by regulatory decisions (e.g. planning) so ML systems may struggle to capture these risks.