Best Practices for Implementing AI in Banking
December 18, 2020
Artificial intelligence technologies are increasingly integral to the world we live in and many large financial institutions have already started using AI.
The promises of AI are great, but understanding the considerations needed to build and implement AI within an organisation is challenging. Here, we explore how one would go about implementing AI in banking.
Artificial intelligence means something slightly different to everyone, from IT buzzword to the next great leap in technology. Sometimes it can feel like little more than an urban myth, only applied in the largest of enterprises. But however you think of it, AI is set to make a huge impact on the global economy, with PwC predicting a $15.7 trillion contribution by 2030.
Although thousands of businesses already have AI projects underway, many industry leaders are still talking about AI in the highest-level terms, making it difficult to define it – and its applications – in a practical way.
AI in banking
AI is augmenting human decision making and automating routine tasks. It presents the potential to help financial service organisations become more efficient, save time and money, and implement more personalised, omnichannel services for their customers and members.
By using machine learning to analyse big data sets, AI is helping companies:
- Monitor for online fraudulent activities in real-time
- Make faster and more informed lending decisions on customers
- Shorten the time is takes to complete compliance and regulatory tasks
According to the Cambridge Centre for Alternative Finance and the World Economic Forum, risk management is the usage domain with the highest current AI implementation rate in financial institutions (56%), followed by the generation of new revenue potential through new AI-enabled products and processes, adopted by 52%. However, firms expect the latter to become the most important usage area within two years.
Best practices for implementing AI in bankingFind the right balance between in-house solutions and collaborating with third-party providers.
For some companies, forays into AI won’t go beyond basic automation, aimed at making processes faster and more efficient. Others, however, are investing heavily in deep learning, machine learning and advanced AI technologies that can support increasingly sophisticated applications.
Major organisations have major budgets – and that makes them the ideal candidates for major AI investments. But that doesn’t mean they’re the only ones that can realise its potential. For smaller businesses, investing in AI is a brave move – but not an irresponsible one if approached with the right plan and partner.
And although some large organisations are completely committing to AI technologies, AI doesn’t have to be the heart of everything. There’s often a sense of “all or nothing” that can be off-putting to smaller organisations that don’t have the requirements or budgets for a large-scale AI rollout. But small AI projects can be hugely effective as standalone parts of an IT infrastructure – it’s about identifying the right places to apply AI for the biggest returns.
Prepare the workforce for Artificial Intelligence.
In the not so distant future, human employees and AI will work together to solve problems. While it’s unlikely that introducing AI will ‘kill off’ job roles, it’s common for these new technologies to change key parts of individuals’ roles. When starting an AI project, it’s important to communicate the impact to employees clearly, so they don’t feel like they’re being replaced, in fact, more jobs are likely to be created for AI and employee collaboration. AI will complement everyday decision making, helping people move from routine tasks to project-based work. For this to be effective, workforces should be re-organised and re-skilled to work with AI.
According to Accenture, banking executives say only 1 in 4 employees are ready to work with intelligent technologies, but banking employees do seem to find value in AI; 67% of them expect intelligent technologies to create opportunities for their work.
Stay connected with customers.
From predicting future issues to personalising recommendations, AI is helping customer service representatives improve their interactions with customers. In addition, AI is being used to resolve simple issues quickly and efficiently which frees up customer service representatives to help with more complicated questions or tasks.
However, while AI can ‘learn’ like humans, it still lacks emotional intelligence and empathy, which is an important part of customer service. Regular touchpoints and customer service surveys can help to ensure a continual feedback loop and maximize the customer-facing benefits of AI.
Take the long view on judging AI solutions’ success.
Even if you do fully commit to AI within your organisation, it doesn’t have to be a big-bang project that integrates new technologies into every process all at once. In fact, it’s much more effective to take small steps, each with a clear goal and performance indicator attached to it. It’s the best way to adopt AI without overspending or putting too much pressure on your time and personnel resources.
Companies will go into an AI project with an idea of the outcomes and benefits they’re looking for. But it’s important to always have an open mind and look for extra opportunities to find value from your implementation. Banks should keep a close eye on the business impacts of solutions they implement from the start to see how they track as they mature.
AI will continue to play an increasingly important role within the banking industry as the rewards outweigh the risks. Building the right solution, leveraging the skills available and solving the highest-priority problems for the financial institutions is key to success.
How we can help
Successful implementation of AI technology depends on already having strong and secure digital processes in place. Here at Acuant, our automated solutions support financial institutions in creating a smoother, safer onboarding experience for their customers.
Onboard up to 68% more customers than with traditional identity verification methods, using our single universal API, Sodium. One simple integration; a flexible 360° solution which is scalable and secure.
Book a demo today and see for yourself how powerful our suite of solutions are.