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Bank of America Merrill Lynch (BAML) has revealed that it is implementing enterprise software fintech HighRadius' artificial intelligence (AI) solution to speed up receivables reconciliation for the bank's large business clients. (Receivables refers to all debts and unsettled transactions owed to a company by its debtors and customers.)
Large companies with numerous customers often receive payments without accompanying contextual information, like which customer or debtor it's come from, or precisely what the payment is for, which makes balancing a company's books, i.e. reconciling, a lengthy and resource-intensive task.
HighRadius' solution uses AI, machine learning, and optical character recognition to identify a payer, match them to an uncontextualized payment, and match that to an open receivable. Moreover, it gives companies the option of sending an automatic prompt to customers whose debts are outstanding. By leveraging this solution, BAML aims to reduce costs for its large business clients.
The bank's move is the latest development in a growing trend of AI deployment by big banks. The world's leading banks are applying AI across a diverse range of business areas, of which receivables is only the latest. Banks are taking advantage of improvements in the technology's data-crunching abilities in spaces like credit scoring to improve their risk assessment methodologies, Nordnet is using the technology to boost its customer service, NatWest is deploying AI to improve its compliance procedures, and JPMorgan Chase announced it's using AI for automated trading at its European business in early August.
The wide range of areas where banks are already using AI indicates there are few aspects of their business that wouldn't benefit from the technology, and suggests we will see many more applications of it going forward.
What is less clear is which suppliers of the technology will come out on top. Significantly, in each of the use cases mentioned above, banks are leveraging an external suppliers' AI solution, rather than developing their own in-house, likely due to a dearth of tech talent and to keep costs low. To date, banks have been turning either to startups like HighRadius, James, and Recordsure, or to solutions from incumbent software providers like IBM, for their AI needs.
This means that, for now, it's unclear which of these camps will be able to secure a lead in this market. Ultimately, the most attractive AI solutions to banks will probably be those that have the most robust financial and data security features in place, so we will probably see both types of provider focusing heavily on security to gain a competitive lead.
Traditional consumer lenders, like banks and credit unions, have historically served segments of the population on which they can conduct robust risk assessments.
But the data they collect from these groups is limited and typically impossible to analyze in real time, preventing them from confirming the accuracy of their assessments. This restricts the demographic segments they can safely serve, and creates an inconvenient experience for potential borrowers.
This has hobbled legacy lenders at a time when alternative lending firms — which pride themselves on precision risk assessment and financial inclusion — are taking off. These rivals are starting to break into a huge untapped borrower market — some 64 million US consumers don’t have a conventional FICO score, and 10 million of those are prime or near-prime consumers.
Incumbents can get in on the game by tapping into new developments in the credit scoring space, like psychometric scoring, which use data besides borrowing history to measure creditworthiness, and by integrating new technologies, like artificial intelligence (AI), to improve the accuracy of conventional risk assessment methods. There are still risks attached to these cutting-edge methods and technologies, but if incumbent lenders are aware of them, and take steps to mitigate them, the payoff from implementing these new tools can be huge.
Maria Terekhova, research associate for BI Intelligence, Business Insider's premium research service, has put together a report on the digital disruption of credit scoring that:
- Outlines the drivers behind incumbent lenders' growing awareness and adoption of credit scoring disruptions.
- Looks at the current range of methods and technologies changing the face of credit scoring.
- Explains what incumbent lenders stand to gain by adopting these disruptions.
- Discusses the risks still attached to these disruptions, and how incumbents can manage them to reap the rewards.
- Gives an overview of what the credit scoring landscape of the future will look like, and how incumbents can prepare themselves to stay relevant.
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