Taktile Makes It Easier to Leverage Machine Learning in Financial Industry

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Image source: Techcrunch

Taktile is a new startup developing a machine learning platform for the financial services industry. This isn’t the first firm to want to use machine learning to develop financial products. Taktile, on the other hand, wants to set itself apart from the competition by making it much easier to get started and switch to AI-powered models.

Some startups chose to focus on the financial industry in particular a few years ago, when “machine learning” and “artificial intelligence” could be found in every single pitch deck. It makes sense because banks and insurance companies collect a large amount of data and have extensive knowledge of their customers. They could use the information to develop new models and machine learning applications.

New fintech firms formed their own data science teams and began developing machine learning algorithms for their own products. Predictive risk tools are used by companies like Younited Credit and October to make better lending decisions. They’ve created their own models, and when they run them on historical data, they can see that they work well.

But what about the financial industry’s stalwarts? A few startups have developed products that are compatible with existing banking infrastructure. Artificial intelligence can be used to detect fraudulent transactions, predict creditworthiness, and detect fraud in insurance claims, among other things.

Some of them have done well, such as Shift Technology, which specializes in insurance. However, many startups create proofs-of-concept and then abandon them. There are no long-term business contracts on the horizon.

Taktile hopes to overcome this barrier by developing a user-friendly machine learning product. Index Ventures led a $4.7 million seed round, with participation from Y Combinator, first minute Capital, Plug and Play Ventures, and several business angels.

Both off-the-shelf and custom-built models are supported by the product. Customers can personalize those models to meet their specific requirements. Taktile’s engine is in charge of deploying and maintaining models. It can be deployed in a customer’s cloud or as a SaaS application.

After that, you can use API calls to access Taktile’s insights. It works similarly to incorporating any other third-party service into your product. With explanations for each automated decision and detailed logs, the company attempted to provide as much transparency as possible. Taktile supports data warehouses, data lakes, ERP, and CRM systems as data sources.

The startup is still in its early stages, so it will be interesting to see if Taktile’s vision comes to fruition. However, the company has already managed to persuade a few seasoned investors. As a result, let’s keep a closer eye on them.

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