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In the past, we have witnessed how traditional financial services transformed into 'Fintech,' owing to disruptive technologies such as the blockchain, Artificial Intelligence (AI), and the Internet of Things (IoT).

Fintech apps have become the new norm in the financial services industry. The role of AI in Fintech, in particular, is mind-boggling.

Do you know that financial institutions rapidly invest in creating and purchasing AI-based fintech products?

"AI in fintech investment is predicted to reach USD 22.6 billion globally by 2025, according to a recent Research and Markets prediction."

Artificial Intelligence in Fintech

Artificial intelligence is transforming the way we handle money in the financial sector. 

AI helps the financial industry streamline and optimize procedures across the board, from credit judgments to quantitative trading and financial risk management.

We've compiled a list of how AI is being used in finance and the organizations driving the charge.

Credit decisions

"According to a recent study, Customers prefer to pay using a debit or credit card 77% of the time, while only 12% choose cash."

Consumers value credit availability for various reasons, not the least of which is the availability of improved payment options.

To name a few things, having good credit can help you get better financing, find a job, and rent an apartment.

The loan and card acceptance process are more important than ever before, with many daily necessities depending on credit history.

Artificial intelligence (AI) solutions assist banks and credit lenders in making better underwriting judgments by including several indicators that more correctly analyze previously underrepresented consumers, such as millennials, in the credit decision-making process.

Here are some companies assisting the financial industry in rethinking the underwriting process.

Enova

Location: Chicago, IL

How it's using AI in Fintech: Enova created the Colossus platform, which uses AI and machine learning to give sophisticated analytics and technology to non-prime customers, businesses, and banks to help them make responsible loan decisions.

Industry impact: The Colossus problem assists customers in resolving real-world issues such as consumer emergency costs and small business bank loans without putting the lender or recipient in an unmanageable scenario.

Ocrolus

Location: New York, NY

How it's using AI in Fintech: Ocrolus develops intelligent automation software that enables organizations to make better lending decisions, ensuring that enterprises, organizations, and individuals have access to the capital they require to achieve their goals.

Mortgage lending, business lending, consumer lending, credit scoring, and KYC are among the focus areas for the machine learning-enabled platform, which examines bank records, pay stubs, tax papers, mortgage forms, invoices, and more evaluating loan eligibility.

Industry impact: Ocrolus makes verifying individual loan status easier and more egalitarian, with less invasiveness.

Risk Management

In the world of finance, time is money, but if the risk is not properly managed, it may be fatal. Accurate forecasting projections are critical to many firms' speed and security.

Machine learning is known as a subset of artificial intelligence, increasingly used in financial markets to generate more precise, nimble models. These forecasts aid financial professionals in identifying trends, identifying dangers, conserving manpower, and ensuring better data for future planning.

The businesses listed below are examples of how AI assists financial and banking sectors improve predictions and risk management.

Kensho technologies

Location: Cambridge, Massachusetts

How it's using AI in Fintech: Leading financial companies such as J.P. Morgan, Bank of America, Morgan Stanley, and S&P Global use Kensho's machine intelligence and data analytics.

Kensho's software combines cloud computing and natural language processing (NLP) to provide analytical answers. The company's technology can deliver simple English solutions to difficult financial questions.

Industry impact: According to a 2017 Forbes article, traders having access to Kensho's AI-powered database utilized the information to quickly predict a sustained collapse in the British pound in the days following Brexit. S&P Global announced in March 2018 that it has agreed to buy Kensho for $550 million.

Symphony AyasdiAI

Location: Menlopark, California

How it's using AI in Fintech: To handle difficult challenges, Ayasdi develops cloud-based and on-premises machine intelligence solutions for businesses and organizations.

Fintech organizations use Ayasdi to identify and manage risk, predict client wants, and even assist anti-money laundering processes.

Industry Impact: Ayasdi's anti-money laundering (AML) detection technologies assist banks in combating money laundering. The sheer volume of probes has put financial institutions under a lot of stress. According to Ayasdi, one big bank witnessed a 20% reduction in investigative volume after using the company's AML solution.

Quantitative trading

Quantitative trading is the technique of identifying patterns in massive data sets to make strategic transactions. In this form of trade, artificial intelligence is extremely useful.

Large, complicated data sets can be analyzed faster and more efficiently by AI-powered computers than by people. The algorithmic trading methods that result automate trades and save time.

The companies listed below are just a few examples of how artificial intelligence-enhanced technology is assisting financial institutions in making better transactions.

Canoe

Location: Newyork, NY

How it's using AI in Fintech: Canoe guarantees that alternative investment data is quickly acquired and retrieved by leveraging APIs, AI, and strong data science capabilities to ingest, validate, and provide critical data.

Industry impact: The first-of-its-kind solution streamlines data workflows and is infinitely scalable to accommodate clients of all sizes.

Alphasense

Location: NYC

How it's using AI in Fintech: AlphaSense is a finance-focused AI-powered search engine that serves clients such as banks, investment firms, and Fortune 500 organizations.

The platform uses natural language processing to evaluate keyword searches inside filings, transcripts, research, and news to uncover changes and trends in financial markets.

Industry impact: AlphaSense is useful to a wide range of financial experts, organizations, and businesses, and the platform is especially beneficial to brokers.

Through the search engine, brokers and traders can access SEC and global filings, earnings call transcripts, press announcements, and information on both private and public businesses.

AI in Banking

With today's digitally-savvy consumers, traditional banking isn't cutting it.

"According to an Accenture survey of 33,000 banking clients, 54 percent want tools to help them track their spending and make real-time adjustments. In addition, 41% are "very willing" to employ computer-generated financial advice."

Artificial intelligence (AI) assistants, like chatbots, employ natural language processing and artificial intelligence to create individualized financial advice and deliver fast, self-help consumer assistance.

Here are a few instances of firms utilizing artificial intelligence to learn from customers and improve the banking experience.

Kasisto

Location: NYC

How it's using AI in Fintech: Kasisto is the originator of KAI, a conversational AI platform used in the finance industry to improve customer experiences.

KAI assists banks in reducing call center volume by giving self-service options and solutions to customers. Furthermore, AI-powered chatbots provide customers with calculated advice and other daily financial decisions.

Industry impact: TD Bank Group has announced intentions to integrate Kasisto's technology into their mobile app, giving consumers real-time support and spending data.

Abe.ai

Location: Orlando, Florida

How it's using AI in Fintech: Abe AI is a virtual financial assistant that works with Google Home, SMS, Facebook, Amazon Alexa, the web, and mobile devices to make banking easier for customers.

From simple information and assistance inquiries to personal financial management and conversational banking, the assistant can help.

Industry impact: Abe introduced its smart financial chatbot for Slack in 2016. This app makes a budget, saving goals, and cost tracking easier.

Cybersecurity and Fraud Detection

Every day, users use online accounts and smartphone apps to transfer money, pay bills, deposit checks, trade stocks, and more, resulting in vast quantities of digital transactions.

Any bank or financial institution must now step up its cybersecurity and fraud detection efforts, and artificial intelligence plays an important role in bolstering online banking security.

Companies that provide AI-based cybersecurity solutions for big financial institutions are listed below.

Dark trace

Location: Cambridge, Massachusetts

How it's using AI in Fintech: Darktrace develops cybersecurity solutions for many businesses, including financial institutions.

The company's machine learning platform analyses network data and generate probability-based calculations, allowing it to spot suspicious activity before it causes harm to some of the world's major financial institutions.

Industry impact: Global financial software provider Ipreo used Darktrace to safeguard its customers from sophisticated cyber threats, according to a case study on the company's website. In real-time threat identification and defense against internal and external attacks, Ipreo experienced instant benefits.

Vectra AI

Location: San Jose, California

How it's using AI in Fintech: Cognito, an AI-powered cyber-threat identification and hunting tool is created by Vectra.

Vectra's software automates threat detection, discovers hidden attackers targeting financial institutions, speeds up event investigations, and even detects compromised data.

Industry impact: A Vectra case study describes how the company assisted a major stock exchange in preventing malware assaults. Cognito quickly found a security flaw in the exchange's authentication systems that would have gone unnoticed otherwise.

AI in Fintech: The Main Benefits for Industry

Now, let's look at the reasons why artificial intelligence and machine learning are becoming increasingly popular among fintech companies. What's in it for you, and what's in it for them? These advantages will provide you with some insight.

Before we begin, the Cambridge Centre for Alternative Finance has provided some statistical data on the major incentives for Fintech to adopt artificial intelligence. The client is still king, to be sure.

Higher User Engagement

AI systems monitor app users, respond to their questions quickly (chatbots), and collect user preferences and activity trends.

A sophisticated AI engine will know your clientele better than any company manager. Your company will always stay ahead of the competition if it understands what customers desire.

Optimized Workload

Fintech staff may use AI technologies to help them with mundane jobs, including answering common queries, classifying clients, and monitoring transactions and new laws.

While technology can manage and react to the slightest changes in the system, the human intellect can be used for more creative activities.

Reduced User Support Cost

In Fintech, AI and machine learning are available 24 hours a day, seven days a week to answer questions, and they get better over time as they understand common patterns and demands.

It reduces the danger of human error and lowers the cost of user support in the long run.

Secure Payments

Fintech and AI work together to enable continuous payment monitoring and user verification, bridging many security vulnerabilities that people are unaware of.

Artificial intelligence acts as a shield that no one sees but is always present.

Attention to Detail

With AI, you'll constantly be aware of what's going on in your company. This guideline applies to any data management task. What is missed by managers will never go unnoticed by tech tools.

The 2021 State of AI in Fintech

As per predictions, AI in the fintech market will grow at a CAGR of 23.17 percent to USD 26.67 billion by 2026.

Conclusion

To this point, these were the most interesting AI applications in Fintech. However, it's important to note that this list is by no means complete. 

FinTech companies can give more fruitful solutions to financial institutions and end clients if they make more thoughtful and grounded decisions.

Daily, technology advances and improves expected to impact our lives forever. All we must do now is sit back and observe.