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Financial firms bank on A.I. as pilot projects head to production

The financial services sector is pouring money into artificial intelligence (AI), with banks, for example, expected to spend $5.6 billion on AI in 2019 – second only to the retail sector.

Most AI projects today are aimed at improving customer service efficiency and security by introducing chatbot technology, or by deploying machine-based learning to uncover trends across business lines in customer behavior and what they need.

For example, something as simple as automating credit line increases has typically relied on simple financial calculations: a client who uses a card regularly and pays on time gets offered a credit line increase.

The bank more recently conducted a short-term Banking Assistant pilot within the Wells Fargo Mobile app to learn about how conversational banking capabilities can improve customer experience and deliver banking information using AI.

'For example, customers have appreciated the ability to access account information and analyze transactions, and we received very useful feedback on a number of additional capabilities they would like to see in future chatbot experiences, such as the ability to transfer funds and make payments.'

At their core, those capabilities are almost always a suite of technologies, enabled by adaptive predictive power and exhibiting some degree of autonomous learning, that have advanced the ability to automate and enhance services or internal processes.

There are four distinct areas where AI is now being used in pilots or production systems, according to Rajan: Anti-fraud, anti-money laundering and know your customer (KYC) rules have also prompted companies to deploy investigative AI, which combs through internal and external resources to paint a more complete picture of potential customers.

When a client logs into a banking site, for example, an AI script would search for a client record, identify any missing data required for regulatory compliance, email the bank relationship manager and subsequently update the information received by the customer - whether it's a person or a company.

AI technologies of different capabilities are being used to more efficiently manage client onboarding, offer a more intuitive line of questioning tailored to them while also being able to cull their preferences in order to offer future products to them, Rajan said.

'A lot of financial services firms grew organically and have multiple systems and it takes a tremendous effort to bring the data on all those systems together for clients quickly,' Rajan said.

One 'global financial institution' client of Deloitte's, which the company declined to name for privacy reasons, faced a significant manual effort in reviewing each expense report and the supporting receipts for validity and accuracy.

The challenge of integrating legacy data systems with AI remains for companies seeking a unified view of client information. The ideal would be to have one or two data platforms where information flows smoothly, but that doesn't happen often, Rajan said.

'If the systems aren't integrated today, which they are not, can I use a technology that will get customer information from a bank file and from a mortgage file, bring it together and present it to you internally so you can then talk to your customer with a unified view?'

Artificial intelligence in consumer banking

When decisioning is required at today's speed and scale, algorithms have to learn on the fly, which means data has to be instantaneously usable.

It is for this reason that the industry's innovation outlook for the next five years is entirely AI-driven, from intelligent data platforms that put structure into data, to dynamic algorithms that continually learn about consumer preferences and intent as they crawl through data lakes and blockchains.

Like an Alexa for banking, personal digital assistants help consumers access a wealth of information on budgeting, saving for retirement, and more, tailored to their banking needs.

That said, a recent study by Genpact suggests that, while most senior executives believe customers will prefer to be served by a bot than a call center agent by 2021, the consumer perspective is much different.

Moving forward, we see these digital assistants providing not only basic transactional information, but also greater insight into, and advice to help promote, consumers' financial well-being – another reason why integration is important.

The variety of payment and investment systems available to consumers today (such as crypto-currencies, shared economy, and marketplace lending) have brought about a new era in money laundering.

Using a variety of methodologies, AI, by means of deep learning and computer vision, can explore the data and find patterns quickly, an impossible feat using traditional approaches.

While it may seem that banks are removing the personal touch, they're actually increasing the level of personalization and improving consumers' journeys, thanks to insights captured from their digital footprints.

As shown by the second edition of Genpact's recent research on AI, 68% of millennials and over 42% of older generations are comfortable with companies allowing AI to use their personal data to improve their customer experience.

Artificial Intelligence Week in Pictures

With IT spending rising in the MENA market to $160bn in 2019 and the Middle East potentially having $320bn worth of impact on their economy by using Artificial Intelligence, AI is here and it is here to stay.

Artificial intelligence will enable banks to increase customer loyalty

By Matt West, CMO at Feefo There is huge amount of noise currently about the use ofartificial intelligence (AI) in the financial services sector.

AI will change banking As they compete in this intense atmosphere, financial organisations will quickly find they must embrace AI, given the range of applications now operational, such as chatbots, virtual assistants or automated personalised review summaries.

Analysts at Gartner have forecasted that more than 85 per cent of customer interactions will be managed without a human by 2020, while AI market research specialist TechEmergence believes that chatbots will become the primary consumer AI applications over the next five years.

This is a demographic that is moving into the mortgage market, gaining higher salaries and having families.They cannot be ignored and while fees and charges matter, the use of technology is a major factor in who they should bank with, especially when it comes to customer-facing technology that makes interaction easier and increases personalisation.

Research conducted by Feefohas found that access to positive feedback from fellow customers in genuine reviews is the single most influential factor when consumers under 35 decide which bank, lender or financial service to opt for (selected by 85 per cent).

Among the financial organisations surveyed, we found that 43 per cent envisage using AI to provide personalised summaries of reviews, saving customers’ time and increasing the overall relevance of the organisation to each individual.

In this way the shortage of expertise is effectively side-stepped, with bottom-line benefits quickly realised as existing customers feel more engaged and potential customers are convinced it is worth switching accounts.

Chatbots, virtual assistants and personalised review summaries are AI technologies that are fit for purpose now, and with sophisticated out-of-the-box solutions readily available, retail financial business must start implementing them or watch competitors leap ahead.

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