The potential applications of Artificial Intelligence (AI) in banking was the hottest topic at FinTech Connect Live last week. From transforming wealth management to enhancing customer service, financial institutions seem to be waking up to the reality that AI will be a driving force in the digitization of the banking sector.
But AI and the technological revolution it promises seems to be a little misunderstood. To many, the automation and efficiencies that AI bring could mean thousands of jobs will become obsolete and banking will become increasingly impersonal. We look at how AI will – and won’t – impact financial institutions and which industry will likely be the next focus for disruption.
FinTech and AI breaking the banking mould?
If money talks then it is shouting about the development of AI, with over $15 billion privately invested in it between 2010 and 2014. Investment is feeding a buoyant market of FinTech startups which use AI to produce exciting alternative financial products and services. Many are now working with incumbent banks to improve services for the digital age for both everyday consumers as well as businesses. Barclays and Santander are running incubator projects to help foster growth in the industry.
Regulators will play an important role in the uptake of AI in banking, as they could either pose a barrier or help facilitate the widespread adoption of this technology. Regulators can quite rightly be wary of new technology due to concerns over inflated hype and low-quality products. It is, however, in the interest of the regulators to embrace AI as advanced computing power will be necessary to cope with the demands of the banks of tomorrow. Increasingly tech-savvy and sophisticated criminals combined with fast-paced and multi-jurisdictional commercial environments will only increase the risks that outdated technology solutions struggle to manage today.
What AI means for financial institutions
The integration of AI into the financial sector will have many impacts. At the most rudimentary level, costs will be reduced as efficiency increases. Computers digest much more information than humans whilst making fewer mistakes. Allowing for a better analysis of data and greater scalability of systems.
Augmented decision making will be a key use of AI in finance. It will allow analysts to make complex decisions with the help of machines which offer both pre and post decision making support, generated by analyzing historic data and emerging trends. These augmented decisions will be increasingly important as financial products become more complex and as more and more data is produced.
Going forward AI will be crucial in the development of predictive analytics for customer and market behavior which will create more accurate risk management solutions.
What AI doesn’t mean for financial institutions
It is often claimed that AI will lead to huge swathes of society losing their jobs, but this is unlikely to be the case. The use of AI in financial institutions will mean that some tasks become automated resulting in roles being altered, but not necessarily removed. Simple tasks will be carried out by machines leaving workers to perform higher quality tasks which are not only more interesting but also add more value to their companies. That being said, over time as some teams become higher skilled, companies will be able to reduce the required headcount for low-level jobs.
And it is important to remember that while more tasks may be given over to machines human beings will not be absolved of responsibility for their actions. The outcomes of decisions made by intelligent machines will still sit with those who programmed them. Maintaining the need for answerable human oversight of the sector.
How AI can be used to improve compliance
Business functions such as compliance, which historically rely on rules-based systems, are ripe for the use of AI. This has been a key driver of recent innovations in regulatory technologies (RegTech). Rules-based systems produce large quantities of “noise” – vast amounts of unstructured and mostly irrelevant information which humans need to manually review, creating a considerable mundane burden for even the largest of compliance teams. By automating simple tasks like real-time scanning of changes to Sanctions and Watchlists workloads can be significantly reduced. Smart systems that learn from your decisions can also dramatically reduce the number of ‘false positives’ (incorrect risk alerts) produced by searches, in some cases by as much as 60%.
ComplyAdvantage is using AI and machine learning to create better AML data and more intelligent technology. Our proprietary dynamic global database of individuals, organizations and their connections that pose financial crime risks, provides more accurate, structured data and insights. Our screening platform helps automate the process for deciding the level of financial crime risk that a customer or transaction poses so compliance professionals can make decisions faster. Our powerful search tools have intelligent, adjustable ‘fuzzy matching’ that automatically identifies non-exact matches like known aliases, alternative spellings, transliteration between languages, variations of name structures – to make sure nothing slips through the net.
We also monitor those linked to criminal activity in the media. Our advanced technologies can understand the context of huge amounts of data and identify risk signals, scanning and analyzing over 5 million articles, blogs and other types of media each day for financial crime risk.
Insurance and AI, the next big industry evolution?
Insurance is the most recent industry to receive the ‘Tech treatment’. InsurTech is quickly developing as companies identify the best ways artificial intelligence could be used to improve the industry. At FinTech Connect speakers said that this would initially take the form of using chatbots and virtual brokers to improve customer engagement and services. At ComplyAdvantage we work with various insurance companies who have embraced RegTech to make their compliance obligations much more streamlined, reaping the same increases in efficiency as the banking sector. Looking to the future the use of AI in insurance could be even more transformative.
InsurTech could be used to significantly reduce the level of insurance fraud. By digitizing the claims process not only will it be easier for customer to make claims but during assessment computers will be able to make estimations that are more accurate and that identify fraud at an earlier stage. AI in insurance will also be used to spot suspicious behavioral patterns which could signify fraudulent activity, Shift Technology is one such company using AI for this exact purpose. The use of smart systems in insurance is still very much in its infancy but is definitely a field to watch.
AI has and will have a big impact on the way we all live our lives, embracing these changes will allow humans and machines to work together for a smarter and more efficient future.