Finance has the lowest AI-maturity, but will soon leap-frog

Babak Vahidi, Chief AI Officer, Blingdale

We pour a freshly brewed cup of Java and hit the couch for an Interview with Babak – guitarist and instrument hoarder, but also our company groups new AI officer. We want to find out what his thoughts are on the evolution of AI and finance, risks and proprietary vs. open source.

For me the sweet spot is working between tech and business, and I really enjoy being a bridge between these areas.

Babak has a background in computer science and innovation management. He loves challenging preconceived ideas and combining it with creativity and disruption, which is one of the reasons why he first got interested in Quiddly and our group company Blingdale.

I’ve always been impressed by how every time I check in with Blingdale something new and big has happened. Now that I’ve been here for a while I can see why. There is always a buzz at the office. Lots of talented people with different backgrounds turn up excited each morning.

Different types of AI and Industries

Before Large Language Models made its entry there was a lot of talk about transportation being the next area that would be disrupted by AI with self-driving vehicles. Autonomous vehicles are becoming reality, and it will expand rapidly the coming years. But it is apparent that Large Language Models will change many industries and automate a lot of tasks.

The interesting thing is that LLMs could be used both to automate time-consuming work, but also fuel creatively and analytical thinking, as such it will be a natural part of our workday and will help us to progress much faster. I think that most companies, whether a tech-company or a restaurant will realize the benefit of AI. Many will start to apply strategies to increase their maturity.

ChatGPT made an impressive entry, but the question is if it will be able to make the same rapid improvement as the previous couple of years. Babak talks about that there will be other parts of generative AI that probably will go through even bigger changes, and that we will see better models of both audio and video generation.

But what about our area of expertise; finance? According to a recent Accenture report, Finance is one of the industries with lowest AI-maturity index (a measurement that show how organizations mastered AI-capabilities to create value). But at the same time finance is predicted to leap-frog that position in 2025.

Areas such as risk management, customer relationship management, cashflow management, trading, regulatory compliance and fraud prevention are just some of the few areas that will see the benefit of AI.

AI for B2B credits and factoring

When it comes to factoring and credits in general, one central point is the risk assessment. Calculating credit risk and credit score has traditionally been a complex task. The results can often be imprecise. AI can help with the process by analysing vast and different datasets, connect the dots and find hidden patterns. This empowers companies to make more well-informed decisions when extending credit.

AI also offers solutions to time-consuming tasks, like extracting relevant information from invoices which historically demanded manual effort.

AI for Debt collection

Debt collection is another area where AI is transforming the business by analysing a range of factors and taking the most optimal decision in relation to speeding up processes and improving collection rates.

AI can determine the most effective communication channel for each debtor, create personalized messages, and pinpoint the best moment for contact.

AI for Invoice service

AI-powered solutions can tackle many different challenges for invoicing. One example is mismatches between payments and invoices due to errors like incorrect payment IDs or amounts. AI can identify these discrepancies and save a lot of manual work.

AI can also be used to generate a personalized message which in turns increase the likelihood of the payment being paid in time and improves customer relationship and experience.

The trillion-dollar question: proprietary or open source?

As in most software niches the question about proprietary vs. open source is also very much relevant when it comes to AI. We ask Babak what he thinks will benefit the evolution of AI the most. It seems like the answer is a combination of both types, at least in the foreseeable future.

Large companies such as Google, Baidu, Facebook, and Microsoft have invested heavily in AI research programs which has undeniably contributed to significant advancements in the field. The research is open which has led to recent years advancement in AI.

For instance, the foundation of ChatGPT, developed by OpenAI, is rooted in Google’s 2017 research on Transformers. So far, we have benefited from having advancement as open-source, but that might change in the future. As AI becomes more powerful, there’s a possibility it could be misused for harmful purposes.

The risks with AI in the foreseeable future?

One significant concern is the potential risk for widespread misinformation amplified by AI algorithms. The displacement of jobs due to automation remains a real risk. There is also the question of accountability for AI decisions that pose an ethical challenge.

As AI systems make decisions that impact individuals and society, clarifying responsibility becomes crucial. Additionally, the potential misuse of AI in creating lethal products or technologies raises serious ethical considerations. Discussions around the risks of superintelligence have gained traction recently by some notable people. In turn, the European Union has introduced the AI Act, a proposal to regulate the use of AI.

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Categories for this post: Knowledge