In my last two posts, I've defined what composable banking is and its potential scope. In both these posts, I've highlighted BIAN as a way of defining the composable modules. One thing I'd like to add though is that BIAN represents the business model of banking first and then how it can be supported by technology. It's not about the modularisation of software components that can be easily interchanged, it is very much about creating flexibility and agility in banking by creating a canonical representation of the business of banking. The biggest challenge for any bank is how do they reach such a vision of composable banking when over decades of investment in technology automation they have hundreds or thousands of systems, with some sharing data through extraction, some integrated through technical bridges and maybe a few more modern solutions through APIs?

The race is on to reduce fraud and continue improving payment flows. Artificial intelligence (AI) offers a winning strategy, says Chalapathy Neti, head, AI and machine learning platform, Swift. AI is out of the lab and already well on its way to delivering smarter tech solutions in our daily lives. Just look at the way Amazon and Netflix use machine learning algorithms to continually serve us fresh content and products based on our previous behaviours. We get a better, more personalised experience while they strengthen their business models.

Artificial intelligence (AI) is fast becoming an essential tool for the financial services industry. According to Insider Intelligence's AI in Banking report, most banks (80%) are highly aware of the potential benefits presented by AI. The opportunities in this space are legion, but AI solutions require careful governance, with the right checks and balances in place to ensure that they are robust and fair. The scope of possible uses for AI and machine learning in finance stretches across business functions and sectors. In the financial services space alone, AI tools are already used to refine customer service, client segmentation, fraud prevention and loan assessment, to name just a few.

It seems that the world is gradually turning everything into data, and we are storing data at lightspeed. How are banks capitalising on new sources of data and using it to develop new services? Our watches now track our sleep, our movement, our heart rate and much more. With it they can "coach" us with training plans that are specific to our individual capabilities. At the top end of smartwatches, you have the ability to pay for things, listen to music, get guided GPS navigation and more.

Not only is technological innovation unfolding at breakneck pace, but the reach of its influence is exponentially expanding as well. Digitalisation is disrupting a broad swath of industries, and finance is no exception. With new financial technology start-ups reimagining banking and accounting, CFOs from companies across every industry have been empowered to change how they work, and often for the better. But in financial services, as in any industry touched by the spark of technology, questions remain – how much will technology influence the future of finance? To what extent will automation dominate the financial field?

The banking sector's digital transformation journey has come a long way over the past five years. Today, technologies like machine learning (ML) and artificial intelligence (AI) are becoming much more commonplace in banks' digital strategies. Until the arrival of challenger banks like Monzo and Starling Bank a little over five years ago, who showed the benefits that taking a digital-first approach could bring, traditional banks failed to adopt the digital transformation at the same speed as other sectors. While the banking sector has come a long way in its digital journey in recent years, the slow pace of adoption initially has had a knock-on effect on the sector, with other industries now far more advanced in their digital approach. The industry was an early adopter of nascent technologies and as a result, it is now using ML to help with early detection of diseases like cancer. We conducted our own research into the banking industry's digital journey, to see where technologies like AI and ML were being used and, crucially, where they were not.

Since the start of the COVID-19 crisis, the number of fraud cases have continued to grow. In late June, over £16 million was lost to online shopping fraud during lockdown according to Action Fraud. From posing as government officials to online TV subscription services, fraudsters are trying every way they can to entice people for their personal details and prey on their hard-earned savings. Now, the latest weapon fraudsters are adding to their arsenal is synthetic identity fraud. Fraudsters are turning to synthetic identities to open new accounts.

Whether you envisage self-driving vehicles to be five or 25 years away, given the substantial investments and technological progress being made, it is hard to argue against the industry's narrative of inevitability. Not to be outdone in this digital age, insurance claims is forging its own digital transformation path, leveraging advancements in technology and analytics to inject automation into the claim process. So how far away are we from delivering claim processing that is automated end-to-end? Will this happen before driverless Ubers are roaming the streets?

Is your company ready and willing to pursue artificial intelligence (AI)? Companies at the forefront of pursuing this long-hyped technology will have an advantage that later movers may never be able to overcome. This new research from Harvard Business Review Analytic Services explains how to move past the hype and lay a true foundation for AI. The good news is that you don't need to be a large, tech-forward enterprise to win the AI race. You just need to be smart about where to start.

Sophie Guibaud, Fidor Bank: AI is on! Implementation of first uses cases around real-time contextual added-value banking notifications and offers will make their appearance in 2018, predicts Sophie Guibaud, vice-president for European expansion at Fidor Bank. Artificial intelligence (AI) is beginning to make some real inroads into the consumer banking experience. While some might have dismissed it as a gimmick a year ago, there's no doubt that AI is going to used more and more by banks into 2018. What's more, it won't just be used in the customer-facing services at the front end, but at the back end too, helping banks to make better use of the data they have.