Taktile makes it Easier to Leverage Machine Learning in the Financial Industry

Taktile makes it Easier to Leverage Machine Learning in the Financial Industry

Meet Taktile, a new startup working on a machine learning platform for financial services firms. This is not the first company that wants to use machine learning for financial products. But Taktile wants to differentiate itself from competitors by making it easier to start and switch to AI-powered models. A few years ago, when you could read ‘Machine Learning’ and ‘Artificial Intelligence’ in each pitch deck, some startups chose to focus specifically on the financial industry. Banks and insurance companies collect a ton of information and know a lot of information about their customers.

They could use that information to train new models and roll out machine learning applications. The new fintech companies are assembling their own in-house data science team and start working on machine learning for their own products. Companies like United Credit and October use predictive risk tools to make better lending decisions.

They have created their own models and they see that their models work well when running on past data, but what about legacy players in the financial industry? Several startups have worked on products that can be integrated into existing banking infrastructure. You can use artificial intelligence to detect fraudulent transactions, predict achievement, and detect fraud in insurance claims.

Some of them have been enriched, such as shift technology with a particular focus on insurance. But many startups create a proof-of-concept and stop there. There are no meaningful, long-term business deals on the road. Tactile wants to overcome a barrier that is easy to accept by creating a machine learning product. It has raised $4.7 million in seeds, led by Index Ventures, with the participation of Y Combinator, First Minute Capital, Plug and Play Ventures, and several business angels.

The product works with both off-the-shelf models and customer-built models. Customers can customize those models depending on their needs. The models are installed and maintained by Taktile’s engine. It can run in the client’s cloud environment or as a SaaS application. After that, you can enjoy the insights of Taktile’s using API calls. It works a lot like integrating any third-party service into your product. The company has tried to provide as much transparency as possible with the interpretation of each automatic decision and detailed log.