Since the financial crisis of 2008, commercial banking has undergone a monumental change in regulatory reform to manage and mitigate operational risk. This transformation has been combined with an increased focus on improving efficiency, profitability and shareholder value across the company.
Established regulations such as Dodd-Frank, Sarbanes-Oxley (SOX), Basel II (superseded by Basel III), and the upcoming MiFID II release, seek to add to and improve the way banks protect themselves against governance threats, risk and compliance (GRC).
The data that is currently stored is already being interrogated using machine learning, bots, virtual assistants, and artificial intelligence (AI). This data has immense power that can be harnessed to achieve greater efficiency, and this trend will continue to evolve for years to come. Several of the world’s leading commercial banks are investing significantly in this area and those who continue on this automation journey are expected to gain a technological competitive advantage.
Recent examples of this include JPMorgan’s program, called COIN (Contract Intelligence), which does the repetitive work of interpreting commercial loan agreements; this process previously consumed 360,000 hours of lawyers’ time per year. The software reviews documents in seconds, is less prone to errors, and never takes time off for vacations or breaks; All of this makes solid business sense and helps lower costs and increase profits.
CaixaBank is also maximizing the use of IBM’s Watson to streamline processes. Pere Nebot, CIO, considers this investment to be valuable: “Connective computing is the new trend in commercial banking technology and, in my opinion, this will change the interactions between clients and the bank and make life easier. Our Connection architecture with Watson will allow us to work smarter and better serve our customers. ” The output of artificial intelligence systems like Watson, with the help of document automation software, has the ability to create and deliver a seamless process for the accurate generation of business-critical loan documents.
Many of the world’s leading banks have grown exponentially in recent decades, through global expansions, acquisitions, and mergers, and the processes that oversee governance have become somewhat uncoordinated and inefficient. This view is supported by a PwC report which states that, “While several banks have begun the business loan transformation process, some have not focused on the data strategy that is needed to meet reporting requirements. emerging regulations profitably … an inefficient commercial loan origination capacity and related data environment will put the bank at a competitive disadvantage. “
Commercial banks operate in a data-driven world, which in turn leaves data accuracy as a potential exposure area and a weak link in the first line of defense in risk management. Process automation in data and documentation output provides a seamless path for companies to save money, increase accuracy, and streamline processes, thereby reducing risk. According to the British Banking Association: Operational risk in market-related activities can arise from many sources, such as poor or inefficient data management, systems and processes. “
The real value of “Big Data” lies in how you analyze and generate specific customer data for better results. This acts as a cornerstone in risk management and has the power to change the point of view from “garbage in, garbage out” to “quality in, quality out” with a clean and standardized output format.
In turn, this helps Basel II and SOX compliance, in terms of execution and reduction of data entry errors by having better management of delivery and business processes. It is of the utmost importance that the validity of the information and the quality of the data are not compromised during processing and output, as the financial and reputational repercussions here are enormous.
Some of the world’s most recognized banking leaders have echoed the view that innovation in software and new technologies has the power to make commercial banking more competent. Ralph Hamers, CEO of ING, states that: “If you are the first to move and break, you will lose some revenue on the one hand, but you will be able to grow more aggressively. The changes we have made have allowed us to process faster responses to credit applications, which improves the service we provide to customers. “
Several challenging banks (such as Metro Bank and Aldermore) continue to disrupt the banking environment by gaining more market share, keeping larger companies on their toes and driving innovation and efficiency across the banking sector.
Improving business processes with document automation has the power to propel even the largest and most established commercial banks to a position of strategic competitive advantage. This focus on document quality as a cornerstone of GRC, particularly in such a data-rich industry, should help offset at least some of the scrutiny of the last decade.