Processing mortgage loans entails tons of paperwork, followed by an extensive waiting period for document verification that results in a tiresome customer experience. RPA (Robotic Process Automation) helps banks perform these routine tasks more efficiently allowing underwriters to focus on value-added tasks. With RPA, banks fight against fraud, reduce heavy expenses, and improve customer experience. Mortgage lenders need to scan through multiple documents to verify the borrower's ability to repay the loan. The massive volumes of documents and data scanned for authentication are quite overwhelming and draining, which is where RPA steps in.

The introduction of artificial intelligence in the banking sector makes banks efficient, helpful and more understanding. The growing impact of AI in this sector reduces operational costs, improves customer support and process automation. AI-based applications help banks by reducing costs thereby increasing productivity. Also, intelligent algorithms are able to spot inconsistency and fraudulent information in a matter of seconds. According to reports, nearly 80 percent of banks are aware of the potential benefits that AI presents to their sector.

Artificial intelligence (AI) technology has become a critical disruptor in almost every industry and banking is no exception. The introduction of AI in banking apps and services has made the sector more customer-centric and technologically relevant. AI-based systems can help banks reduce costs by increasing productivity and making decisions based on information unfathomable to a human agent. Also, intelligent algorithms are able to spot anomalies and fraudulent information in a matter of seconds. A report by Business Insider suggests that nearly 80% of banks are aware of the potential benefits that AI presents to their sector. Another report suggests that by 2023, banks are projected to save $447 billion by using AI apps.

Artificial intelligence (AI) technology has become a critical disruptor in almost every industry and banking is no exception. The introduction of AI in banking apps and services has made the sector more customer-centric and technologically relevant. AI-based systems can help banks reduce costs by increasing productivity and making decisions based on information unfathomable to a human agent. Also, intelligent algorithms are able to spot anomalies and fraudulent information in a matter of seconds. A report by Business Insider suggests that nearly 80% of banks are aware of the potential benefits that AI presents to their sector.

Anyone still doubting whether fintech is disrupting Chicago's financial services industry only needs to look at a handful of recent partnerships to see that innovative technology is necessary for large enterprises to stay competitive in an ever-evolving market, lest they become obsolete. Take the following inked deals, for example. Amount -- a digital credit solution provider -- partnered with TD Bank and HSBC last year to help the two large institutions streamline their personal loan services, reflecting a marketplace that grew by $21 billion in 2018 to a record high of $138 billion, according to credit reporting agency TransUnion. Meanwhile, AI-powered financial compliance solution Ascent recently partnered with global information tech company IBM to help banks and other financial entities meet changing regulatory requirements. These types of partnerships help banks and financial institutions react to market changes and prepare for the future of finance; namely, by giving consumers more of the seamless user experiences they're used to and leveraging AI to streamline manual regulatory processes, saving valuable time and resources.

One of the bigger trends in enterprise software has been the emergence of startups building tools to make the benefits of artificial intelligence technology more accessible to non-tech companies. Today, one that has built a platform to apply power of machine learning and natural language processing to massive documents of unstructured data has closed a round of funding as it finds strong demand for its approach. Eigen Technologies, a London-based startup whose machine learning engine helps banks and other businesses that need to extract information and insights from large and complex documents like contracts, is today announcing that it has raised $37 million in funding, a Series B that values the company at around $150 million – $180 million. The round was led by Lakestar and Dawn Capital, with Temasek and Goldman Sachs Growth Equity (which co-led its Series A) also participating. Eigen has now raised $55 million in total.

In the financial services industry, innovations such as faster payments, together with global regulations and regulatory bodies1 raise a significant question: Do existing risk-rule-based money laundering detection systems really work? Financial institutions may also wonder about the effectiveness of fraud detection, the danger of false positives, structural costs, and the impact on customer transaction experience. According to Gartner, "if money laundering were an economy, it would be the fifth largest in the world." Strikingly, the UN also estimates that the amount of money laundered annually is equivalent to 2-5% of the global GDP. Another report from the Heritage Foundation suggests that complying with anti-money laundering (AML) rules, which require hiring the right talent needed to file suspicious activity reports, costs U.S. companies alone as much as $8 billion a year.

With increasing diversity in the banking customers' age groups, needs, values, priorities and perspectives, banks interact with several'generations' of customers. Multigeneration banking evolved from the need for providing personalized and unique experiences to a variety of customer segments. Changing demographics, incomes, attitudes and behaviours along with instant availability of information have empowered the banking customer to demand better choice, high quality service, instant response and transparency. Banks are exploring super customized customer experience methodologies to retain existing customers and attract new ones. As a technology, AI has been helping banks interpret precise customer preferences to help them further personalize products and services.

Feedzai is announcing a $50 million Series C this morning led by an unnamed VC with additional capital from Sapphire Ventures. The six year old startup builds machine learning tools to help banks and merchants spot payment fraud. In today's rapidly maturing world of fintech, Feedzai is trying to thread the needle between turnkey solution and customizable platform. With 60 clients including major financial institutions like Capital One and Citi, Feedzai remains optimistic that allowing savvy customers to build on top of its service is the key to longevity. Feedzai's platform is specifically designed to help mitigate payment fraud.

Advances in Artificial Intelligence (AI) technology will enable simpler user interfaces, which will help banks create a more human-like customer experience. The technology has become efficient in gaining extensive data analytics and customer insights, which will help banks to create a more personalised customer experience, according to Aspect Software. Four in five bankers believe AI will "revolutionise" the way in which banks gather information as well as how they interact with their clients, said the Accenture Banking Technology Vision 2017 report as customers are looking for a fast, efficient solution to their queries. The new report revealed that AI will become the primary way banks interact with their customers within the next three years, according to three quarters of bankers surveyed and also found that, while the number of human interactions in bank branches or over the phone was falling and would continue to do so, the quality and importance of human contact would increase. Stephen Ball, SVP Sales, Europe and Africa at Aspect Software, suggests that as the banking world continues to change with the adoption of new technologies, and a growing number of'challenger banks' and fintech providers emerging to shake up the established order, traditional banks are responding by improving their customers' experience.