Tag: Financial Sector

How AI is empowering digital lending platforms

The financial sector has been witnessing revolutionary growth due to the evolution of digitisation. Artificial Intelligence and Machine learning-powered systems are becoming an essential part of all financial institutions’ decision-making process. AI and ML-based products are significantly changing the digital lending landscape where startups and companies are leveraging AI to build better lending solutions while working alongside banks, NBFCs and other financial institutions.

Below, we look at the leading fintech startups that utilise AI and machine learning to accelerate the credit economy.

Capital Float

Capital Float was established in 2013 to aim to scale retail lending in India by offering flexible and short-term loans to SMEs. Since then, the company has developed various customised working capital finance products for traditionally segments like small retailers, franchisees and proprietors that have often been ignored due to high operation costs. Capital Float’s initial focus was bridging the MSME credit gap by using best-in-class technologies. The company has been providing loans that can be used to acquire inventory, optimise cash cycles and service new orders.

AI and ML models have played an integral role in the growth of the lending firm. Its small-ticket loans are fully automated and built using AI. The company uses AI-based algorithmics to generate users’ financial insights, which in turn helps the company offer customised credit facility as per the needs of the customer. Capital Float has also developed an in-house, industry-first early warning signal system using ML-based sophisticated collections stacks.

Valyu.ai
Valyu.ai is a Gurugram based FinTech startup founded by Rashoo Kame and Gaurav Kumar in April 2020. In a nation where nearly 70% of employees live paycheck to paycheck, Valyu has set out to reduce employee financial stress by providing employers with a holistic approach that addresses financial wellbeing issues at its core.

Valyu.ai is leveraging AI and Machine Learning to provide advanced salary solutions that can help companies alleviate their employees’ financial worries by providing them early access to their earnings & help companies create a financial care framework. Valyu.ai proposes to render 100% digital and automated experiences to all its clients and users. Their algorithm is based on AI and ML. The ML-based rules engine works 24×7 to monitor the risk profiles of their existing customers. The systems look at each customer individually and work to provide a product configuration that can meet the individual’s specific needs and circumstances.

NBFCs like Kudos Finance & Investments and Arthmate (Mamta Projects) have joined hands with the startup as financing partners. It has also tied up with People Strong as their channel partner. The company envisions reducing employees’ financial stress and ensuring their financial wel lbeing by providing quick and easy access to liquidity and advance salary in times of need. It currently services 10 lakh employees nationally and plans to increase its reach to 25 lakh employees from more than 1000 brands in the next two quarters. In the next five years, the company is targeting to disburse INR 2,500 crores. Employers can avail the Advance Salary solution for employees by registering with the Valyu.ai platform.

Jiffy.ai
Jiffy.ai, headquartered in California, was founded by Babu Sivadasan that is working to accelerate human-machine collaboration. The company has developed a no-code development platform for enterprise automation. Jiffy.ai’s revolutionary app-based intelligent automation platform turbo-charges productivity, transforms complex processes, and helps teams unleash their creativity and innovation.

Jiffy.ai uses AI-powered machine learning, cognitive processing and Natural Language Processing to provide an integrated automation experience. The automation removes mundane, error-prone tasks from the workforce, allowing employees to focus on higher-value strategic and innovative work. JIFFY.ai’s clients include Southwest Airlines, which has used the platform to automate its supply chain processes, revenue accounting, and operating groups. Since the pandemic began, JIFFY.ai has seen a lot of traction for their platform as large companies tried to transition to remote working seamlessly and needed automation to ensure that their central and back-office processes are being done promptly and accurately.

LendingKart
Lending Kart was founded in 2014 to address the various inefficiencies that mar the Micro, Small and Medium Enterprises’ lending space in India. The company has so far given out nearly 70k loans to more than 64k MSMEs. The company has set itself apart from other lenders in the market by developing a robust digital origination system and automated credit decisions based on AI. The company prides itself on acquiring and servicing MSME customers at India’s remotest places using its digital reach. Supply chain finance, term loans, line of credit are a few of the most popular products that can be availed from its website that is available in 7 vernacular languages. Lendingkart uses AI to predict accounts that are likely to go delinquent in advance. It has also built a state-of-the-art data infrastructure, which helps capture every interaction with the customer.

2020 Top Five Financial Sector Security Challenges

Security measures within the financial sector have evolved dramatically, with regards to combining elements such as key codes, two-factor authentication, voice ID, behavioural analysis, one-time passcodes, protective messaging, digital fingerprinting, and so on. But, with more security measures in place, there are arguably more elements to infiltrate.

This week SecurityHQ released a white paper on the ‘Financial Sector, Threat Landscape 2020’. In this paper, and through an analysis of a real-life threat to a large financial client, their findings revealed the five top security challenges that the financial sector is currently facing, the risks of future threats, and how to spot these risks before it is too late.

Among other elements, five of the top challenges to the financial industry include ransomware attacks, internal threats, issues in app developments, changes in working due to COVID-19, and third-party risks.

Ransomware
In the three years since the term was added to the dictionary, ransomware has increased dramatically both in terms of the number of attacks, but also in terms of the range of methods used to conduct said attacks. Attackers are extremely sophisticated. Once they have your data, there is no guarantee that if you pay them, that your data will be given back or decrypted. There is also no guarantee that you will not be a target a second time around. Often, once an attack is made, the bad actor will sell the details on to their associates to go after the victim again after deployment, because the payload can still be there, activated and deactivated.

Internal Threats
According to the Verizon, 2020 Data Breach Investigations Report (DBIR) ‘employees’ mistakes account for roughly the same number of breaches as external parties who are actively attacking’ the organisation. In fact, misdelivery within the company, by which information has inadvertently been sent to the wrong person, appears to be the most common issue within insider threats. Misdelivery can occur via emails forwarded or sent to the wrong person/recipient, or by incorporating the wrong mailing list, or via the wrong address on a paper document. Misdelivery is, more often than not, accidental and non-malicious, but the effects can be devastating. Especially if sensitive data is inadvertently shared to the wrong recipient.

App Developments
Apps surrounding investment and finance have grown substantially in 2020. This, in part, is a good thing, as the ability to invest online is quick and easy, and accessible to all. But due to the demand, many of these apps were developed quickly and are underprepared for cyber-attacks. Many do not provide two-factor authentication, are not supported by the appropriate regulations, are not patched or maintained properly, and do not have contingency plans in place to mitigate the effects of a cyber-attack. As a result, personal information of app users is relatively easy to steal and sell. This can be done by creating duplicate fraudulent apps to trick the user. On these duplicate apps, the imagery and language of the genuine app is mirrored. And, once the personal information is supplied, both real and virtual money is then accessible. Thus, the circle of ransomware ensues.

Third-Party Risks
These days, few organisations work on their own. The majority use third parties, including vendors, partners, e-mail providers, service providers, web hosting, law firms, data management companies, subcontractors and so on. With regards to many of these, from IT systems to sensitive information shared with legal teams, these third parties could easily be a backdoor into your financial systems for attackers to infiltrate.

COVID-19
Cybercriminals are continuing to target the financial sector amidst the pandemic. As a result, we have seen a spike in attacks on banks, financial organisations and the third parties connected to them. Before COVID-19, if an attacker wanted to sabotage a company or steal data, they would target the business itself. The website, the social accounts, the logins and all their vulnerabilities. In response, organisations had parameters set up for this. But now, you just need to target a single remote worker.

In response to these five threats, banks and financial institutions require tailored and sophisticated security to support their systems and people and to defend against an onslaught of complex and aggressive cyber-attacks. Not only must security compliance within the financial sector by tenfold, but it is essential that security precautions evolve, to mirror the growing threat landscape.

To read more about these threats, to explore a real-life analysis within the financial sector, and to learn how to mitigate your industry-specific threats, download the white paper here.