The idea of leveraging artificial intelligence (AI) for enterprise automation and transformation is creating shockwaves within the business world. In this blog post by AICoreSpot, we will delve into the issues of retail, tech, and healthcare heavyweights adopting and harnessing bleeding-edge technologies. Another field where AI illustrates its massive transformational potential is within the domains of banking and finance.

Regardless of whether it’s a startup or a well-established enterprise, those businesses that harness and go about implementing artificial intelligence to enhance in-house processes and external contacting with clients or partners are treading in the correct direction. Raconteur observes in the “AI for Business 2019” report that the financial sector makes up 18% of all artificial intelligence startups. It is the second-largest domain for startups following health and well being.

Also, making investments in artificial intelligence by financial institutions is poised to appreciate to unprecedented levels over the next few years. Taking up artificial intelligence will become a crucial requirement for enterprises to stand out in a harshly competitive market.

Through deploying artificial intelligence in the finance sector, enterprise owners can unveil a few methods to upstage competition via enhanced client experiences. Conventional finance services enterprises in the present day focus more attention on client experience issues.

Going by Accenture research, Artificial Intelligence will totally redefine financial services provision. It can guarantee well-structured cooperation with clients, enhance the security level of financial transactions, drive risk administration, develop new products and services, and revolutionize the client experience.

As an owner of an enterprise, you are required to be certain your business will be successful in enhancing client experience. Therefore, you require to mention processes and services where Artificial Intelligence can have a dominant influence.

Finextra, web analytics and statistics, have furnished valuable information with regards to the matter. The discovered that in upcoming half-a-decade artificial intelligence in the domains of fraud prevention, risk administration, personalized insights, and anti-money laundering will provide tangible outcomes. 52% of respondents concurred on that, and 32% stated that AI is bound to disrupt these domains. So, let’s find out what enterprises of differing sizes can leverage.

Perks of AI in Finance ranges from Back Office to Client Interactions

Concentrating on enhancing process efficiency and minimize expenditure, enterprises are looking to make use of artificial intelligence within accounting and finance. Specialists from Business Insider reckon expenditure-saving opportunities that AI can furnish to banks, tax agencies, or credit unions at $447 billion in two years time from now.

Finextra’s research indicates that implementing of artificial intelligence technologies will help in mitigating fraud and risks by approximately 70% and more.

It will also assist in enhancing client retention by up to 68%. The visual below displays the advantages that companies can obtain through implementation of AI solutions.

Several advantages could be obtained from automation of data-driven processes and outsourcing problems with regards to client experience to AI algorithms. It is critical to be aware that a few of the most meaningful AI applications within finance to accomplish strategic business objectives.

1. AI Biometrics Technology within Finance

Information security and access control are a critical aspect of developing an improved client experience. AI drives biometric identification and recognition solutions, like face recognition, voice recognition, and fingerprint recognition.

Facial recognition algorithms go about verifying/authenticating a person by taking facial features from imagery or videos and contrasting it to faces available within datasets. The technology assists in detection of fraud in a timely manner can be leveraged to make sure the required level of security for both online services and within offices. Such biometric authentication is a safeguarding measure which is poised to be broadly leveraged across the financial services industry.

Machine learning (ML) technology facilitates machines to identify voices on the basis of such traits as articulation, pitch, tone, and so on. Voice recognition systems develop and record a unique “voiceprint”. It can be further leveraged rather than or in conjunction with a password for making the user authorization process very secure and smooth.

Fingerprint recognition is a widespread measure. It needs massive amounts of data so that AI-driven systems can contrast and match user fingerprints.

2. Smart utilities to personalize insights

AI-based financial tools like the one put forth by MX, a major financial services provider, can help clients in finding solutions to complex financial issues. With minimal or nil human involvement machines can furnish financial advice, drive improved decision making and enhance client retention.

Financial enterprises, mainly banks and debt collection organizations, will be capable of forecasting their client’s behaviour more accurately and apply a more personalized approach to every client.”

AI can assist in enhancing client loyalty and develop a competitive edge. That is what harnessing big data can provide to enterprises within the niche of finance.

3. Risk administration and anti-money laundering

Raconteur indicates that 40% of use cases of AI deployment in finance are in relation to risk administration. AI can take responsibility for several business processes that need working with big datasets. It will have the outcome of improved forecasting decision outcomes, mapping out various ways with regards to development, and assisting enterprises choose the best adapted strategies and techniques to reduce organizational and business-oriented risks.

To react in a quicker way to fraud and protect their clients, financial enterprises require to go about implementing innovative Artificial Intelligence solutions. Machine learning and deep learning technologies were demonstrated to be very efficient in both preventing and investigating illegal financial activities. These algorithms are founded on the basis of supervised learning, a variant of model training approach that consists of human reviewing of the output. ML-driven solutions can operate with alerts, sift through massive datasets, or conduct analyses of dubious transactions within a fraction of the time prior taken and with an increased degree of precision.

4. Modifications to the loan system

The influence of Artificial Intelligence within finance extends additionally to lending and loan administration. AI solutions assist banks significantly save time on lending protocol and minimize running expenditure. The analysis of forms can be automated, and human staff members will require to review the outcomes.

The automated analysis of client personal information will provide additional perks. It consists of fraud detection, minimized credit loss, minimized write-offs, and enhanced client satisfaction rate.

For instance, JPMorgan Chase, a US-based financial services enterprise, has taken up artificial intelligence to undertake analysis and processing of commercial credit agreements. They estimated that manual review of 12,000 contracts needs up to 360,000 hours, whereas ML-driven systems review the same amount in seconds. It illustrates the great prospects AI tools hold to make in-house operations time- and cost-effective and enhance customer engagement.

5. Support Ticket Processing

Processing client queries is a real hurdle for support services to overcome. When a support ticket is received, it goes through various stages prior to the correct person can tackle the issue. Several routine efforts have the outcome of bottlenecks and below-average client experience.

Salesforce discovered that 64% of clients and 80% of enterprise buyers expect real-time communications and responses from a provider business. Implementing AI for managing support tickets is the way to obtain an improved understanding of client requirements and surpass expectations. An AI-based solution facilitates the automation of routine ticket and query processing activities and complete or partial elimination of human involvement in the process.

The leveraging of natural language processing (NLP) enables machines to “read” and “comprehend” support tickets in a human-like manner. These ML strategies such as sentiment analysis, ticket categorization, keyword analyser can assist tailor a custom solution to particular support service requirements. AI-driven solutions are scalable and can help accomplish up to complete automation dependent on the nature of the business process.

These are the best ways your enterprise can accomplish and maintain a competitive edge. By choosing AI development services and a custom-made AI-led solution, you choose to concentrate on your customer’s expectations and developing a lasting client experience.