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J.P.Morgan and unsupervised machine learning for contracts
J.P.Morgan, as many other financial institutions are investing heavily in technology. For J.P.Morgan this resulted in the development of the COiN platform, an internally developed unsupervised machine learning platform for the analysis of contracts.
As an example, we recently introduced COiN, a contract intelligence platform that uses unsupervised machine learning to analyze legal documents and to extract important data points and clauses. In an initial implementation of this technology, we can extract 150 relevant attributes from 12,000 annual commercial credit agreements in seconds compared with as many as 360,000 hours per year under manual review. This capability has far-reaching implications considering that approximately 80% of loan servicing errors today are due to contract interpretation errors.
Machine learning in the financial sector
Machine learning is, and will be for a long time, a disruptor that shakes up traditional ways of working in the financial industry. The financial sector is traditionally a sector which is rich on data. We already have seen the adoption of big-data based analysis in the past picking up rapid speed at financial institutions, now we see the adoption of machine learning picking up in the same sector.
