(Sriya.AI CEO, Srinivas Kilambi)
The dynamic relationship between financial services and technology products has expanded significantly throughout the years, coining an entirely new industry–fintech. Although financial services groups have long since benefitted from the incredible power of technology for everything from standard processing to identifying efficiency gains, the growing market of top-of-the-line artificial intelligence products is redefining operations in one of the world’s oldest and most widespread industries. Sriya.AI, an emerging leader in numerically inclined artificial intelligence solutions, is empowering financial groups to drastically improve their internal operations while mitigating key risks associated with the industry.
Financial companies support global operations while managing the needs of everyday individuals, as well as core business leaders in every industry. Managing the flow of money, supporting the stock market, and keeping highly sensitive information secure involves several moving pieces, which is why financial groups have long since turned to technology to help mitigate human error while gaining key efficiencies. Today’s top financial companies have several areas of focus where improvements need to be made, including the loan approval process, reducing payment processing errors, and detecting instances of fraud as quickly as possible. With the support of Sriya.AI’s patent filed AI Square algorithm, companies can gain actionable insights into all of these areas and more with 95-98% accuracy and 99% precision.
“Improving outcomes for these critical processes offers an enhanced customer experience while increasing revenue and decreasing losses,” says Srinivas Kilambi, CEO of Sriya.AI and inventor of AI Square. “Each of these areas can be broken down into numbers, and our algorithms can turn data from any financial company into a clear source of innovation.” Financial services companies collect data with every customer interaction and employee action. Sriya.AI’s system, which includes 5 US provisional patents and has already revolutionized operations at more than 25 companies, leverages its own creation–large numerical models–to empower businesses to detect fraud and accurately identify high-risk borrowers with up to 100% accuracy.
Behind these high-value insights is Sriya.AI’s agnostic Machine Learning tool, which has nearly perfect accuracy and precision while requiring 30 times less data than today’s traditional models. AI Square leverages a company’s unique data, allowing it to check, fix, and use data to increase its value over time. Rather than just providing analysis and insights, Sriya.AI products allow AI to learn from AI to provide tailored insights that continue to improve over time. These developments are what separate large numerical models (LNMs) from large language models (LLMs), placing a distinct focus on improvements with accuracy to learn, grow, and optimize business outcomes. The return on investment (ROI) for Sriya.AI begins immediately, whether the system is detecting over 2000 extra fraudulent transactions or reducing the total number of customers with late payments by over 5,000 through enhanced risk assessment.
Artificial intelligence solutions are changing business operations all around the world, but many traditional models, while revolutionary, are facing emerging problems. Extractive AI-ML solutions have low accuracy and precision due to the high volume of interdependent features. Generative AI lacks effectiveness and creativity with numbers, leading to generic or even unreliable outcomes (hallucinations). With 99% of business functions being centered around numbers and data, the limitations of these systems are clear. By contrast, large numerical models place numbers front and center, offering support for data sets of varying sizes while introducing reliable and creative analytical solutions that offer an incredible understanding of core business operations. With these values, financial companies can quantify every move they make, allowing them to constantly identify new areas for innovation that support better security and a more positive customer experience. Remember, what cannot be measured can’t be improved. Businesses need AI with improved analytical accuracy, and Sriya.AI’s LNMs were made to support this function while offering an area under the ROC curve (AUC) of 0.98-1 across all test cases.
Interpretations based on patterns in data can lead financial services groups to gain or lose money depending on their accuracy. When a lender approves a loan for someone based on an inaccurate risk assessment, large amounts of money can be lost. Processing errors that lead to adjustments come at the expense of the business, not the customer. Fraud can lead to substantial losses and cause a poor experience for a valued customer with lasting implications. At the end of the day, reducing risk in these select areas is the key to remaining competitive in the rapidly changing financial industry. From improving customer retention to increasing informed decision-making, artificial intelligence can support financial groups starting on day one. Sriya.AI shows that these changes are possible and achievable with the right approach to AI solutions.
Company: Sriya.ai
Contact: Srinvas Kilambi
Website: https://sriya.ai
Email: sk@sriyaai.com
Source: McMillanMethod
Release ID: 1013331
