How Can AI Improve the Way Financial Services Are Managed?
AI and financial services have not always gone hand in hand. In fact, only recently has Artificial Intelligence been equated with real-world applications. No longer a mere concept or, at best, the symbol of a hope for a more tech-centric future, AI is here for good. It is now appealing to business owners and executive managers who are exploring its use in several areas, including finance. We have reached a point where this technology is involved in various aspects of our lives and changing many things for the better. Here are a few examples of the positive impact AI has on the financial industry.
The Central Role of Explainable AI in Financial Services
In an effort to increase revenue for actors in the industry of financial services, experts such as Dreamquark have developed solutions based on Explainable AI. This is the key component in the implementation of AI technology in FinTech because it elucidates the rationale behind its decision-making. Where explainability used to be an afterthought of the AI integration process, the need for more transparency now cannot be overstated, especially in such a sensitive area as that of finance. It has allowed the gradual deployment of AI in financial services and continues to consolidate its relevance.
One area in particular where the “thought process” of AI needs to be perfectly understood for it to be trustworthy is credit decisions. If lenders can be assured of its objectivity, they can then trust AI-based credit scoring to distinguish between loan applicants in a completely unbiased manner. Banks can automatise the process of issuing loans and put convenient apps at their clients’ disposal, which they can use to evaluate their eligibility. The transparency of the program’s decision even discloses the exact reasons why applicants are rejected, giving them all the information they need to improve their credit score.
As far as risk management is concerned, the impact of AI in financial services is also very significant. The most efficient way to manage the structure and unstructured data is undoubtedly cognitive computing because the amount of time it would take a human being to review such amounts of information would make it utterly impractical. By the time the analysis is complete, it would no longer even be relevant! Thanks to the immense processing power of Artificial Intelligence, the history of risk cases is analysed by algorithms which study real-time activities in any given environment or market to make dependable predictions.
Unsurprisingly, the insights provided by AI in financial services also encompass fraud detection. Based on the study of clients’ purchasing habits, location, and general behaviour, security systems can be triggered as soon as uncharacteristic patterns are identified. Similarly, intelligent machines can recognise suspicious activities and identify risks of money laundering very effectively. Fraud-detection systems are complex, but thanks to explainable AI, their deduction process is entirely transparent.
Customer satisfaction is at the heart of banking offerings which combine AI and financial services to provide additional comfort and benefits to their users. The chatbots we have come to not only accept but also appreciate are all powered by AI, thus reducing the workload – and therefore wait time – in call centres. As evidenced by the rise in the adoption of virtual assistants, consumers are starting to fully embrace the personalised experience these bots offer. From simple banking operations all the way to financial advice, these systems are capable of tracking recurring expenses, income, and spending habits to create optimised financial plans.
All these uses of AI in financial services are only the tip of the iceberg! In coming years, we can expect artificial intelligence to continue to make banking practices more transparent and reliable.