27 Jan 2020
How will AI keep its promises and add tangible value at every stage of your business?

How will AI keep its promises and add tangible value at every stage of your business?

By

Patrice Latinne

EY EMEIA Financial Services Data & Analytics Partner

Passionate leader in the broad data science & AI systems. Energized by team empowerment, success and focus on client satisfaction. Married and father of 3.

27 Jan 2020

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The potential of AI to transform our way of working is becoming better understood, introducing it into a wider range of sectors.

Artificial Intelligence is a game changer. Its potential to transform business operations, customer relationships, risk management, employee empowerment is increasingly being understood, especially at senior management level. AI also allows companies to drive innovation in the way they provide new services and products. And moreover, the business community now expects faster adoption. While the initial cost of applying AI may be high, the potential for long-term savings or benefits is also high. The intelligent automation of processes has been and still is mainstream to AI implementation in the financial services industry.

Today,  “ready-to-use” AI applications emerge too. This creates great new opportunities to transform the FS firm. This also requires to evolve permanently and adapt our jobs, even the one of the data scientist… Visible complexity of AI tends to disappear in favor of high quantities of endpoint AI-Human interfaces to release and manage. Tomorrow, we will talk about the Human worker and AI symbiosis: AI will do the analytical thinking while humans will wrap that analysis in warmth and compassion.

From AI experimentation to operationalization

For a few years now, many companies have mainly been experimenting with the possibilities, introducing “AI” into certain operations and business use cases but on a limited scale. Amongst a hundred of EMEIA FS firms surveyed in autumn 2019, the most mature achievements have happened mostly in risk management and compliance and secondly in customer engagement, very rarely in all other domains. About these mature AI systems, only 30% of these firms have confirmed however that they have been “fully deployed” at scale in their organization. All other use cases are still in a stage between initial experiments and small-scale deployments.

One of the major obstacles we have heard is about changing their business culture. Then comes data quality and old legacy systems bottleneck. Companies held an aversion to change, which they felt risked their reputation. But now companies are aware that they have to move those complex AI-driven solutions into production. Logically companies observe how fast AI adoption goes in China for instance and aim to replicate somehow GAFAs’ successes in their industry. 

The future successes reside in the symbiose between humans and AI systems driven by well-governed use cases

Overcoming the barriers of AI deployment

Controlling risks and overcoming complex barriers are in EY’s DNA (read Data & Analytics also if you prefer), which begins with the ideation stage: bringing industry ideas, people, data, technology and trust together to shape the next best project. Scientists and engineers might jump into the better-governed AI development lifecycle and lines up the development and operational organizations towards go-live release and after-care maintenance of AI systems now fully embedded in business applications.

By “AI” we mean concretely here those relevant selection of techniques and methods being identified to solve the real business problem in hand: maybe it is a suitable combination of machine learning, natural language processing, document recognition and mathematical optimization for instance).  It is key to monitor risks along all the phases of this journey, responding to any stakeholder’s concerns relating to potential conflicts of processes or transparency and data security.

In fact, the compliance departments of companies are often perceived a barrier to increased deployment of AI, incorrectly fearing that it would make operations less transparent. Hence why EY offers hand-in-hand collaboration from the start, providing the right onboarding and training if needed. This problem is still much greater in Europe, which has introduced strong data protection and transparency regulation. 

Eagerness for AI throughout the entire company

It has always been essential to ensure that senior executives are eager to sponsor and drive through change. This remains the number one rule of thumb for any AI-driven initiatives too. All aspects of the business must be onboard, including the compliance and data departments. To ease this introduction, the value of AI needs to be clearly and tangibly demonstrated. While larger companies are more able to invest in the rare talents and emerging technologies, smaller enterprises may resort to outsourcing operations. 

You need to demonstrate upfront AI’s business value – that it’s worth investing in

Increase in AI application across sectors

The potential of this technology is increasingly recognized by our clients. And these are not only banks and insurance firms, which commonly have introduced AI systems but at different stages of maturation. It is companies in other sectors as well. We see that the medical and health care sector has the potential to be amongst the most significant growth area. I personally hope it is AI for the good such like new great initiatives in the public sector leveraging IoT and mobility data for instance.

Also, retail companies are expanding their traditional small-scale data & machine-learning systems. In the media, the use of speech and video recognition technology is becoming increasingly popular, opening up the application of new scientific research in the AI field too, as the lack of training data is become the biggest bottleneck of more advanced AI use cases. Many of these areas are now extending AI processes more comprehensively than the financial services sector. 

Tailored and end-to-end AI solutions

EY keeps continuously connected to the market and research developments, in order to stay at the forefront of what’s happening. In this way and combined with our unique industry expertise, we can respond to our clients’ needs and issues, while respecting our values and safeguarding the trust they place in us. AI should be embedded in everything that we do, proposing it as a service or as an asset. We help find the best possible approach for the client, respecting its budgetary and staffing constraints. We not only advise: we co-create, we co-develop and co-deploy continuously hand in hand and take care after go-live to sustainably consume and leverage the newly live Trusted AI assets.

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Summary

Although obstacles are still present, senior executives are increasingly seizing the potential of artificial intelligence.

About this article

By

Patrice Latinne

EY EMEIA Financial Services Data & Analytics Partner

Passionate leader in the broad data science & AI systems. Energized by team empowerment, success and focus on client satisfaction. Married and father of 3.