21 August 2019

Data Analytics, Artificial Intelligence and Big Data in Banking and Financial Services

62% of Banks agree that Big Data solutions are critical to their success, according to the Global Transaction Banking White Paper. However, only 29% say they get enough business value from data. This happens because financial entities need to rethink operations and adopt data-based approaches if they want to remain competitive.

According to McKinsey, using data to make decisions can save to 15-20% of your marketing budget. Given these banks spend an average of 8% of global marketing budgets, using Big Data is excellent for reducing costs and generating additional revenue through highly targeted marketing strategies.

In an Era of constant technological advances, where data is growing exponentially and we are dealing with a substantially informed and demanding consumer, Banking and Financial Services organizations feel, therefore, the need to reinvent themselves and adapt to this disruptive new digital world, in order to respond to an increasingly competitive market and to avoid eventual mistakes which may have committed in the past.

The banking sector is by excellence a sector that produces a wide amount of data, many of it is sensitive, in fact, according to Capgemini, 74% of Millennials are willing to share personal data with the banks, compared with only 49% of the public over 55.

Also, the pressure on banks and financial services to remain profitable is enormous, and analysing this huge amount of data to understand the customer better, is undoubtedly a critical success factor.

A quick and accurate overview of financial data, knowledge of customer behaviour and needs, or effective risk analysis, are just some of the advantages offered by Banking and Financial Services. However, the truth is, the synergy between Big Data and Analytics combined with Artificial Intelligence, brings unprecedented benefits to any industry with a significant increase in performance and in operating costs reduction.

To increase performance and to staying competitive, Banking and Financial services can also resort to data analysis to extract clever insights and forecasts, as well as transactions, frauds, market trends and internal and customers risk management. The insights generated from this data, enable to improve the way how banks segment, analyse and retain customers and create new service offerings.

Through Artificial Intelligence (AI) financial institutions gain a greater competitive advantage. In terms of customers experience, chatbots are the most visible form of AI in the industry, offering customers the convenience of accurately solving issues, anywhere and anytime. Presently, the chatbots can recognize tens of thousands of common questions that a customer will ask. AI also has a positive impact on task profitability by absorbing the most monotonous and repetitive task, leaving employees with more rewarding and high-value roles.

According to IDC, investment in Artificial Intelligence will reach 3 billion of dollars in West Europe as early as 2019 and will reach over 10 billion by 2022. Banking and Retail are at the top of the main sectors, which invest the most in this area. Investment in the financial industry is helping organizations to detect illegal acts in customers’ accounts and distinguish genuine from fraudulent transactions, which can not only cause reputational damage but also, significant financial loss.

Using Big Data in the banking industry will help recommend immediate actions, such as blocking irregular transactions, which prevents fraud before it happens and improves profitability.

Also, nowadays, no one has time to go to a physical bank. The customer wants to interact with the bank anytime and anywhere through available tools. The internet and mobile have become the natural way to engage in a series of interactions with the bank, that force traditional banking to digitally transform itself through innovative customer-focused strategies and a personalized and optimized offering.

As a result of the digital transformation, entities offer an integrated multichannel experience, gathering data in real-time and using the information to gain customer insight for a more personalized offering.

According to the IBM’S 2010 Global Chief Executive Officer study, 89% of banking and finance CEOs, say their top priority is to understand, predict and give customers what they want. Financial metrics and KPIs provide effective measures to summarize the bank’s overall performance and become quickly available and easily through intuitive reports.

While data analysis is not a new topic in the industry, regulatory reforms, risk management changes, expansion into new markets and a focus on profitability bring new considerations to top management.

Advanced Analytics combined with Artificial Intelligence can help to make significant improvements in your day-to-day, accelerate growth and predict your organizations’ losses. By streamlining processes, any entity can use algorithms to understand different counters needs across the country or optimize routes to save costs.

In-depth analysis of historical and current market data provides sophisticated trend data and predictions of market behaviour. These models facilitate faster, more informed and more effective decision making.

As we have seen, having the right technology allows to redefine processes, create new products and services, automate functions and transform relationships with customers and employees.