Artificial intelligence is one of the critical technologies that is transforming banking and finance to help institutions and consumers in a variety of ways. The automation capabilities it provides can help to save time and boost revenue while identifying fraudulent activities and risk factors that may escape manual review. This process adds value for customers in the industry because it makes it safer and easier to manage wealth and investments.
According to Deltec Bank, Bahamas – “Machine models have a unique capability of analyzing significant databases in structured and unstructured supervision to improve analytical abilities. “This advantage enables risk managers in financial institutions to spot potential problems in a timely and efficient manner, leading to empowered choices that make it less risky to engage with industry services.
Artificial intelligence applications in the banking and finance ecosystem can identify connections and patterns that escape human review, augmenting processes while creating more opportunities to improve scalability. Digital identity systems, chatbots, machine learning blockchain, and more technologies in this area ensure accuracy and transparency so that trust can build between the institution and their clientele.
Artificial Intelligence Can Still Give Banks a Competitive Edge
Although AI implementation has been a priority for the banking and finance sectors since 2010, only 32% of executives in these industries say that they’ve used artificial intelligence features like recommendation engines, predictive analytics, voice recognition, and automated response. The institutions that are using this technology to improve their interactions with customers stay focused on payments or other card-based activities.
Chatbots are the most visible tool that the banking and finance sector uses to reduce risk factors when customers open new accounts or request financial products. These intelligent virtual assistants handle a standardized set of questions or comments to automate many of the repetitive functions that humans used to perform. Advanced programming can review a client’s account to provide customized investment or saving recommendations that can lead to wealth management.
AI can also analyze millions of transactions in minutes to detect patterns in purchasing behaviors. If an abnormality occurs in a specific profile, then the technology can stop the operation from happening until an authorization check occurs. The customer receives a text or email, asking if they are the ones who initiated the request. If they are, then a simple tap on a smartphone can release the funds. When it is an unauthorized activity, then the institution can move quickly to stop that illegal behavior.
AI Works on Real-Time Facts Instead of Demographic Insights
When the Great Recession hit in 2008, many financial analysts were caught off-guard by the events because the outcome was different than the data that the banking and finance sector collected. Before artificial intelligence was available to the industry, customer intelligence was built on the use of focus groups, behavior surveys, and simple heuristics. Individual behavior didn’t always correspond to the proposed risk realities, which eventually led to markets collapsing.
Artificial intelligence can use previously collected data as part of its calculation matrix to determine risk, but it also uses real-time information to create a customized approach for each customer. Software integrations can assess a credit profile, leverage social media photographs, and check-ins, review GPS logs, and evaluate online purchases to determine if a bill-payment history is accurate or not.
“Banks can use cognitive technologies like AI to gain a competitive edge because it handles and evaluates unstructured data accurately,” says Deltec Bank – Bahamas.
There Isn’t a Fixed Definition of AI Maturity to Use
Artificial intelligence offers a lot of potentials, but the approaches that the banking and finance sector use to implement it are closer to being experimental than mature. There isn’t one fixed definition of AI maturity that currently works in all contexts. Metrics and geographies can be gleaned through deployment, diffusion, and standardization in a variety of settings, which is why the implementation is more of a patchwork of systems instead of a concise approach.
It isn’t good enough to group people into “yes” and “no” categories from a financial perspective. AI can use information about the loan repayment habits of individuals and businesses, the number of open accounts, existing credit lines, and similar data to develop a customized risk profile that leads to a unique interest rate. What works for one lender might not be suitable for another, enabling consumers to speak with different institutions in a competitive landscape that wouldn’t be possible without artificial intelligence.
AI transforms risk analysis by taking an efficient approach to trading processes that can look at past data patterns to create accurate predictions for future activities. Anomalies can exist in these databases, but it is also possible to teach artificial intelligence through machine learning to understand what could trigger potential problems to plan for them. Even an investor with a high-risk approach to their portfolio can rely on this technology to make acceptable recommendations for when to buy, sell, or hold items.
AI Makes It Easier to Manage Finance Risks
Some people can manage a personal budget with skill and certainty. Then there are the households that don’t even look at the balances in their accounts, choosing to keep spending until a denial occurs at a merchant. Artificial intelligence can manage risk in this area because it can alert people to low balances, unusual spending behaviors, and other activities that happen outside of the usual routine. Some startups use this tech to create spending graphs for consumers to develop a better understanding of personal choices.
Instead of trying to decipher lengthy spreadsheets or complicated financial processes, consumers can let AI do that work on their behalf. Then banks can see improvements to spending profiles and react accordingly. It creates new opportunities to meet needs on both ends of the lending and investment spectrum while building in risk-reduction actions that can limit potential losses. This approach leads to more intelligent trading, improved customer interactions with institutions, and added trust in each relationship – and that combination of factors leads to more wealth as time passes for everyone.
Disclaimer: The author of this text, Robin Trehan, has an Undergraduate degree in economics, Masters in international business and finance and MBA in electronic business. Trehan is Senior VP at Deltec International www.deltecbank.com. The views, thoughts, and opinions expressed in this text are solely the views of the author, and not necessarily reflecting the views of Deltec International Group, its subsidiaries and/or employees.
About Deltec Bank
Headquartered in The Bahamas, Deltec is an independent financial services group that delivers bespoke solutions to meet clients’ unique needs. The Deltec group of companies includes Deltec Bank & Trust Limited, Deltec Fund Services Limited, and Deltec Investment Advisers Limited, Deltec Securities Ltd. and Long Cay Captive Management.