Targeting and timing your investment

AI is set to be the key source of transformation, disruption and competitive advantage in today’s fast changing economy. Drawing on the findings of our AI Impact Index, we look at how quickly change is coming and where your business can expect the greatest return.
In the research carried out for this report, we’ve drilled down to the sector-by-sector and productby-product impact of AI to enable your business to target the opportunities, pinpoint the threats and judge how to address them.

The unique analysis within FORFIRM’s AI Impact Index includes a rating for the potential to free up time and enhance quality and personalization. We’ve used this analysis to create nearly 300 use cases setting out the openings for innovation, the drivers, timings and current feasibility of market adoption, what could hold this up and how these barriers could be overcome.
The areas with the biggest potential and associated timelines we outline at a high level here are designed to help your business target investment in the short to medium term. Some aspects of change, such as robotic doctors, could be even more revolutionary, but are further off.


What’s the potential impact for your sector?


Businesses can develop customized solutions rather than expecting consumers to sift through multiple options to find the one that’s appropriate

Financial services

Three areas with the biggest AI potential

• Personalised financial planning.

• Fraud detection and anti-money laundering.

• Process automation – not just back office functions, but customer facing operations as well.

Consumer benefit

More customised and holistic (e.g. health, wealth and retirement) solutions, which make money work harder (e.g. channelling surplus funds into investment plans) and adapt as consumer needs change (e.g. change in income or new baby).


Ready to go:Robo-advice, automated insurance underwriting and robotic process automation in areas such as finance and compliance.

Medium-term potential: Optimised product design based on consumer sentiment and preferences.

Longer-term potential: Moving from anticipating what will happen and when in areas such as an insurable loss (predictive analytics) to proactively shaping the outcome (prescriptive analytics) in areas such as reduced accident rates or improved consumer outcomes.

Time saved

The information customers need to fully understand financial position and plan for the future is at their fingertips and adapts to changing circumstances. Businesses can support this by
developing customised solutions rather than expecting consumers to sift through multiple options to find the one that’s appropriate.

Barriers to overcome

Consumer trust and regulatory acceptance.

High potential use case: Personalized financial planning

While human financial advice is costly and timeconsuming, AI developments such as robo-advice have made it possible to develop customised investment solutions for mass market consumers in ways that would, until recently, only have been available to high net worth clients. Finances are managed dynamically to match goals (e.g. saving for a mortgage) and optimise client’s available funds, as asset managers become augmented and, in some cases, replaced by AI. The technology and data is in place, though customer acceptance would still need to increase to realise the full potential.

Assisted intelligence in action

A financial services organisation used machine learning to develop time-series clusters of their policyholder transactions. The machine learning solution helped the company to identify common customer transaction patterns and better understand the key triggers driving variances. Combining policyholder data with external data on customer preferences, financial literacy, and other behavioural dimensions allowed the firm to better predict which patterns would occur for each customer persona. The organisation designed interventions around these insights, which opened the way for improved outcomes for both the customer and the company.